CONFERENCE AGENDA

Industrial automation has reached an inflection point. Warehouses and factories are no longer limited by the availability of robots but by how well those robots, systems, and people work together. As organizations scale automation across vendors, sites, and workflows, complexity quietly becomes the biggest bottleneck.

This session explores a fundamental shift underway in the automation industry: moving from isolated robot deployments to intelligent orchestration. Drawing from real-world enterprise implementations across manufacturing and intralogistics, the talk reframes automation not as a hardware challenge, but as a systems and decision-making problem.

Attendees will learn why traditional fleet-level optimization fails in multi-vendor environments, how orchestration platforms unlock hidden throughput without adding robots, and what it takes to create a single operational “brain” across AMRs, AGVs, conveyors, PLCs, and WMS/MES layers. Through simple analogies and practical examples, the session demystifies complex automation concepts and shows how orchestration enables resilience, scalability, and faster ROI.

This presentation is for automation leaders, system integrators, and operations teams who want to scale automation intelligently without replacing existing investments. The goal is not to sell technology, but to offer a clear mental model for how the next decade of automation will be built.

Factory conditions change constantly: lighting, surface texture, process flow, even product geometry. Traditional “train-once, deploy-forever” machine-vision systems degrade as this drift accumulates. The emerging solution is self-learning vision, inspection systems that use structured feedback to refine their understanding over time in a safe and explainable way.

This session examines how feedback and operational experience can power the next frontier in machine perception without revealing any proprietary algorithms. We’ll explore the building blocks that let AI vision evolve responsibly in real manufacturing:

• Feedback as fuel: how operator reviews, sensor signals, and production metadata inform adaptive calibration.
• Model stability and drift detection: monitoring subtle appearance shifts before they erode accuracy.
• Governed adaptation: using validation gates, shadow testing, and audit trails to control self-updates.
• Human-AI collaboration: designing interfaces that let humans steer learning without re-labeling entire datasets.
• Edge and cloud synergy: maintaining low-latency inspection while synchronizing improvements enterprise-wide.

Metrics that matter: evaluating performance not by offline accuracy alone but by sustained First Pass Yield, reduced false rejects, and uptime stability.

Attendees will gain a design-level understanding of how self-learning architectures extend the lifespan of deployed AI systems, reduce manual retraining cycles, and improve trust in automated inspection. The talk also covers best practices for governance, change control, and validation to ensure that learning remains transparent and auditable in regulated manufacturing settings.

Whether you are an AI engineer, system integrator, or operations leader, you will leave with a clear framework for turning field feedback into continuous improvement and a vision of how adaptive AI can make factories more resilient, efficient, and intelligent over time.

Manufacturing is being redefined. As automation, AI and additive manufacturing converge, companies are no longer achieving scale through size alone – they’re achieving it through software. The ability to connect, adapt and use AI to reconfigure production digitally is now the true measure of competitiveness.

In this session, Tom Kelly, CEO of Automation Alley, will explore how this software-first mindset is transforming the business of making things. He’ll challenge attendees to look beyond automation as a collection of machines or systems and instead see it as a living, data-driven framework that powers flexibility, speed and collaboration across the entire value chain.

Drawing on Automation Alley’s experience helping thousands of Michigan manufacturers navigate digital transformation, Tom will share real-world lessons from Project DIAMOnD, the nation’s largest distributed 3D printing network. This initiative connects hundreds of small and medium-sized manufacturers, empowering them to fulfill orders collaboratively and scale production through digital coordination rather than costly physical expansion.

Example real-world case studies include:

• Zero Tolerance LLC (Clinton Township, MI): Used its Project DIAMOnD 3D printer to design a hand-held insert tool called “The Claw,” reducing each molding cycle by eight seconds and increasing throughput without new capital investment.
• Air & Liquid Systems (Rochester Hills, MI): Replaced a $100 stainless-steel component with a $1 carbon-fiber version printed in-house – cutting costs and inspiring a company-wide culture of digital experimentation.
• Project DIAMOnD Network – Ukraine Response: When the Ukrainian Defense Ministry urgently needed 3D-printed tourniquet clips, Michigan manufacturers within the network produced and shipped 8,000 parts in days, demonstrating the scalability and humanitarian impact of distributed manufacturing.

In this session, attendees will learn how manufacturers can use automation and AI to:

• Scale through a distributed network: Build capacity, not by expanding plants, but by connecting systems and data for adaptive production.
• Unlock new agility: Use predictive analytics, generative design and digital twins to iterate faster and respond instantly to change.
• Empower people: Equip the workforce with tools that elevate creativity and problem-solving instead of replacing human expertise.
• Build distributed resilience: Reduce supply chain risk through decentralized, connected manufacturing networks.
• Adopt a continuous innovation culture: Shift from one-time technology investments to an agile, software-driven approach to progress.

This is not just an evolution of the production line, it’s a revolution in how we define value, scale and competitiveness. The software-first factory doesn’t replace what makes manufacturing strong; it enhances it. By integrating AI, automation and data at every level, manufacturers can achieve scale that is smarter, faster and more sustainable than ever before.

Drawing from Automation Alley’s hands-on work with manufacturers, Tom will show how embracing digital thinking can turn automation and AI into the foundation for sustainable growth.

Effective communication is the foundation of successful automation projects, shaping everything from technical problem-solving to project delivery and collaboration across engineering disciplines. In a world where manufacturing lines and automation systems are becoming increasingly sophisticated, traditional verbal and written communication often falls short in conveying the nuances of complex machine behavior. Traditionally, 2D drawings served as the universal language of design, but these static images contain limited information, offering only flat, isolated views that require skilled engineers to mentally reconstruct complex shapes and interactions. The move to 3D CAD transformed this landscape, adding depth, scale, and detail. Three-dimensional models let teams visualize assemblies and mechanisms from multiple perspectives, greatly improving everyone’s ability to share and understand designs. Yet even 3D CAD falls short when projects demand a complete understanding of dynamic systems. They can be limited in demonstrating how machines move, interact, and function under real operating conditions. Enter virtual commissioning: the next major leap in engineering communication. By animating digital models, emulating control logic, and harnessing real-time data, virtual commissioning provides a far richer and more interactive medium. It enables teams to see a machine “in action” before it’s built, validating concepts collaboratively and catching errors early. Just as 3D CAD once revolutionized design by revealing what 2D could not, virtual commissioning goes further by showing the actual behaviors, timing, and logic that ultimately drive project success.

This session will demonstrate how virtual commissioning enhances communication from multiple perspectives: accelerating issue identification, reducing the time and cost of design changes, and enabling seamless collaboration between previously siloed teams. Real-world examples will show how cycle time simulations help engineers relay design confidence, how collaborative emulation environments foster interdepartmental problem-solving, and how immersive technologies like VR and AR offer new ways for operators and stakeholders to engage with designs long before equipment reaches the floor. A collection of video clips will illustrate these concepts, emphasizing how virtual commissioning transforms static project documents and CAD drawings into dynamic, interactive models for review, training, and integration. Attendees will learn how improved communication via virtual tools minimizes commissioning risks, increases quality, and shortens deployment cycles, positioning organizations at the forefront of advanced manufacturing. Join to experience how digital transformation and virtual commissioning work together to turn communication barriers into bridges—driving clarity, speed, and success in today’s automation projects.

Many assume Return on Investment (ROI) is the primary factor businesses use to justify purchasing a collaborative robot (cobot). This belief is reinforced by the prevalence of ROI calculators found on nearly every cobot manufacturer’s website. While ROI can be a useful metric, it is not the most common or most influential reason companies decide to implement cobots. In fact, ROI-based justification is often among the least common in real-world adoption. In this presentation, we’ll explore the actual drivers behind cobot investment decisions—factors that often deliver greater strategic value than simple financial returns. Using real-world case studies, we’ll discuss how companies are increasingly justifying cobot deployment based on:

• Labor shortages and workforce challenges – Addressing the difficulty of finding and retaining workers for repetitive or ergonomically risky tasks.
• Flexibility and scalability – Leveraging cobots’ ability to be reprogrammed, redeployed, and adapted for changing production needs.
• Improved quality and consistency – Reducing variability and human error to enhance product quality and throughput.
• Employee safety and satisfaction – Enhancing workplace ergonomics, reducing injuries, and creating more engaging work for human operators.
• Speed of deployment and ease of integration – Minimizing downtime and capital risk through quick setup and reconfiguration.

These non-financial justifications often deliver benefits that are harder to quantify but far more sustainable over time. As such, they are expected to be the main forces driving the growth of the cobot market over the next five years.

The Control of Hazardous Energy Lockout, Tagout & Alternate Methods (ANSI Z244.1)

Alternative Methods:
Lockout or tagout shall be used unless the user can demonstrate an alternative method will provide effective protection for persons. When lockout or tagout is not used then alternative methods shall be used only after the hazards have been assessed and risks documented.

Risk Assessment:
Selection of an alternative method shall be based on a risk assessment of the machine, equipment or process & shall take into consideration that existing risk reduction measures provided with the machine, equipment or process may need to be removed or modified to perform a given task.

Omron Senior Product Management will share a practical roadmap for creating a data-first culture that reduces the cost and complexity of deploying advanced process controls. While much attention has been given to algorithm development and deep neural networks, this session focuses on the critical foundation for successful AI adoption in factory operations.

Manufacturers face unprecedented pressures: volatile supply chains, unpredictable consumer demand, and relentless shareholder expectations. Competitive advantages increasingly depend on flexible yet consistent production, and the key to achieving this lies in leveraging AI strategically, not as a future concept, but as a tool built on robust data. Data that creates immediate operational resilience.

This session will guide attendees through three milestones of advanced process control maturity:
1. Foundational Data – How to capture high-value process insight non-intrusively.
2. Prototype AI – How to create robust designs for edge deployment.
3. Scaled AI – How to methodically deploy without ripping and replacing current automation.

By framing these concepts within operational efficiency, the session will illustrate how an intentional data-first strategy can strengthen production systems today while preserving flexibility for advanced process control tomorrow. Attendees will leave with actionable steps to maximize uptime today through non-intrusive data collection and be able to avoid costly challenges when seeking to build a scalable intelligent automation architecture.

Industrial Robots are at the heart of Lean Manufacturing and are vital to the current vibrant manufacturing economy in North America. The “Getting Started with Robotics” presentation is an introduction to the Industrial Robotics or Flexible Automation Industry. We will explore Robot Based Automation Systems to include how the industry functions, why to choose robot based automation, principles of system integration, general principles of robot technology, the business case for automating and calculating ROI plus the common mistakes made in Robot Integration. The attendee will learn through discussion and evaluating system photos and videos illustrating various robotic based flexible automation systems.

Robots are evolving from programmed ROS applications to embodied AI (LLMs running on physical robotics hardware) solving missions. New robotics AI tools are evolving such as VLMs (Vision Language Models also called multimodal LLMs), VLAs (Vision Language Action models), and MCP (Model Context Protocol) servers. Robots now stream sensors like RealSense depth cameras into these AI tools allowing the AI to figure out on its own how to move its wheels or legs to achieve a goal such as following a person. During this session, we will build an embodied AI experience together live on stage! What could go wrong?!

What if manufacturing engineers, operations leaders, and maintenance teams could all work from the same living digital model of the factory — one that learns, predicts, and explains? In this innovation session, discover how Digital Twin, AI, and Generative AI are being applied from engineering to the shopfloor and beyond. See how the Siemens Factory Twin is continuously synchronized with real operations through Edge, enriched by Insights Hub, and enhanced with Senseye for AI-driven asset intelligence — creating a true closed-loop digital twin and delivering high-value outcomes at scale.

What questions will we answer together?

• How can GenAI support manufacturing engineers in validating changes before deployment?
• How do operations teams use live digital twins to optimize throughput in real time?
• How can maintenance teams predict failures earlier and act with confidence?
• What does it take to scale this across lines, plants, and teams to deliver high-value outcomes?

Powered by data, AI, and digital twins, join us to see how these roles come together.

As industrial automation systems become increasingly software driven, connected, and intelligent, cybersecurity is emerging as a defining factor in product quality and global competitiveness. The European Union’s Cyber Resilience Act (CRA) represents a significant shift, introducing binding security requirements for all connected digital products, including those that power automation, control, and industrial IoT systems.

This session translates the implications of the CRA into actionable insights for automation stakeholders. It examines how its core principles of secure by design development, vulnerability management, and lifecycle security can strengthen not only regulatory compliance but also operational resilience and customer trust across global markets.

Attendees will learn:

• How the CRA redefines software accountability for automation and industrial control products
• What automation suppliers, integrators, and OEMs can do today to align with emerging global standards
• How to embed security by design practices in automation and control software development
• Practical approaches to managing third party components, open source dependencies, and post market vulnerabilities
• Lessons learned from early adopters building secure, resilient automation ecosystems

Whether your systems ship globally or you are preparing for future United States cybersecurity regulation, this session will provide a clear and practical framework for building more trustworthy automation solutions without slowing innovation.

It's an exciting time in maintenance, it is experiencing rapid development in concepts, technologies and solutions. New and innovative approaches are being implemented based on the merging of new technologies (IIoT/cloud, sensors, controls, networks, software, AI) with older, data-driven maintenance practices started by the Royal Air Force in World War II.

I’ll review some of the challenges faced by today’s manufacturers (scarce labor, rising costs, supply chain issues, trade/tariffs, demand for faster deliveries, etc.) and how a focus on Overall Equipment Effectiveness (OEE) can help them address these challenges. Maintenance plays a key role in the components of OEE: Availability X Performance X Quality; and data is the critical component in efficiently managing manufacturing and warehouse operations.

I’ll then explain the historical basis in the RAF’s shift to a data-driven approach to maintenance and asset utilization, when a critical phase of the war forced reevaluation of practices. Analysis revealed that scarce resources (airplanes and people) were being constrained by traditional maintenance methods and allocation – and a data-driven approach yielded unexpected findings and dramatic improvements in availability, performance and quality.

I’ll connect the RAF’s lessons to today’s situation and discuss how manufacturers are applying similar data-driven solutions to optimize maintenance and asset allocation. Our advantage over the RAF is that we can gather, and analyze, more and better data directly from our assets using smart sensors, industrial networks, IIoT edge gateways, cloud tools and software/AI and dramatically improve our systems’ performance, addressing the many challenges manufacturers face.

As automation continues to transform how goods move through warehouses and distribution centers, material handling remains a critical frontier. In this session, Ahmad will explore how autonomous forklifts are shaping the future of logistics and how organizations can successfully plan, implement and scale them. Attendees will walk away with insights into:

• The core technologies behind autonomous forklifts—navigation, sensing, control and integration with warehouse systems.
• Key operational considerations—site prep, safety, workflow adaptation and fleet management.
• Business value and ROI metrics—how to quantify the benefits in throughput, labor reduction, asset uptime and safety improvements.
• Real-world deployment lessons—obstacles faced, lessons learned and best practices for scaling from pilot to full fleet.

Whether you’re already exploring driverless material-handling solutions or seeking to understand how to integrate them into your operation, this session will provide practical knowledge and strategic guidance to make autonomous forklifts a tangible reality in your facility.

Autonomous robots are reshaping warehouse operations, but robot-only perception can fall short in complex, dynamic environments. This session explores how to take an infrastructure-first safety approach using NVIDIA Halos Outside-In Safety Blueprint, based on IGX, to augment robot awareness beyond onboard sensors to extend functional safety and maximize throughput.

By integrating fixed cameras, real-time perception, and centralized safety orchestration, industrial safety agents can monitor and guide entire fleets with constructs like adaptive zones, virtual boundaries, and event-driven triggers.

Discover how this approach improves operational flow, minimizes unnecessary interruptions, and supports safer human–robot interaction. Real-world examples include automated trailer loading and intelligent zone management with AI-level agentic reasoning.

While automation has matured in electronics manufacturing, it remains constrained by deterministic programming that fails the moment it encounters the high variability of modern assembly and end-to-end testing. These systems don’t adapt or learn, remaining fixed in value. To enable adaptive production, we need a global shift toward an industrial AI architecture that solves the high-value bottleneck that is dexterous cable management and insertion.

In this panel, senior staff roboticist Jimmy Baraglia, explores how the Intrinsic AI for Industry Challenge is accelerating this transition and how this challenge emulates the future of intelligent solution design.

Dr. Baraglia, will share his insights into running the global robotics Challenge. Providing salient information about the tips and approaches to consider when setting up a challenge like this, and what pitfalls to be aware of.

He’ll discuss unlocking developer talent, using open source tools and Intrinsic's platform to solve valuable, currently unsolved problems, and touch on how to set up an impactful evaluation committee.

Time-of-Flight (ToF) cameras are revolutionizing 3D imaging and automation with their ability to rapidly measure depth and spatial geometry. This talk presents an in-depth look at the physics underlying ToF technology, explaining how pulsed and modulated light sources are used to measure return times and compute distance. Attendees will learn about key adjustable parameters—such as modulation frequency, integration time, illumination power, and ambient light compensation—and explore the impact of each on system accuracy, range, resolution, and artifact mitigation. The session will provide a comparative overview of commercial ToF cameras, highlighting differences in sensor architecture, calibration strategies, and use cases. Additionally, practical guidance will be given on converting depth maps into point clouds for 3D analysis, and on interpreting the capabilities and limitations of ToF imaging—addressing scenarios such as translucent surfaces, multi-path interference, and material reflectivity. Through real-world examples, participants will gain actionable insights for selecting and deploying ToF cameras in demanding automation, robotics, and industrial workflows.

Improve any manufacturing process with IO-Link sensors and other devices. As IO-Link passes is 12th year as an IEC standard, we have many real-world examples and use-cases to explore. Discover proven ways OEM’s and production facilities have used this technology to help their bottom line.

Many went to IO-Link to save wiring cost of analog sensors. The savings on just PLC analog input modules was enough to justify trying a new way. Additional diagnostics were hard to quantify. Now, a dozen years later, OEMs and production facilities have discovered and measured the benefits.

Once manufacturers used new machines with IO-Link, they experienced reduced downtime. Traditionally, the non-default parameters of configurable sensors might be in the schematics or drawing package. Seldom were they updated when the process was optimized. Hot swapping sensors and automatically loading the saved parameters is a game changer.

Utilize the higher accuracy available compared to the old 4-20mA signing. That technology had not been updated since the mid-1900s and is still in use today.

Leverage predictive maintenance. Get data from sensors into a database without additional PLC programming. Use AI to spot patterns from saved data.

Other devices that are configurable benefit from IO-Link also. Examples include smart-cameras, code readers, circuit breakers, and power supplies.

Attend this session to discover ways others have improved their manufacturing process, and ways you can apply similar ideas to improve your own.

Artificial intelligence (AI) promises better, more human-like decision-making and more autonomous operation, yet 87% of industrial AI initiatives never make it to production.

This course explains how to create deployment-ready autonomous systems that incorporate engineering expertise to optimize complex and high-value industrial processes. The key is modular multi-agent systems that combine AI’s power to learn with existing automation, which has already been using software agents successfully for generations. The result is reliable, explainable systems that can automate processes that could never be automated before.

This introductory course is for all industrial automation stakeholders: plant and line managers, engineers, data scientists, and executives. You’ll walk away understanding the industrial and agentic AI landscape and ready to select technologies, service providers, and vendors to put high-performing AI into production.

The rapid development of digital technologies and the Industrial Internet of Things (IIoT) are the drivers of the industrial revolution currently taking place under the name "Industry 4.0". In the course of this, advanced manufacturing technologies are being combined with IIoT systems with the goal of automated, unmanned production. The necessity for this change results from the constantly growing requirements for accuracy, efficiency as well as flexibility of production processes in combination with the already highly acute shortage of skilled workers. A key technology for meeting these challenges are intelligent monitoring systems that provide quantitative information about the condition of machines and processes. The transparency thus created enables data-based decisions regarding intervention in manufacturing systems. The talk will cover how to enable machine tools for such cognitive autonomous decision making and give application examples.

Preparing a facility for automation is often more complex than selecting the right equipment. It requires the right data, the right processes, the right infrastructure—and the right expectations. In this educational session, two end user customers and JBT will break down the foundational steps every engineering and operations team must take before launching an automation initiative.

Drawing on lessons learned from real implementations, the panel will cover the technical, operational, and organizational requirements that determine whether automation deployments run smoothly—or stall before they begin. Topics include assessing process readiness, facility layout considerations, data and system requirements, safety planning, change management essentials, and how to build a roadmap that balances quick wins with long term scalability.

Engineers and plant managers will gain practical guidance on:

• Evaluating manual workflows to identify automation ready use cases
• Preparing facility layouts, traffic flows, and infrastructure for AGVs/AMRs
• Understanding WMS/ERP integration needs and data dependencies
• Planning for safety, communication protocols, and operational redundancy
• Aligning internal teams and building a cross functional readiness plan
• Avoiding common pitfalls that slow down first deployments
• Knowing when to pilot, when to scale, and how to measure early success

With firsthand insights from two customers who have navigated this journey—and technical perspective from JBT—attendees will leave with a clear, actionable framework for getting their facility ready for automation and setting their first project up for long term success.

In light of the global adoption of new technologies and standards in 2026 & 2027, the speed of evolution of the collaborative robot or “cobot” has moved faster than most technologies in the manufacturing space. In this session, we will briefly review the historical rise of the collaborative robot and how this space is changing in 2026 and beyond. With a shallow dive into new technology, safety & cybersecurity standards that should be easy to follow for a novice, we will start with how collaborative applications, collaborative robots & traditional automation are all changing; and more importantly we will discuss practical steps to take so leaders can take advantage of these changes in their business. Second we will cover how advanced robotics functionalities like dual arm capabilities and mobile robots are utilizing robots designed for collaborative applications to boost productivity and product quality. Lastly we will dive into how industrial robots are utilizing Physical AI tools to bring automation to problems that were previously difficult or impossible to automate. In this fast paced session with agnostic real world examples, attendees will be ready to automate collaborative applications in new and value creating ways.

Machine vision is redefining robotics by enabling systems that not only see but understand and respond in real time. In this session, Rajesh will examine the evolution of vision-guided robotics, where perception, AI inference, and deterministic control converge to deliver advanced inspection, precision handling, and adaptive automation.

Through real-world use cases, Rajesh will show how manufacturers are deploying vision and AI at the edge to enhance quality, consistency, and throughput across diverse production environments. Attendees will gain a clear perspective on architectural design choices that drive performance, scalability, and readiness for more autonomous operations.

Open, software defined automation is transforming how engineers design, deploy, and evolve industrial systems. This session will take a technical deep dive into the engineering advantages unlocked when control moves from rigid, hardware bound architectures to flexible, software-defined environments. Participants will learn how open automation reduces integration effort, simplifies lifecycle management, and accelerates system modifications without the delays and constraints of proprietary platforms.

We will explore how standardized software components, reusable code libraries, and IT friendly engineering tools streamline project execution and reduce commissioning time. The session will also cover how software-defined automation enables easier connection to digital twins, simulation environments, and real time analytics, allowing engineers to test, validate, and optimize designs well before deployment.

Whether you are building your first automated system or expanding a mature operation, this course will provide practical guidance on how open, software-defined automation can increase flexibility, improve maintainability, and prepare your plant for the next generation of digital, intelligent operations.

The Problem
Industrial automation is hitting a "Knowledge Gap." Critical intelligence is trapped in millions of unreadable legacy documents—P&IDs and handwritten logs—forcing technicians to spend 40% of their time searching for data and risking the loss of decades of institutional knowledge as the workforce retires

The Approach
We propose a shift to Multimodal AI Reasoning. This session explores an "AI-Optimized Stack" that enables agents to "see" complex diagrams and bridge the gap between archives and real-time data, evolving from simple search to "Agentic Operations" that plan and execute workflows.

The Evidence

• Scale: UK Power Networks digitized 1.1M historical records in 26 hours—saving 19 years of manual effort.
• Visualization: Using Gemini and Veo to transform 2D diagrams into 3D visualizations for field technicians.
• Retention: Westinghouse surfacing 75 years of nuclear engineering expertise to accelerate construction.

Industrial automation has moved through two distinct eras. In the Hardware-Defined era, rigid PLCs and lengthy deployment cycles made every project a custom build. The Software-Defined era abstracted logic from hardware through cloud-native programming, no-code workflows, and digital twin simulation — but teams still spent months stitching together vendors and engineering tools before a line could run.

A third era is now underway: AI-Defined Automation. In this session, Brendan Sterne, Chief Product Officer at Vention, will discuss how the convergence of unified hardware, software, and AI is collapsing automation timelines from months to days, while reducing integration risk and producing systems that perform reliably from day one.

Attendees will learn how recent advances in AI, simulation, and edge computing make it possible to design, program, deploy and operate automation systems within a unified environment. Through real-world examples, the session will show how manufacturers are deploying robotic applications faster, scaling automation programs with greater confidence, and getting it right the first time.

Traditional industrial robotics has excelled in structured, repetitive manufacturing environments. However, a significant portion of industrial tasks, such as random bin picking, variable assembly, logistics, and material handling in high-mix, low-volume scenarios, remain unautomated due to the complexity and unpredictability of unstructured environments.

Key features discussed will include autonomous adaptivity, allowing the robot to perceive its dynamic surroundings, make human-like judgments, and generate optimal, collision-free paths without being explicitly programmed for every scenario. We will also define AI in robotics and where we see them fitting into the real world. We will present practical examples of Motoman NEXT successfully performing tasks that require human-level perception such as sorting and boxing irregularly placed items, and its ability to operate alongside human workers in flexible, unpredictable workcells.

As manufacturing enters a new era of digital transformation, the role of the frontline worker is being redefined. In this session, Paul Ryznar, CEO of LightGuide, will explore how augmented intelligence—powered by augmented reality (AR) and AI machine vision—is enabling a new generation of connected workers across factory floors, data centers, logistics hubs and other environments.

Attendees will learn how LightGuide’s AR platform overlays interactive workflows directly onto workspaces, guiding operators through complex tasks with precision and speed. When paired with AI-powered machine vision, these systems create adaptive, real-time feedback loops that reduce errors, accelerate training, and boost productivity. Paul will share real-world examples of how leading organizations are using visual guidance and AI machine vision to achieve rapid ROIs by making manual work more engaging, competitive, and rewarding.

This presentation will also dive into the human side of technology adoption, emphasizing that trust, transparency, and intuitive design are essential for empowering—rather than replacing—workers. Whether you're looking to digitize your factory processes, improve quality assurance, or scale training across sites, this session will offer actionable insights and a bold vision for the future of work.

This presentation will provide insight into modern distance measurement technologies and how they can be used to improve automation processes. We will explore a comparison between the different types of sensors and their best practices in distance measurement. The presentation will explore when each technology – including ultrasonic, radar, laser, inductive, and time-of-flight sensors – is most valuable for its specific application, such as inductive technology for metal sensing, ultrasonic sensors for transparent targets and dusty or humid environments, and laser for best-in-class sensing technology in a compact form. Additionally, this presentation will provide real-world examples of how each distance measurement technology has excelled in the past, including applications in quality control, dispensing positioning, and factory automation.

Deep learning is redefining what’s possible in industrial image processing – yet its practical adoption often raises more questions than answers. This session provides an educational overview of how and where AI delivers measurable value in automation, without marketing claims or product focus.

Attendees will learn the core principles of deep learning in computer vision and how these approaches differ from traditional rule-based systems. Using real industrial examples, the talk explores key application areas such as classification, object detection, and segmentation, as well as newer capabilities like out-of-distribution detection and continual learning.

The presentation also addresses practical aspects of deployment – from data quality and annotation strategies to model selection and system integration. Participants will leave with a clearer understanding of when deep learning makes sense, how to get started, and what to expect in terms of scalability and maintenance.

This session is designed for engineers, integrators, and decision-makers seeking grounded, experience-based insights rather than theoretical promises.

As industries accelerate toward electrification and autonomy, one critical challenge stands between innovation and impact: scaling from prototype to production. This presentation explores how smart automation, intelligent data systems, and modular manufacturing design can enable organizations to bridge that gap — with lessons drawn directly from the EV and eVTOL sectors.

Electric vehicles and electric vertical takeoff and landing (eVTOL) aircraft share a common DNA — highly integrated electronics, safety-critical systems, and rapid design evolution. In early-stage programs, most validation and assembly processes remain manual and experimental. But once a product shows market viability, these processes must evolve into repeatable, traceable, and cost-effective production systems.

Through real-world case studies from Rivian and Joby Aviation, this session demonstrates how to transition from lab-scale setups to smart, scalable test and manufacturing architectures. Attendees will see how digital transformation tools — including IIoT connectivity, AI-assisted fault detection, and digital twins — can optimize throughput and reduce risk in production environments.

The presentation also covers the foundational engineering principles behind scalable automation design:

• Modularity: Designing mechanical fixtures, motion platforms, and electrical test racks for reusability across multiple products.
• Smart Data Integration: Leveraging IIoT frameworks to capture real-time metrics and drive continuous improvement.
• Human-Machine Collaboration: Enabling operators, engineers, and AI systems to work synergistically for predictive maintenance and rapid issue resolution.
• Design for Automation: Engineering products and processes that naturally lend themselves to automation, improving yield and flexibility.

Keyur will share lessons learned from building automated test infrastructures that supported hundreds of vehicle ECUs and complex avionics systems. Attendees will gain practical insights into scaling automation responsibly — balancing performance, reliability, and cost.

This session ultimately illustrates how organizations can combine mechanical innovation, digital intelligence, and a human-centered approach to create flexible production ecosystems ready for the next generation of sustainable mobility.

Smart manufacturing is reshaping industries through AI, IoT, robotics, and real-time analytics—creating agile, data-driven operations. But adopting these technologies requires more than innovation; it demands strategic change management to align people, processes, and systems. As factories become smarter and supply chains more predictive, organizations must navigate cultural shifts and workforce transformation. Attendees will gain actionable insights into these trends, learning how to build business cases that resonate with stakeholders and justify capital investments. By understanding the true ROI of automation, they’ll be equipped to lead change and unlock capex funding to future-proof their operations.

Machine vision, in its various forms, has long been a critical tool in automation: empowering manufacturing professionals with advanced technologies that enable a wide range of use cases from quality and assembly inspection to vision-guided robotics - over diverse industry verticals. The path to real and repeatable success, though, with automated imaging solutions may seem elusive, but a short list of key practical "quick steps" can help empower engineers and managers in the implementation of this valuable technology.

This session will examine some of the ways specification, design, and integration help ensure success in automated visual inspection applications. The presentation will provide specific use cases and examples covering both mature components and tools as well as cutting-edge technologies.

Target audience: end-users, systems integrators, engineers, and anyone interested in machine vision success.

Bringing autonomous robots into a live manufacturing environment is fundamentally different from developing them in a lab. Toyota Research Institute has been working side-by-side with Toyota Manufacturing to co-develop robotics solutions and a strategy that enables this difficult leap for our highly autonomous mobile manipulation robots.

This session shares what that process has revealed: the gap between research and production, what real operators actually need from an autonomous system, and what an industry-research partnership could look like. An honest account of progress, setbacks, and what we're learning along the way.

Plus, we will share details on the Mobile manipulation robots we are building to support some of the hardest problems left in manufacturing’s logistics automation pipeline.

Industrial robotics is entering a new phase where openness, intelligence, and collaboration are becoming essential for progress. At the center of this evolution is OPC UA for Robotics, a global interoperability standard that connects robots, controllers, and automation systems across manufacturers and platforms.

This session will highlight how OPC UA for Robotics, developed within the VDMA Robotics + Automation Association together with the OPC Foundation, is shaping the future of communication and control in robotic systems. Built on secure, platform-independent information exchange, OPC UA provides a unified framework for describing diverse robotic systems, from traditional industrial arms to mobile and collaborative robots. With the recent Part 1 Remote Operation update (OPC 40010-1), it now enables standardized monitoring, program management, and control at every level of automation, from the factory floor to the cloud.

The next chapter of robotics will be defined by intelligence and connectivity. As artificial intelligence becomes an integral part of automation, it is increasingly important that robots can be developed, deployed, and optimized within a shared digital ecosystem. This is where initiatives such as the RoX Project come into play. RoX, a BMWK-funded consortium project, is building a decentralized digital infrastructure for AI-based robotics. It focuses on connecting data, models, and services throughout the lifecycle of robotic systems, creating the foundation for scalable, AI-driven automation. Within this ecosystem, OPC UA for Robotics provides the essential semantic and interoperable interface layer, ensuring that robots and AI services can communicate consistently and securely, regardless of vendor or platform.

By linking standardization efforts like OPC UA for Robotics with innovation ecosystems like RoX, the robotics community is laying the groundwork for an open and intelligent automation future. Attendees will gain insights into how standardized semantics and interfaces can reduce engineering effort, accelerate integration, and enable AI-driven robot orchestration. Through practical examples and a forward-looking discussion, this session will demonstrate why OPC UA for Robotics is not just a communication standard, but a foundation for trust, flexibility, and innovation in the age of intelligent automation.

At Automate 2025, we'll explore a groundbreaking shift in industrial automation: the advent of advanced AI agents designed to work seamlessly with control systems engineers. This new technology represents a fundamental change from AI assistants that simply respond to queries to truly autonomous agents capable of proactively executing entire processes with minimal human intervention.

The core of this innovation lies in a sophisticated AI agent architecture featuring an intelligent orchestrator. Much like a skilled craftsman selecting the right tool for each job, this orchestrator deploys specialized AI agents to solve complex tasks across the entire industrial value chain. These agents work autonomously – understanding intent, improving performance through continuous learning, and accessing external tools and other agents as needed.

The session will explore how this technology is automating automation itself. We'll explore AI agents that enhance various aspects of control engineering:

1. Design agents that accelerate product design processes, helping engineers navigate complex data and balance trade-offs across multiple domains.
2. Planning agents that optimize production scheduling and resource allocation, maximizing efficiency and minimizing waste.
3. Engineering agents that generate automation code through natural language inputs, speeding up development while minimizing errors.
4. Operations agents that provide holistic insights into entire plants and offer guidance for shop floor workers, service technicians, and maintenance engineers.
5. Service agents that support the entire maintenance lifecycle, from reactive repairs to predictive and preventive strategies.

The future we envision is one where AI agents work seamlessly alongside human engineers, handling routine processes independently while enabling humans to focus on innovation, creativity, and complex problem-solving.

Join us to discover how this collaborative approach between human expertise and artificial intelligence is set to revolutionize control systems engineering, creating more efficient, adaptive, and innovative manufacturing systems for the future.

Join industry leaders and decision makers to learn and explore how cloud technologies are transforming manufacturing operations, driving efficiency, and unlocking new opportunities for growth. The conversation will spotlight how mid-market companies can accelerate their digital transformation journeys through smart cloud adoption with some real-world customer use cases. Following a brief presentation, attendees will engage in a dynamic interactive conversation to exchange insights, address challenges, and develop actionable strategies.

Nobody wants to be the next headline. As manufacturing becomes the #1 target for cyberattacks, the line between IT and OT has never been more vulnerable. In this session, AMDT shares real-world insights from securing over a million industrial devices worldwide. Discover how production resilience, fast recovery, and intelligent versioning can keep your operations safe, and why the next ransomware attack won’t happen on your watch.

As the reshoring movement gains momentum across the United States, manufacturers are grappling with the harsh realities of labor shortages and the urgent need for high-mix, low-volume production flexibility. To address these hurdles, this session focuses on the practical application of Techman Robot’s Smart Vision and AI-integrated cobots through a series of real-world case studies. We will explore how leading manufacturers have successfully implemented AI-driven automation to transform their production floors and overcome the complexities of bringing manufacturing back home.

The presentation will demonstrate how AI-native vision systems simplify the automation of tasks that were previously too complex or costly, such as precision assembly, intelligent sorting, and automated quality inspection. By showcasing diverse industry examples, we will highlight the tangible benefits of using robots that can "see" and "learn"—specifically how they reduce integration time and empower a less experienced workforce. Attendees will walk away with a clear understanding of how to leverage AI cobots to bridge the productivity gap, mitigate reshoring risks, and build a sustainable, future-proof manufacturing strategy

The traditional industrial robot is an engineering marvel, but a limited one. It can repeat, react, and follow instructions. What it can’t do, until now, is adapt, learn, and optimize in real time.

This session will explore how Xaba is helping global OEMs and integrators bridge that gap. By embedding Physics-Based GenAI directly into the control systems of robots and industrial machines, Xaba unlocks a new class of intelligent automation. These are not just smarter robots; they’re systems that understand the manufacturing context, adjust to real-world variability, and optimize operations without human reprogramming or supervision.

CEO Max Moruzzi will share case studies from Xaba’s work with leading robotics and sensor OEMs, showcasing how manufacturers are using Xaba’s AI platform to:

• Reduce cycle times by up to 80% without compromising precision
• Reduce energy consumption to produce cars, aircraft, or railcars by more than 50% without compromising cycle time or part quality
• Enable machines to self-correct in response to part tolerances, thermal drift, or system wear
• Eliminate the need for expert-level reprogramming when switching between SKUs or materials
• Increase throughput and flexibility in aerospace, automotive, and electronics assembly lines

Attendees will gain a practical understanding of what it takes to deploy this type of intelligence, from sensor stack requirements to integration within existing workflows. Whether you're a systems integrator, factory operator, or tech OEM, this session will show what’s possible when the machine becomes the programmer.

Artificial Intelligence is no longer limited to predictive maintenance or analytics dashboards. A new generation of AI Agents is emerging, systems that can reason, act, and collaborate autonomously within real industrial workflows.

In this session, we’ll explore how AI Agents are transforming the way industrial companies sell, quote, and support automation systems. Unlike generic chatbots, AI Agents can understand technical requirements, access product catalogs, build proposals, and even update CRMs automatically, reducing quoting cycles from days to minutes and freeing engineers to focus on solving real customer problems.

We’ll demystify what AI Agents actually are, how they differ from traditional automation scripts or chat interfaces, and how to deploy them safely and effectively in industrial environments. Through real examples from OEMs, System Integrators, and Distributors, attendees will learn the key steps to integrate agents into existing sales and service processes, what data and infrastructure are required, and the measurable business impact they can deliver.

Whether you’re an executive looking to improve commercial efficiency or an engineer curious about the technical side of agent workflows, this talk will provide a clear, practical roadmap to adopt AI Agents responsibly without the hype.

Mobility is becoming an important part of many integrated manufacturing systems and logistics solutions. This session explores the opportunities created when adding autonomous mobility to your automation menu. We will discuss the key items to consider and pitfalls to avoid when choosing and deploying IMR systems.

Organizations across industries are under increasing pressure to boost productivity, reduce costs, and make smarter investments—and automation has emerged as one of the most effective ways to achieve measurable impact. Yet many leaders still struggle to assess where to begin or how to confidently quantify the return on automation initiatives. In this session, Schneider Electric experts will share a practical framework for evaluating automation opportunities, modeling potential benefits, and building a clear business case for investment.

Manufacturers are constantly looking for ways to improve efficiency and reduce repetitive tasks through robotics, but for those just beginning their automation journey, the first deployment can feel overwhelming. While the initial integration is often the most complex, long-term success comes from designing systems that can grow and adapt over time. Automation should be viewed not just as a one-off project, but as a flexible investment that can evolve alongside production needs.

This presentation will guide participants through essential considerations for automating machine tending, from basic robotic handling to automated clamping on machine tables. Attendees will explore practical strategies to optimize investment in automation, focusing on increasing throughput, reducing manual labor, and creating scalable solutions.

The session will highlight a range of real-world machine tending scenarios, progressing from simple, cost-effective setups to more advanced configurations. These approaches include:

• Lean Automation: Using the machine’s own table and spindle motion to implement an entry-level automation path.
• Workpiece Automation: Automating the transfer of raw materials into the machine’s clamping device, ideal for larger lots with minor part variation.
• Pallet Automation: Pre-clamping parts outside the machine and loading them automatically via pallet systems, ideal for applications with high variability.
• Combined Workpiece and Pallet Automation: Coordinating tools for both the robot and machine table to handle a wide range of production volumes.
• Flexible Manufacturing Systems (FMS): Integrating multiple machines with automated transport and storage systems for high-volume, variable production environments.

Attendees will gain insights into leveraging existing machine motion, evaluating manual versus automated clamping solutions, and using robots and cobots to increase handling flexibility. The session will also explore strategies for planning production changes, managing multiple operations, and streamlining infeed and outfeed processes.

By the end of this session, participants will understand how flexible machine tending strategies can free skilled employees from repetitive tasks, improve productivity, and enable automation systems that adapt to evolving production requirements.

In today’s rapidly evolving manufacturing landscape, the pressure to innovate, optimize, and deliver faster has never been greater. Traditional methods of factory design and automation planning are no longer sufficient to meet the demands of Industry 4.0. Manufacturers are facing increasing complexity in their operations, tighter production timelines, and higher expectations for flexibility and customization. To stay competitive, they need smarter tools, faster workflows, and more collaborative environments. That’s where 3D automation simulation comes in and why Visual Components is leading the charge.

Exploring how 3D simulation is transforming the way manufacturers design, validate, and deploy automation systems. Attendees will discover how Visual Components empower teams to build smarter factories virtually before a single machine hits the shop floor. By simulating production environments in 3D, manufacturers can visualize layouts, test processes, and optimize performance, all without the cost and risk of physical prototyping.

We’ll begin by examining the core challenges facing modern manufacturers: fragmented design processes, costly physical prototyping, and limited visibility into how automation decisions impact overall production. These pain points often lead to delays, budget overruns, and inefficient layouts. From small production batch to large-scale assembly lines, companies are leveraging 3D simulation to test ideas, optimize workflows, and reduce risk, all before committing to physical implementation. It enables engineers, designers, and decision-makers to collaborate in a shared virtual space, making smarter decisions faster.

We’ll also explore how 3D automation simulation supports broader digital transformation initiatives. As manufacturers embrace digital twins, predictive analytics, and AI-driven optimization, platforms like Visual Components serve as the foundation for these innovations. By creating a virtual replica of your production environment, you can simulate scenarios, test changes, and make data-driven decisions with confidence. This session isn’t just about technology, but rather it’s about outcomes.

Join this interactive workshop to explore how AI and machine learning are transforming automation in manufacturing environments—from life sciences to energy and beyond. Led by experts from JR Automation and (Hitachi/TBD), participants will learn from real-world applications, practical frameworks, and proven strategies to help organizations accelerate digital and operational transformation.

Through discussions and case studies, participants will learn and engage in discussions on:

• Assessing Organizational Readiness: How to evaluate digital maturity and readiness for automation using proven frameworks and assessment tools.
• Risk Management for Intelligent Systems: Risk assessment methodologies for AI/ML-enabled automation systems, with a focus on maintaining product quality, data integrity, and compliance.
• Validation and Integration Challenges: Best practices for validating intelligent automation solutions and how to aligning with evolving technology.

This session is ideal for operations leaders, automation engineers, and quality professionals seeking to modernize their manufacturing processes while improving employee safety, quality and performance.

Legacy manufacturing facilities power much of American industry—but their manual workflows, disconnected systems, and aging infrastructure often make automation feel out of reach. This session offers a practical, data-driven roadmap for deploying Autonomous Mobile Robots (AMRs) in legacy environments, drawing on real-world pilot programs and scaled deployments at Tesla.

Attendees will learn how to assess automation readiness in existing operations, identify high-friction material flows, and define meaningful Key Efficiency Indicators (KEIs) that translate AMR performance into measurable business outcomes. The presentation walks through the full AMR lifecycle—from pilot design to plant-wide scale-up—highlighting how interoperability across fleet management systems, WMS, PLCs, and analytics platforms is essential to success.

The session also addresses one of the most critical and complex challenges: human-robot collaboration. Through real examples, Joshua demonstrates how thoughtful floor design, safety strategies, and operator-centric workflows can improve throughput, safety, and workforce adoption rather than create resistance.

Finally, the discussion explores how manufacturers can move beyond proof-of-concept by leveraging real-time data, interoperability standards, and cross-functional alignment to scale AMRs across lines and facilities. Attendees will leave with a clear decision-making framework for evaluating ROI, justifying investment, and modernizing legacy plants with confidence.

As machine vision technology continues to advance, industry standards play a crucial role in ensuring interoperability, performance, and reliability. In this session, Bob McCurrach from A3, Jan Pech representing the European Machine Vision Association (EMVA), Masahito Watanabe from Japan Industrial Imaging Association (JIIA), and Suprateek Banerjee from VDMA will provide an overview of the latest updates to machine vision standards, including key changes, new developments, and their impact on automation applications. Attendees will gain valuable insights into how these evolving standards influence system integration, compliance, and future innovations in industrial vision solutions.

Western manufacturers are facing a wake-up call. Executives returning from Asia describe factories where robots work entirely in the dark—no operators, no downtime, no hesitation. Meanwhile, many North American plants still rely on manual handling for applications that automation could already solve.

In this session, Apera AI Founder & CEO Sina Afrooze will show manufacturers how to catch up fast. Drawing on his work with North America’s top six automotive OEMs, Sina will guide attendees through a virtual “plant walk-through,” highlighting every vision-guided robotics (VGR) opportunity that exists today, from de-racking and bin picking to part placement and assembly.

Doing anything with your eyes closed is harder. For decades, robots worked blind, limited by rigid programming and poor reliability. But with 4D Vision and AI, robots can finally see, adapt, and respond like humans—bringing true flexibility and autonomy to manufacturing.

Attendees will learn:

• Why global competitiveness now depends on adopting vision-guided robotics
• How to evaluate plant-floor processes for AI-driven automation potential
• Real-world ROI examples from plants that achieved 99.9%+ reliability and months-to-days deployment
• How customer mandates to eliminate “hands on parts” are accelerating adoption

Fueled by low-cost engineering and heavy government incentives, overseas markets are progressing rapidly. In five years, it may be too late to close the gap. Join this session to see how AI-powered 4D Vision is helping North American manufacturers unlock hidden performance and stay in the race for global leadership.

We are entering the era of Software-Defined Manufacturing, where the shop floor is no longer a collection of rigid, hard-wired cells, but a dynamic environment controlled by Physical AI. Whether it is high-density AMR fleets, automated quality inspection via edge vision, or collaborative humanoid robotics, these "embodied" systems require more than just a connection—they require a deterministic, high-capacity "nervous system." For IT and OT leaders, the challenge is moving beyond "best effort" wireless.

This session addresses the technical and operational realities of using Private 5G to provide the mission-critical backbone for Physical AI. We will explore how to architect a network that treats connectivity as a high-performance industrial utility, reconciling IT’s requirements for integration with existing systems with OT’s demand for ultra-low latency and "five-nines" reliability.

The ISO 10218 standard is the cornerstone of industrial robot safety, guiding manufacturers, integrators, and end users in ensuring safe robotic system implementation. In this session, Roberta Nelson Shea, a leading expert in robot safety, will provide an in-depth overview of the latest updates to ISO 10218 and the R15.06 revisions. Key changes, new requirements, and their implications for the industry will be discussed, with a focus on the evolving safety landscape for robotic automation. Attendees will gain critical insights into how these updates impact risk assessment, collaborative robotics, compliance strategies, and the integration of robotic systems, ensuring they stay ahead in an ever-changing industry.

Seeing It All: How 360° Imaging Transforms Quality Control
Beatrice Danese, Opto Engineering
As inspection demands increase, manufacturers are turning to 360° imaging to capture complete product views with a single camera. This session explores how 360° view lenses solve complex inspection challenges—from curved surfaces on high-speed lines to micro-components—while reducing blind spots, system complexity, and cost. Attendees will see real-world use cases and innovations demonstrating how 360° inspection improves quality, efficiency, and automation readiness across industries.

From Pixels to Production: AI-Powered Computer Vision for Automated Inspection and SOP Compliance
Nitin Gupta, Dori AI
AI-enabled computer vision is replacing rigid, rule-based inspection systems with flexible, scalable solutions that adapt to real-world manufacturing demands. This session shows how deep learning vision enables a single system to perform multiple inspection, verification, and compliance tasks while integrating seamlessly with existing automation and factory systems. Attendees will see real-world examples demonstrating dramatic reductions in inspection time and errors, along with best practices for deploying AI vision at scale.

Recent AI Advances in Manufacturing Vision and the Technical Trade-Offs of Deployability
Russell Nibblelink, Overview.ai
AI vision has progressed rapidly—from deep segmentation models capable of detecting micron-level defects to data-efficient training pipelines that learn from fewer than 10 samples. Yet true value in manufacturing comes not from the models themselves, but from deployability: the ability to run deterministically at the line edge, handle real-world variation, integrate cleanly with OT, and be maintained by engineers on the floor.
This talk examines the latest breakthroughs in industrial AI vision (segmentation, small-sample learning, edge computing, reflectivity handling, and multi-angle inspection) and analyzes the technical trade-offs required to move from pilot accuracy to plant-wide scalability. We’ll walk through real examples of what works, what fails, and what engineers must evaluate when selecting or deploying an AI vision system.

Quantify Line-Speed Accuracy & Real ROI: Generative AI + 2.5D
Keven Wang, UNITX
Manufacturers need inspection solutions that deliver higher accuracy and speed without adding cost or complexity. This session shows how Generative AI and 2.5D imaging enable line-speed inspection of reflective, high-mix parts while producing measurable ROI. Attendees will learn a practical deployment playbook and proven methods to quantify savings across scrap, rework, labor, and throughput—from pilot to multi-line rollout.

Manufacturers are demanding more than isolated AI pilots—they need connected systems that solve real challenges across the entire factory. In this session, we’ll show how a rapidly expanding ecosystem of vision, industrial automation, and software partners is using the NVIDIA stack of AI models—including NVIDIA Metropolis, Cosmos, and Omniverse—combined with GPU-accelerated infrastructure and tools to deliver faster ROI, higher accuracy, and self-improving factory systems.

This growing ecosystem is coming together around a common platform, enabling partners to interconnect quality inspection, safety analytics, robotic perception, facility insights, and warehouse intelligence into cohesive, plant-wide AI systems. You’ll learn how shared models, shared data pipelines, and compatible architectures are allowing partners to deliver “compound applications” that unlock new levels of efficiency and insight across manufacturing.

Warehouse automation encompasses a broad spectrum of solutions, from digital tools like barcode scanners, cloud databases and machine learning analytics to physical systems including conveyance, AS/RS, high-speed sortation and autonomous mobile robots. But what does it truly mean to automate your warehouse operations?

This session will move beyond the technology showcase to address the critical factors that determine automation project success. You'll discover how to use advanced automation to accelerate workforce efficiency, secure financial justification for projects ranging from $10M to $125M and take a holistic approach that integrates software, hardware, people and processes for end-to-end distribution and fulfillment excellence.

Through a practical risk/reward framework and real-world examples, you'll gain the strategic insights needed to avoid costly automation pitfalls and build compelling business cases that deliver measurable ROI.

SO/IEC 42001 is the first global standard for Artificial Intelligence Management Systems (AIMS), providing a framework to ensure AI technologies are ethical, transparent, reliable, and aligned with organizational and societal values. This presentation explores the significance of ISO 42001, its key components, and its role in shaping the future of AI governance. The content will delve into the standard's principles, including ethical considerations, risk management, and performance metrics, and discuss how organizations can implement it to build trust and compliance in their AI initiatives.

Across industries such as medical devices, consumer electronics, semiconductors, aerospace manufacturing, and more, production teams face growing pressure for faster throughput, tighter tolerances, and flawless quality. Traditional inspection methods often fall short when dealing with reflective, transparent, or multi-layer materials. Traditional inspection methods often fall short when it comes to reflective, transparent, or multi-layer materials.

3D line confocal imaging offers a unique solution - delivering high-speed, high-resolution, non-contact inspection for some of the most challenging targets in medical devices, semiconductors, and consumer electronics. From measuring micron-level surface roughness to capturing transparent and reflective surfaces with precision, this technology opens new possibilities for inline process control and quality assurance.

This talk separates real progress from hype with a simple rule: less is more. We review the biggest shifts of the year: small task-specific models that beat general ones on cost and latency, agent workflows that combine lightweight tools with clear rules, retrieval that cuts hallucinations without heavy fine tuning, and privacy-preserving training that meets regulatory needs.

We fold in a key recent finding on hallucinations: bigger models do not automatically hallucinate less. Hallucination rates drop most when you shrink scope, ground answers with retrieval, use structured prompts, and route to tools for facts and math. You will get clear decision frames for when a small model plus retrieval is better than a larger model, and when classical ML still wins. We also show how to trim everything that does not add value: parameters, prompts, features, and pipelines.

Are you already leveraging automation but feel there's more potential to unlock? This session is for you. Many organizations achieve initial automation wins, but truly transformative gains come from a shift in perspective — moving from isolated tasks to a culture of continuous automation discovery. Join us to explore how to systematically identify new opportunities, scale your initiatives, and maximize productivity across your operations. We'll delve into diverse approaches, from quick-win solutions to more complex, integrated strategies, ensuring you leave with actionable insights tailored to various needs. Discover how to empower your teams to see automation not just as a tool, but as an ongoing journey towards sustained efficiency and innovation.

The automation industry has NEVER just been about robots. It's vision equipment, conveyance, fixturing, inspection, package, and the list goes on. So how did we become obsessed with Collaborative robots, and what do we do now that safety regulations have changed

Jacob Sanchez dives into how we will need to all redefine collaborative solutions and adjust our mindsets around "collaborative robotics" if we want to be able to keep up with safe efficient cells in our businesses. He utilizes his 11 years in automation during the big resurgence of affordable cobots to lead this presentation as well as key insight from robotics manufacturers from around the world lending their experiences as well.

In this session we will go through why regulations have changed, what these robots bring to the table versus an industrial application and most importantly how can you analyze your current manufacturing process to create a collaborative solution whether that is with a industrial robot or a former "collaborative robot".

There are more than 2.7 million industrial robots safely operating in factories worldwide, and the robotics industry can take pride in its impressive safety record. For nearly forty years, A3 Robotics – formerly the Robotic Industries Association – has taken a lead role in assuring that the robotics industry continues to proactively assess the safety environment and provide safety resources as robotic applications continue to expand. At the forefront of A3 Robotics’ leadership role in industrial robot safety is the development of the ANSI/RIA R15.06-2012 safety standard. 

Join A3's lead robot safety trainer to learn to help you keep your team safe and learn the basics of conducting a risk assessment for your facilities.

Picture a production line that stalls without warning. In that moment, time becomes your most expensive commodity, and human limits show up fast. What if your best expert could see through a junior’s eyes, highlight the exact connector to check, and guide the fix in real time, hands-free? In our live “Troubleshooting the Game” demos, technicians solved the same fault ten times faster than with paper and twice as fast as with a tablet. The information was identical. The difference was context in the line of sight, and both hands were free to act. When 23 percent of unplanned downtime traces to human error and some sectors bleed up to 20,000 dollars per minute, those saved minutes are not small wins; they are cultural change. You cannot stop the clock during downtime. You can fight it with the right tools.

This talk translates two fresh LightStream whitepapers into a clear playbook for plants and OEMs. We show how AR-powered remote assistance keeps experience present on every shift, even when senior bodies should not climb ladders, and how governed documentation plus AR guidance builds safer, calmer interventions that scale across sites. You leave with a practical rollout sequence, the KPIs that matter, and the business models that make it stick, from subscription support to centralized expert pools. Most of all ... you see how to convert retiring know-how into a living asset that mentors in real time, reduces repeat interventions, and makes digital transformation measurable where it counts at the cabinet in front of a technician. Experience may slow down with age. It should never retire.

This presentation showcases results from an research project exploring how artificial intelligence and image processing can fully automate CNC programming. The example demonstrates how a combination of 2D and 3D vision, AI-based handwriting and symbol recognition, and automated code generation can transform even a simple hand sketch on a raw workpiece into a complete CNC machining program.

Traditional CNC programming is often complex and time-consuming, involving CAD modeling, CAM setup, and skilled operators. In small-batch or prototype production, this manual effort can outweigh the value of the parts themselves. As part of its research, EVT explored how AI and advanced vision systems could be used to replace manual coding with automatically generated, data-driven CNC programs.

The process begins with a 3D scan of the machining space to detect the position, orientation, and dimensions of the blank part. Next, the AI interprets handwritten notes, geometric shapes, and symbols drawn directly on the workpiece or on a 2D image. These are combined with 3D positional data to automatically generate G-code and initiate the CNC process. The same system can perform a final 3D scan for quality inspection, verifying the finished dimensions and documenting the results.

This new approach enables CNC manufacturing without CAD files or programming expertise, making it ideal for single parts, prototypes, and small series production. By simplifying the workflow from concept to finished part, manufacturers can reduce setup time, eliminate programming errors, and significantly increase flexibility - a key advantage in modern, high-mix, low-volume production environments.

The presentation also highlights how this research integrates with industrial communication standards such as OPC UA, ProfiNet, and UMATI, ensuring easy integration into smart factory infrastructures. The result is a fully connected, vision-driven, and adaptive manufacturing system that represents the next step toward autonomous production.

As manufacturers accelerate toward Industry 4.0, the concept of lights-out manufacturing—fully automated, human-free production—is becoming a reality. In this session, discover how SICK’s advanced sensor technologies are reshaping the frontlines of production for numerous industries.

From intelligent motion detection and predictive maintenance to AI-driven quality control, SICK sensors enable smarter, safer, and more efficient factories. Learn how these innovations reduce downtime, enhance flexibility for customization, and support the transition to autonomous operations—illuminating the path to a future where the lights stay off, but productivity never stops.

Machine vision has evolved from a niche technology in the late 1980s to a cornerstone of modern manufacturing automation. Drawing on 44 years at General Motors—25 of them dedicated to machine vision—I will share insights into what defines success in vision applications and how that definition continues to shift as technologies and expectations advance.

This session will explore the essential requirements for achieving consistent, reliable results across generations of hardware, software, and production environments. We will cover strategies for:

• Establishing clear performance standards that drive measurable outcomes
• Avoiding common pitfalls in system integration
• Adapting quickly to emerging AI technologies while maintaining quality and reliability

I will also present findings from a survey conducted at Automate 2025, where I asked multiple AI solution providers five key questions. Their responses reveal insights and opportunities that must be included in your future vision system specifications.

Finally, through a historical lens and real-world automotive experience, I will outline the evolving balance between robustness, flexibility, and cost-effectiveness—providing a practical roadmap for engineers and managers to design vision systems that succeed today and remain viable tomorrow.

Mining is one of the world’s most resource-intensive industries, facing constant pressure to increase output while improving safety and reducing environmental impact. Automation and advanced control systems are at the core of meeting these challenges, transforming traditional mining into a smarter, data-driven industry.

In this session, Avadh Nagaralawala will explore how automation technologies—from PLC–SCADA integration to predictive monitoring—are redefining mining operations. Drawing from over a decade of practical project experience, he will share real-world examples of designing and implementing control systems that deliver both efficiency and resilience in harsh industrial environments.

The presentation will highlight:

• PLC–SCADA Integration: Building frameworks that provide real-time visibility into mining operations and enable proactive decision-making.
• Predictive Monitoring and Analytics: How smart sensors and automated control loops reduce downtime and extend equipment life.
• Safety through Automation: Designing fail-safe logic and operator-assist features that protect workers in high-risk conditions.
• Sustainability at the Control Level: Using automation to optimize energy usage, minimize waste, and support environmental goals.
• Future Outlook: How digital transformation, Industrial IoT, and cybersecurity will shape mining automation in the years ahead.

Attendees will gain actionable strategies for modernizing mining operations, ensuring consistency, and positioning their organizations to meet the evolving demands of global resource markets.

The integration of AI into robotics has transformed how robots and autonomous systems perceive, learn, and act across industries—from intelligent bin-picking to collaborative tasks in modern factories. Now, with the rise of Generative AI, we're witnessing a fundamental shift in how robotics systems are built, trained, and deployed.

This talk will discuss how MATLAB and Simulink empower engineers to develop intelligent robotic systems using both traditional AI approaches and the latest advancements in robotics foundation models. Learn how to design end-to-end workflows that incorporate deep learning, reinforcement learning, transformer-based vision-language-action (VLA) models—all within a single, simulation-driven platform.

Highlights:

• Design and deploy AI-powered bin-picking and motion planning systems with reduced human supervision.
• Automate data labeling and training for object detection and pose estimation.
• Perform automated visual inspection using deep learning for defect detection and quality assurance.
• Object detection with zero-shot text-conditioned models.
• Segmenting objects across images and videos using vision foundation models.

Multi-agent AI systems optimize complex processes and automate tasks that could never be automated before. This comprehensive course delves into the design of multi-agent AI systems, focusing on the principles, strategies, and methodologies used to create intelligent systems capable of autonomous industrial operations.

By the end of the course, you’ll understand how to orchestrate AI agents and other automation technologies together into high-performing systems that can digitize and reproduce the skills of the highest-performing human operators. You’ll learn how to train agents to specialize in specific skills and become familiar with reusable templates for multi-agent system orchestration to address industrial automation challenges like noise and changing conditions. At the end of the course, you’ll know how to create a team of expert, specialized agents to work together to solve your hardest automation problems.

China has the largest scale of industrial scenario data. We will share how Chinese brands, through one-stop software + hardware solutions and leveraging software scheduling collaboration, enable embodied robots to adapt to complex scenarios and facilitate automation upgrades.

Toolholders are integral to machines doing cutting, grinding, milling and drilling operations.

In higher speed applications, proper balancing of the toolholder is critical for good finish and for longevity of the equipment.

Toolholders (ISO, BT, HSK, etc.) collets and collet nuts should all be considered as consumables. Regular use can cause minor damage which accumulates to cause out-of-balance issues.

When out-of-balance, the quality of the work can suffer. Out-of-balance can damage bearings and reduce the lifespan of the cutting electro-mechanical motor spindle.

Both collets and fixture nuts normally accumulate damage first and should be replaced regularly.

Toolholders are usually more durable but can also fall out-of-balance. Any toolholders that are dropped or involved in machine crashes should be discarded.

Tool holding consumables are substantially more cost effective to replace regularly than to repair failed equipment or discard out-of-specification work pieces.

Designing a machine vision system can be complex and costly, often requiring physical prototypes to test different cameras, lenses, and lighting setups. With the recent development of new simulation environments, including Digital Twins, companies now have new tools available to overcome these common challenges when configuring a vision system, reducing the need for high investment in physical test setups and shortening time to market. This talk will help companies understand how vision requirements and application challenges can be more easily identified in a simulation environment specifically focused on vision systems. By leveraging machine vision know-how and product data we will show how cutting-edge simulation technologies deliver sensor-realistic simulations, enabled by the NVIDIA Omniverse.

Industrial automation is entering a new phase, where vision-guided robotics and intelligent inspection are powered by unified compute architectures and edge AI. In this session, Ricky will examine how integrated architectures for perception, motion control, and reliability analytics within a single compute environment is improving responsiveness, scalability, and operational efficiency on the plant floor.

Attendees will gain insight into implementation frameworks that connect robotic vision, edge processing, and AI-driven decision-making to deliver measurable performance gains and support the evolution toward autonomous, software-defined manufacturing environments.

AI is rapidly changing the very nature of manufacturing robots, with one of the most promising developments being innovations that enable robots to execute complex tasks with greater autonomy and adaptability. These advancements could solve the high-mix, low-volume challenges commonly faced by small and medium manufacturers. Fewer than 10% of U.S. manufacturers have implemented robotics, likely due to the need for highly adaptable work cells, which could be addressed through AI-enabled robotics. Meanwhile, even fewer manufacturers have implemented AI in their operations. Innovations in robotics and AI often stall before they can reach small and medium-sized manufacturers due to fragmented infrastructure, incompatible interfaces, and limited pathways to scale.

A national, expertly curated repository of AI-enabled robotic technologies is needed to get manufacturers using those technologies to expand their productivity and competitiveness.

The ARM Institute is addressing this gap through the development of a standardized framework and a Hardware-in-the-Loop test capability aimed at accelerating the path from R&D to commercial deployment for AI-enabled robotics on the factory floor. The framework will develop low code interoperable interfaces across robot hardware and controllers, establish data curation best practices, and host a federated library of manufacturing process data sets, models, and early-stage AI-enabled robotic skill algorithms. By creating these shared resources, the ARM Institute will accelerate the ability of OEMs, integrators, and manufacturers to readily integrate emerging AI technologies with current commercial offerings. As a non-profit with a 470-member organization consortium and thousands of individual experts spanning industry, academia, and government, the ARM Institute is uniquely positioned to democratize AI-enabled robotics for the manufacturing industry.

This session will outline the architecture, guiding principles, and roadmap for this initiative, illustrating how this standardized framework accelerator will shorten technology-readiness cycles and strengthen U.S. manufacturing competitiveness.

In modern manufacturing, variable frequency drives (VFDs) have evolved far beyond simple motor control devices—they are now powerful performance engines that unlock efficiency, reliability, and intelligence across the plant floor. As industry pressures grow around productivity, sustainability, and system flexibility, leveraging drives as strategic automation assets has become essential.

This session explores how today’s advanced drives architectures deliver measurable impact through energy optimization, built in diagnostics, edge intelligence, and seamless integration with automation and control systems. Attendees will learn practical approaches to using drives to improve machine performance, enhance predictive maintenance strategies, and support digital transformation initiatives without adding system complexity.

Operational demands are evolving faster than many manufacturers can adapt. Facing siloed processes, worker shortages, and rising costs, manufacturers need an innovative, holistic solution to connect their factory, increase productivity, and empower their workforce. The production logistics solution delivers exactly that—autonomous operations from dock to dock, centrally managed processes, and data-driven insights that enable continuous optimization. 

In this session, learn how Fortune 500 manufacturer Rockwell Automation is bringing this vision to life at its Twinsburg, Ohio plant, where a production logistics solution unlocked over $160K in annual savings and improved space utilization by 70%. Attendees will discover how autonomous material handling and Rockwell’s orchestration software work together to create a fully connected operation—and the steps they can take to begin their own production logistics journey.

What Last Mile Delivery Could Look Like in the Future
Ask any supply chain professional to define last mile delivery, and you'll get a consistent answer: transporting a package the final distance to the customer's address. But ask how it's achieved, and the discussion becomes far more interesting.

For this discussion, last mile delivery encompasses the processes, people, equipment, and technology required to get a package to a customer's doorstep. In 2025, most of us are familiar with how this occurs: order something online, enter delivery details, and a driver eventually arrives with your package. Some understand the behind-the-scenes fulfillment centers, sorting facilities, and route planning. But what everyone recognizes is that the last mile of delivery involves the driver, the truck, and the technology to confirm delivery.

The Coming Challenge
Here's the problem: e-commerce accounted for 16% of total U.S. retail in 2024 (20% globally), and that percentage is climbing. Meanwhile, the supply chain faces a driver shortage. Eventually, the current system will collapse. The only questions are when, and whether we'll adapt before it happens.

I'm betting we figure it out first and thought it would be fun to speculate what that future might look like.

Three Categories, Three Solutions
Future last mile delivery will likely split into three distinct categories: urban, suburban, and rural—each requiring tailored solutions.

Urban Delivery
Imagine leveraging existing utility infrastructure beneath city streets for package delivery. Fulfillment centers would still use current picking and packing processes and automation, but instead of a package diverting to trucks for loading, the packages would travel via conveyor into underground tunnels. An extensive network of covered conveyors would run beneath the streets, funded by municipal tax dollars.

Each city building would feature its own delivery system. Your package travels underground, gets diverted to your block, and arrives at an automated storage and retrieval system (AS/RS) that sorts packages by address. The final step involves a pneumatic delivery tube and technology to identify customers and unlock access to their packages. No trucks. No drivers. The last mile of delivery is achieved with conveyors, ASRS, pneumatic tubes, and facial recognition software (that was purchased by the government from phone providers attempting to remain in business facing the obsolescence of their product…but I digress).

Suburban Delivery
Current underground systems won't reach most suburban homes, so this solution takes a different approach. Packages still leave the fulfillment center on conveyors, but are conveyed to the rooftop instead of the underground system. Drones pick them up from the roof and deliver to more government-owned AS/RS systems (this time above ground).

From there, packages are sorted by route and loaded onto autonomous delivery trucks. Each home would have a delivery port similar to current roadside mailboxes. The autonomous truck pulls up, delivers the package to the port, and moves on. The suburban last mile of delivery would involve ASRS and self-driving vehicles.

Rural Delivery
Rural areas could mirror the suburban model with autonomous route delivery, or drones might deliver directly from fulfillment centers to far flung locations.

Making It Reality
Are these scenarios possible? Probable? The technology exists or is rapidly emerging. The real challenges are infrastructure investment, regulatory frameworks, and coordinated implementation.

The automotive industry continually seeks innovative solutions to boost efficiency, consistency, and product quality. The conventional method for paint repair, especially the critical and highly skilled task of finesse sanding, is inherently variable when performed manually, leading to inconsistencies and efficiency bottlenecks. This presentation details a successful collaborative project between Stellantis and FerRobotics to develop a fully automated paint repair process. This solution integrates a sophisticated defect detection system with cutting-edge compliant robotics to establish a new benchmark for quality in surface finishing.

The Fully Automated Workflow: From Detection to Finish: The complete, automated process begins with defect detection and ends with flawless surface repair, eliminating the need for manual intervention throughout the entire chain.

1. Sophisticated Defect Detection: The process is initiated by an automated vision system (provided by J3D) that accurately scans the vehicle chassis to map and localize all paint defects. This crucial first step provides the precise coordinates and type of defect necessary to program the robotic repair path.
2. Automated Repair Execution: The robotic system then executes the repair sequence, transforming the localized defect data into a highly controlled physical process. The system is designed to manage the entire repair workflow: from the preparatory wet sanding to the final polishing and cleaning.
3. Streamlined Operation: A key innovation is the use of an automatic changing system for different abrasive and polishing media, ensuring continuous, non-stop operation and eliminating changeover downtime.

Core Technology: Perfecting Robotic Sensitivity: The success of the physical repair phase hinges on overcoming the challenge of replicating human tactile sensitivity. This was achieved through the implementation of FerRobotics' proprietary Active Compliant Technology (ACT).

• Active Force Control: This core technology grants the robotic system the ability to exert precise, consistent contact force independent of the robot's position and speed. This is vital for navigating the contours of a car body and preventing damage to the thin underlying paint layers - a capability previously exclusive to skilled manual operators.
• Specialized End-Effector: The system utilizes a highly engineered orbital sanding end-effector specifically designed for robotic applications. This tool allows for the decoupled and dynamic control of all crucial process parameters: rotation speed, contact force, and feed rate. This independent control ensures process optimization and repeatable high quality, even across small or complex repair areas.

By integrating this compliant technology with the precise data from the 3D vision system, the project successfully transformed a highly subjective, manual process into an objective, industrial solution.

Quantifiable Results and Industry Impact: Deployment of this automated system has delivered substantial benefits now being realized at multiple Stellantis manufacturing sites:

• Product Quality: Achieves improved surface quality and a significant reduction in defects due to consistent, algorithmically controlled force application.
• Operational Efficiency: Results in reduced repair cycle time and a substantial increase in overall ihroughput compared to manual stations.
• Sustainability & Cost: Leads to optimal abrasive utilization (longer durabitlity) and minimized material waste resulting from precise process control.
• Workplace Safety: Provides enhanced worker safety by automating tasks that are ergonomically strenuous or involve exposure to contaminants.

When I started DeWys Engineering in 2010, it was as a mechanical engineering firm specializing in designing factory automation equipment. For years, I kept a close eye on additive manufacturing and wondered, “Why aren’t we using this technology to produce components for the machines we design?”

The gap was clear: machine builders didn’t fully understand the capabilities of additive technologies, while additive manufacturers often lacked insight into the true needs of automation engineers. In 2016, I set out to bridge that gap with the acquisition of a local additive supplier and the launch of our 3D printing division, Forerunner 3D Printing. Since then, my team and I have focused on educating automation and machine-building companies about how additive manufacturing can go far beyond simple jigs and fixtures.

This presentation will showcase real-world, shop-floor applications where additive manufacturing has delivered measurable value in automation environments. Attendees will walk away with practical design tips, application ideas, and a clearer vision of how 3D printing can be leveraged in their own operations.

Key applications to be explored include:

• TPU material use cases: Class A–safe nesting, protection of painted/chrome/lens parts, custom-shaped vacuum nests, inflatable plugs for leak testing, and textured rubber grippers.
• Nylon 12 and ABS applications: Lightweight, exotic end-of-arm tooling with integrated vacuum/air channels, pogo pin test stations, hybrid pallet line components, complex locking mechanisms, and custom low-volume hand tools.

The session will be entry-level and accessible to anyone interested in automation—no prior knowledge of additive manufacturing required.

What if loading and unloading a trailer took less than 10 minutes?

Across warehouses and manufacturing plants, loading docks remain one of the biggest throughput bottlenecks. While automation often promises improvement, it historically comes with complexity. This session flips that expectation, showing how robotics can increase the speed, safety, and simplicity of dock operations.

We’ll explore real-world operations where automated loading robots were deployed in days, reducing truck idle time by >90%, boosting dock throughput by 10X, and keeping personnel and forklifts off trailers. From palletized freight to mixed totes and racks, these robots are proving that speed and simplicity—not complexity—drive ROI.

Attendees will learn:

• Redefining speed at the dock: what it takes to achieve consistent sub-10-minute load/unload cycles across any trailer, any freight.
• Rapid deployment strategies: deploying in days without facility rework, Wi-Fi, or IT infrastructure.
• Freight-agnostic handling: adapting one solution to multiple freight types across operations.
• ROI in months, not years: how measurable gains in throughput, labor efficiency, and trailer utilization compound fast.
• Attendees will leave with a proven playbook for turning the slowest part of their supply chain into the fastest.

In this panel discussion, the ARM (Advanced Robotics for Manufacturing) Institute will explore trends, best practices, and lessons learned in robotics for manufacturing. ARM Institute-funded robotics and AI projects aims to strengthen US manufacturing with a focus on dual use applications by industry and the defense sector.

As a Manufacturing Innovation Institute part of the Manufacturing USA Network, the ARM Institute is tasked by the Department of Defense with strengthening US manufacturing through robotics, AI, and workforce innovations. The ARM Institute accomplishes this mission by leveraging a consortium of 450+ organizations and thousands of individual experts representing the full manufacturing industry, from start-ups and technology providers to manufacturers of all sizes and workforce programs. Since its inception in 2017, the ARM Institute has funded hundreds of collaborative projects that address a variety of issues as identified by the institute's membership and DoD partners. From textile manufacturing to surface finishing, by bringing together organizations that otherwise would not collaborate, the ARM Institute is leading the way to a stronger future for US manufacturing.

We will present a panel discussion led by Miguel Rodriguez (ARM Institute Senior Programs Manager) with three panelists representing industry, government, and academia. Through this panel, we will explore robotics projects that have successfully transitioned from ARM Institute funding to impact on the factory floor, detail lessons and best practices learned, identify trends in robotics for manufacturing, and explore how attendees can get involved in current and future efforts. Attendees will walk away with a keen understanding not just of the project outputs, but how this work benefits their businesses.

Manufacturing is undergoing a profound transformation driven by rapid market change, increasing customization, and an evolving workforce. Traditional hardware-centric automation models are no longer sufficient to meet these demands. Software-Defined Automation (SDA) introduces a software-first approach that decouples automation software from physical hardware, enabling greater flexibility, scalability, and continuous improvement in industrial systems.

This panel will explore how SDA is shaping the future factory by allowing manufacturers to adapt more quickly to changing customer and business requirements, optimize operations over time, and reduce the cost and complexity of change. Beyond the technological shift, the discussion will examine the impact of software-centric automation on the industrial workforce, including the emergence of new roles, skills, and collaboration models as IT and OT continue to converge.

Panelists will share perspectives on how organizations can prepare both their technology and their people for this transition — empowering engineers, accelerating innovation, and building a resilient foundation for the factories of the future. Attendees will gain a clear understanding of why Software-Defined Automation is becoming a strategic cornerstone for modern manufacturing.

Hitting on the following points:

• preparing for the future factory since industrial complexity is increasing
• decoupling of hardware and software, and the importance of this
• impacts on the workforce and skill shortages
• convergence of IT and OT

A candid discussion between Invisible AI and an OEM on moving physical AI projects out of the pilot phase and into full-scale production.

Key Takeaways for Attendees

• Best practices for proving ROI within the first 100-200 days of an AI project.
• How to secure exec buy-in
• Lessons learned on integrating AI with legacy MES and PLC systems.
• Strategies for implementing a Human-Centric AI approach to drive workforce adoption, increased productivity, quality and prevent injuries.

The rising cost of machine downtime, coupled with increasing complexity in automated machinery and the gradual loss of deep technical expertise from an aging workforce, poses significant challenges for manufacturers seeking profitable returns on investment. To address these trends, an AI-driven troubleshooting mentor has emerged as a valuable tool to enhance the capabilities of service organizations. Traditionally, expert technicians acquire their skills through on-the-job experience alongside seasoned mentors, relying on intuition, problem-solving, process knowledge, and access to diverse documentation rather than standardized procedures. By leveraging artificial intelligence, the critical knowledge and diagnostic skills of these experienced technicians are replicated to provide accessible, real-time mentorship for technicians facing diverse machine issues anywhere and anytime. This AI mentor combines general troubleshooting methodologies with application-specific knowledge drawn from multiple data sources, including technical documents, schematics, software source code, video materials, and operational databases. Through multimodal interaction, the mentor helps technicians interpret machine data and correlate it with operational performance, guiding them step-by-step through the diagnostic process with relevant, targeted information. Additionally, with continuous access to real-time operational data, the mentor can proactively alert technicians to potential maintenance needs, supporting preventative strategies. Importantly, this AI mentor augments rather than replaces human technicians, effectively elevating service team expertise and substantially reducing costly machine downtime.

As demand for efficiency, consistency, and flexibility grows in the food and beverage industry, manufacturers are turning to robotics to stay competitive. This session explores how standardized robotic solutions are transforming packaging, palletizing, and material handling across food and beverage operations.

Wes Garrett, Executive Director of Global Accounts at FANUC, will share insights from real-world deployments, highlighting how scalable automation strategies can reduce complexity, accelerate ROI, and support long-term growth. Attendees will learn how to identify automation-ready processes, select the right robotic technologies, and leverage integrator partnerships to streamline implementation.

Whether you're just beginning your automation journey or scaling existing systems, this session will provide practical guidance to make robotics simple, effective, and future-ready.

Just as there are many ways to get from point A to point B, in the world of automation we can move, pick, and transport parts in numerous ways with a large variety of automation components to choose from often leaving the system designer/engineer with the challenge of how to select the best fit actuators to match the application. Choosing the right technology and then zeroing in on pneumatic actuators and navigating through the various options available. During this sessions we will discuss: (1) The pros and cons of pneumatic actuation and electric actuation along with some guiding considerations as to choosing the best fit technology; (2) Deciding on the best fit pneumatic actuator, be it a traditional piston rod type cylinder, or venturing into the vast types of guided or rodless type actuators, and the steering questions to make the right choice for the application.

The transition from run-to-break (reactive) maintenance to prescriptive maintenance represents a fundamental shift in how manufacturers approach asset management. Here's a strategic roadmap for making this transformation.

This will be an update to the presentation I gave the last three years on how to make machine vision integration simple. I will continue to include more real-world applications and dive into a few of the items that I use in my day job to solve customer applications and make their integration life easier.

I will showcase the tools and equipment that can be used to make your machine vision application work for a long time. I will focus on the questions that you need to ask upfront during the design process to make sure you have a successful deployment. I added Vision Validation last year and will continue to discuss how to make your deployments simpler.

As automation demands grow, manufacturers seek solutions that maximize flexibility, workspace efficiency, and throughput. This session explores three key technologies that extend robotic capabilities beyond a fixed base: floor-mounted Robot Transfer Units (RTUs), overhead RTU, and gantry robots.

Attendees will learn:

• How floor tracks (RTUs) add a 7th axis for long-distance travel and heavy payload handling.
• Why overhead tracks (Top Loaders) optimize floor space and enable top-down access for complex workflows.
• Where gantry robots deliver reach over large scale operations, maximizing the work envelop.

We’ll compare design considerations, integration challenges, and applications scenarios such as machine tending, material handling, packaging, and logistics. Whether you’re planning a new automation line or upgrading existing systems, this session will help you choose the right solution for your production goals.

Industrial robotics have transformed core manufacturing processes such as machining, welding, and painting. Yet across nearly every industry, assembly remains the largest concentration of manual labor on the factory floor. High product mix, variability, and human-centered workflows have long made assembly difficult to automate with traditional approaches.

This session explores why assembly represents manufacturing’s last major automation challenge—and why that is now beginning to change. Advances in AI, perception, and robotic motion planning are enabling systems that can handle the variability and decision-making required in real-world assembly environments. Drawing on lessons learned from early automotive deployments and extending them to other manufacturing sectors, this talk examines where automation is now practical, where it still falls short, and what manufacturers should consider when approaching assembly automation.

Attendees will gain a realistic view of how modern robotics can help address labor constraints, quality demands, and competitiveness by tackling one of manufacturing’s most persistent challenges.

Once the decision to automate is made, the next step is designing an effective workcell. However, even before that point, it’s critical to carefully evaluate what processes should be automated and how existing workflows may need to be redefined. After these foundational decisions, the selection of the right components becomes equally vital.

This session explores key considerations and trade-offs in automation design, including:

• Robot configuration and geometry
• Safety requirements
• Redeployability versus stability
• Advantages of integrated solutions

By understanding and balancing these factors, manufacturers can optimize both profitability and performance to meet project goals. Leveraging best practices and the latest automation tools can lead to more productive, flexible, and cost-efficient systems—ensuring automation investments deliver lasting value.

The session will address a joint development project toward next generation liquid-to-liquid (LH2) and liquid-to-high-pressure gas (GH2) CryoPumps for hydrogen refueling stations. This electro-hydraulic drive and long-stroke cryogenic pump solution, as an integral part of the overall station architecture, intends to revolutionize the hydrogen refueling infrastructure by optimizing logistics, reducing footprint, and reducing operational costs at refueling stations. Existing CryoPumps, often designed for LNG, and crankshaft driven, are not optimal for liquid hydrogen due to vastly different physical properties such as boiling temperature, latent heat, and sensitivity to boil-off. Efficiency losses of (30-50%) and reliability issues (200h) further curtail adaptability in fuel stations associated with consumer-driven consumption cycles, in contrast, for example, to Industrial applications which may have more predictable, stable consumption requirements throughout the day, and can tolerate space requirements for buffer tanks. Additionally, their placement in open environments to prevent explosions complicates noise dampening and increases station complexity due to the need for additional high-pressure storage tanks, valve panels, and cooling systems. This joint development solution toward next generation refueling stations has several, key attributes: (1) Electro-Hydraulic Drive and Control: By transitioning from mechanical to hydraulic transmission, we achieve better controllability, especially regarding low clearance volumes within the cryopump. This compensates for thermal and mechanical expansion, enhancing efficiency; (2) Increased Stroke Length: Hydraulic systems allow for longer stroke lengths compared to crankshafts, decreasing load cycles and increasing reliability; (3) Direct Heavy-Duty Filling: The increased power and size of the pump facilitate direct filling of heavy-duty vehicles, reducing station complexity and enabling the upgrade of existing refueling stations. (high pressure storage banks, valve panels and cooling system not necessary); and (4) Safety and Packaging: This approach includes enclosing all components and monitoring with safety hydrogen sensors to prevent explosions in case of leaks. This strategy offers several advantages: (a) Enhanced Safety: Small leaks can be detected early, preventing dangerous situations; (b) Noise Reduction: Enclosure allows for effective noise dampening, thereby improving eligibility for deployment within urban settings; and (c) Smaller Footprint: The compact design reduces the station's footprint.

Risk assessment is a key step in the development of safety solutions for all robot systems. When IMRs are part of the system, the risk assessment approach needs to be expanded beyond the typical task/hazard pairs of traditional systems. This session explores the additional scope to be considered when autonomous mobility is introduced.

The rapid integration of automation into the food and beverage industry is driven by evolving regulatory standards and rising consumer expectations for global food safety and quality. A primary challenge in these environments is the necessity for harsh, high-pressure, and high-temperature washdown protocols to ensure sanitation. Consequently, specifying machine vision components to high IP ratings has become a standard requirement for automation system engineers.

However, the IP rating of system components is only one of three key factors that determine the long-term ROI of automated procedures for F&B manufacturers. This presentation posits that an IP rating is insufficient on its own and details a broader framework that evaluates two other critical, and often overlooked, factors: geometric design and material science.

Focusing on the first of these factors, this session will explore the crucial role of geometric design in 'cleanability' and maintenance costs. We will delve into the sanitation risks of traditional equipment component designs, noting how crevices on automation equipment can complicate washdown cycles and foster bacterial growth, while contrasting this with the critical, hygienic design trends the industry is adopting to solve for them.

Furthermore, we will examine the importance of material science in component durability against caustic cleaning agents. This analysis will cover the pros and cons of various enclosure materials, from the superior corrosion and pitting resistance of specific stainless-steel grades to the failure points of coated substrates and polymers. The goal is to provide a methodology for optimizing F&B systems for their specific environments and preventing avoidable risks.

Using machine vision system components as a central case study, attendees will gain a framework for specifying automation components that are truly hygienic, durable, and capable of reducing contamination risks while maximizing long-term maintenance ROI.

Collaborative robots, or cobots, are transforming the way manufacturers approach automation by enabling humans and robots to work side by side safely. This session will provide a practical introduction to cobot technology, exploring how these systems differ from traditional industrial robots and where they deliver the most value.

Attendees will gain insight into key applications such as assembly, machine tending, inspection, and packaging, along with real-world examples of how organizations are using cobots to increase productivity, improve ergonomics, and address labor challenges. The session will also cover safety considerations, ease of programming, and integration into existing workflows.

In addition, we’ll highlight how modern cobot solutions—such as ABB GoFa and ABB PoWa—combine speed, precision, and user-friendly operation to support a wide range of industries.

Whether you are new to automation or looking to expand your current capabilities, this session will provide a clear understanding of how cobots can deliver flexible, scalable solutions for today’s manufacturing environments.

Manufacturers are under pressure to improve efficiency, reduce downtime, and deliver higher ROI—yet connectivity gaps and fragmented data often limit the impact of traditional AI. The next step is agentic AI on the edge: autonomous, adaptive systems that act like digital supervisors, learning continuously and responding in real time.

In this session, we will show how agentic AI can:

• Deliver fast, reliable apps for operators, including real-time documentation, fault recovery, and video-based verification.
• Provide management with actionable insights into production metrics, multi-site orchestration, and supply chain performance.
• Balance cloud and edge intelligence to optimize latency-sensitive operations while enabling large-scale model training.
• Strengthen resilience and security through better data orchestration and governance.
• Unlock new use cases such as adaptive robotics and computer vision–driven quality control.

The automotive industry faces growing pressure to deliver vehicles faster, at lower cost, and with greater flexibility. Achieving this requires a shift from isolated engineering tools to a fully connected digital ecosystem supported by next generation technologies such as artificial intelligence, data analytics, and automation.

This session explores how a model based approach, powered by DELMIA, supports end to end Body in White (BIW) development by connecting process planning, robotic simulation, and production execution through a continuous digital thread. Within this workflow, AI is leveraged to enhance robot path optimization, interpret point cloud data for equipment validation, and accelerate design to production decisions. Participants will see how the Virtual Twin Experience enables teams and suppliers to validate designs earlier, optimize resource utilization, and improve launch readiness before any physical build begins.

Drawing from real world examples, the presentation will focus on practical methods for integrating people, data, and processes across the enterprise, transforming BIW operations from concept to commissioning. Attendees will leave with clear strategies to advance digital transformation in their own organizations, regardless of their current maturity level.

Manufacturers are pushing production speeds higher than ever—and inspection systems must keep up. At thousands of frames per second, every microsecond counts. Yet most inspection challenges at high speeds can be traced back to lighting design: insufficient pulse power, poor synchronization, or heat-induced degradation.

This session will unpack the engineering principles behind lighting for ultra-high-speed inspection. We’ll explore how light pulse duration and timing influence image sharpness, why it’s important to synchronize strobing precisely with camera exposure, and how to manage LED junction temperature to maintain brightness and color stability. Attendees will learn to balance LED overdrive levels, duty cycles, and system lifetime to achieve maximum illumination without exceeding thermal limits.

Finally, we’ll compare continuous vs. strobe lighting, with practical examples of how strobing enables up to 10× brightness without overheating or shortening LED life.

Attendees will leave with actionable insights to optimize their systems for reliability, repeatability, and throughput—without sacrificing image quality. Whether you’re designing new inspection systems or retrofitting existing lines, you’ll learn how to make lighting perform flawlessly at 1,000 fps and beyond.

This presentation explores the evolving role of automation in industrial sealing processes, focusing on real-world strategies to improve manufacturing efficiency, quality, and sustainability. Drawing on practical experience from deploying automated sealing systems in complex production environments, the session will examine how automation gradually replaces manual tasks to enhance process consistency, reduce material waste, and support compliance with environmental standards. Attendees will gain insights into the challenges and solutions involved in integrating smart sensors, real-time data analytics, and modular automation platforms to optimize sealing operations.

The session will also examine the ongoing shift from manual to automated sealing processes, highlighting how automation gradually replaces manual tasks to improve reliability, reduce errors, and increase throughput. Dürr’s approach demonstrates how advanced automation not only enhances process consistency but also allows manufacturers to adapt quickly to changing production demands. Attendees will gain insights into how rethinking sealing processes through automation can drive operational excellence and sustainability, positioning manufacturers for success in rapidly evolving global markets.

Optimize productivity, CO2 reduction, and energy savings through enhanced monitoring. Learn how the design and implementation of smart devices at the machine level can help to achieve production goals, reduce downtime, and cut costs by making data-driven decisions. This presentation will explore the ramifications of adding significant monitoring and communication to the standard modular air preparation system in the industrial automation workspace. Such a system can reduce compressed air use while digitally finger-printing the machine's current performance. Let's use a case packer as an example: Typically, these machines have many large actuators that operate at a very high cycle rate. If the case packer is outfitted with sufficient monitoring, communication, and control, the end user can very quickly realize deep energy savings (25-40%) by “automatically” switching the machine into 1 of 2 possible “Eco modes” when the machine is idle. The end-user can also take full advantage of the monitoring (perhaps via an OPC-UA interface) to collect and analyze machine performance and establish condition-based-maintenance (CBM) algorithms, thus minimizing breakdowns due to pneumatic component failure. The data stream should bypass the traditional methods of PLC mining and go directly to the end-user’s SCADA system to minimize integration effort, particularly on legacy machines.

The principles of zero defect and poka-yoke laid the foundation for quality but today’s dynamic, high-velocity supply chains demand far more. We’ve entered the era of Vision and Agentic AI-driven precision, where accuracy, speed, and adaptability define competitiveness.

Despite significant automation, many enterprises still struggle with fragmented data, limited visibility, and inconsistent efficiency. Vision and Gen AI now enable organizations to bridge these gaps, analyzing complex data, predicting disruptions, and optimizing decisions in real time.

When integrated with digital twin technology, this impact multiplies. Digital twins provide continuous visibility across sites, simulate what-if scenarios, and detect potential bottlenecks before they occur. This combination empowers predictive maintenance, reduces downtime, and optimizes resource utilization, driving sustainable operational excellence.

This session explores how Vision, Agentic AI and digital twins are redefining manufacturing, logistics, and supply chain operations—helping organizations move toward greater resilience, agility, and real-time decision-making.

How can you future-proof your automation tools? This session explores how building flexibility into robotic end-of-arm tooling and supporting technologies can dramatically improve deployment success and long-term value. By combining primary gripping technologies such as electric, pneumatic, and vacuum solutions with auxiliary tools like modular finger systems, quick-change mechanisms, and configurable end effectors, a single robot can take on a wider range of tasks without extensive redesign or downtime. These strategies enable faster changeovers, reduce engineering effort, and help manufacturers adapt to shifting production demands with confidence.

The presentation will walk through real-world examples demonstrating how flexible tooling strategies turn a robotic cell into a multi-purpose asset rather than a fixed-purpose machine. We will discuss practical considerations for choosing between standard modular components and custom configurations, evaluating changeover requirements, and planning for scalability from the very first installation.

Attendees will learn how to:

•  Expand the capability of automation through smart tooling choices
•  Reduce integration and debugging risk through adaptable design strategies
•  Plan scalable solutions that can grow as needs evolve
•  Justify automation investment more effectively by enabling redeployment and versatility

By the end of the session, participants will understand how flexibility transforms robotic automation from a single-use project into a long-term manufacturing platform that supports future growth, faster ROI, and a more resilient production strategy.

Each year, engineers and business leaders demand more from each piece of hardware in automated systems. Vision systems, in particular, are being pushed to their performance limits, with the goal of extracting as much information as possible from each pixel with the highest possible accuracy. This push has accelerated the need to utilize highly accurate, calibrated camera models. Though long established, camera calibration remains a mysterious art to many, and its execution is often neglected or taken for granted.
The goal of this session is to demystify camera calibration and explore its common applications in vision systems. Attendees will learn about camera models, camera calibration best practices, figures of merit, model deployment, and use cases in 2D and 3D vision systems.
Participants will walk away with practical knowledge of how camera models are used in modern vision systems and an understanding of how to improve the performance of their imaging system or existing calibration process.

AI and 3D point cloud technologies share one common requirement: dynamic monitoring of application-level parameters. Ideally, this is directly tied to the system parameters. These systems must be evaluated for their ability to set operational thresholds. Once evaluated, a design must be developed to continuously monitor operational thresholds. This requires a direct communication link to the safety control logic. 

Design Verification and Validation must be carried out to ensure compliance with applicable standards.

In today’s manufacturing landscape, machine vision remains one of the most powerful yet underutilized tools due to its steep learning curve and fragmented ecosystem of proprietary software and hardware. This session will explore how recent advances in AI-driven code generation can dramatically simplify machine vision deployment, making it accessible to non-experts and adaptable across platforms.

Through a live, interactive demonstration, we will simulate a miniature factory line on stage using small bottles or similar objects moving along a conveyor. A 2D camera will capture frames in real time, and an AI system will interpret natural language prompts to generate machine vision code on the fly. Attendees will see how simple commands such as “count the number of bottles” or “detect misaligned caps and stop the line” can be translated into functional automation logic without manual programming.

The presentation will progress from basic to advanced use cases:

• Basic Prompt: “Count the number of bottles on the factory line” — AI displays the count in real time.
• Intermediate Prompt: “Count half-full bottles” — AI applies segmentation and classification.
• Advanced Prompt: “Detect misaligned caps and stop the line” — AI integrates detection with control logic.

This session will highlight how AI can democratize machine vision, enabling factories to break free from vendor lock-in and continuously improve their automation systems. By showcasing a flexible, language-driven interface, we aim to inspire manufacturers to rethink how they approach vision-based automation—making it more intuitive, scalable, and future-proof.

Attendees will leave with a clear understanding of:

• How natural language interfaces can reduce the barrier to entry for machine vision.
• The potential for AI to unify disparate hardware/software ecosystems.
• Real-world implications for cost reduction, flexibility, and continuous improvement in factory automation.

This talk is designed for engineers, integrators, and decision-makers looking to simplify deployment, reduce training overhead, and accelerate innovation in their automation strategies.

As manufacturers adopt connected technologies, cyber threats to operational technology (OT) systems are growing. Reactive security is no longer enough—cybersecurity must be built in from day one. By applying Cyber-Informed Engineering (CIE) within the ISA/IEC 62443 lifecycle, manufacturers can design systems that identify, protect, detect, respond, and recover by design. Early risk assessment, security zoning, and recovery planning create resilience, safeguard uptime, and protect IP. Whether upgrading legacy systems or building new facilities, embedding cybersecurity into engineering ensures operations remain secure, reliable, and future-ready.

Imagine jumping to the moments that matter most in your production and knowing exactly what happened, how long it took, and how often it occurs. Vision AI now enables seamless tracking of anything visible on the factory floor. With 24/7 coverage, it captures leading indicators for safety, quality, and productivity so issues are addressed before they impact output.

In this session, Cyrus Shaoul, Chief Evangelist and Co-Founder of Leela AI, will show how modern vision systems deliver structured, decision-ready data directly from video. The result is clearer visibility into bottlenecks, waste, and process drift that other systems miss. Attendees will learn how leading manufacturers use Vision AI to improve throughput, safety culture, and quality using the cameras they already have.

In today’s automation landscape, it’s easy to get distracted by low-cost suppliers and the latest AI-driven technologies promising instant results. But without a deep understanding of the underlying process, even the most advanced system is destined to underperform.

This session challenges the “technology-first” mindset that too often drives automation projects. Using real-world examples from robotic material removal processes. We’ll explore why successful automation begins and ends with process knowledge. Attendees will learn how to evaluate whether their teams and suppliers truly understand the fundamentals of their operations, how to align technology choices with process realities, and how to avoid the costly pitfalls of chasing price or hype.

Ultimately, this talk provides a candid, experience-based perspective: automation doesn’t solve problems you don’t understand. By focusing on process first, organizations can unlock greater reliability, consistency, and return on automation investment — no matter the technology.

Aircraft manufacturing demands rigorous inspection of components and assemblies — yet traditional inspection workflows remain heavily reliant on human judgment, creating challenges around consistency, scalability, and deployment at remote worksites where specialized expertise may be limited. This session explores how Boeing combines augmented reality (AR) and AI to create a self-validating inspection system that doesn't just overlay digital information on the physical world, but actively confirms whether that overlay is accurate — removing a critical dependency on human verification.

The core technical challenge addressed is one of "latching": ensuring that a 3D CAD model rendered in an AR view is genuinely aligned with the physical component being inspected, not merely displayed near it. To solve this, the system generates composite images by superimposing masked CAD renderings onto real-world camera captures, then feeds those composite images into a trained neural network classifier that determines whether the CAD model is correctly latched to the physical component. The training dataset is constructed automatically by pairing real captured images with both matching and deliberately non-matching CAD poses, generating labeled positive and negative examples without requiring large volumes of manually annotated data.

This session will walk through the end-to-end architecture across four key stages: 

1. Real-time camera pose estimation
2. CAD-matched rendering generation
3. Composite image pipeline construction
4. Classifier training and inference deployment

The session will also cover practical considerations around deploying this kind of system across diverse inspection environments — variable lighting, remote worksites, different component geometries — and the design decisions that make the system robust across those conditions. Data quality and diversity is equally central to success: the system's ability to generalize depends on generating composite training examples that faithfully represent the range of real-world conditions the model will encounter, including variations in camera pose, lighting, and environmental factors such as condensation or air quality. 

Attendees will walk away with concrete insights into designing and training a self-validating AR inspection system — from data pipeline construction and pose estimation to deployment considerations — applicable to any manufacturing or assembly context where component verification is critical.