Automate Innovation STAGE

Many companies are at a crossroads as to whether to invest in a warehouse management system (WMS), warehouse control system (WCS), warehouse execution system (WES), or a combination of the three. The decision is made more confusing because of the overlap of some of the functions of each system. Selecting the right solution is critical for optimizing warehouse efficiency and ensuring seamless operations.

As robotic welding continues to advance, ensuring weld quality remains a critical challenge. Traditional inspection methods often struggle to detect defects with speed and accuracy, leading to costly rework and potential failures. The next major breakthrough? Automated weld inspection powered by 3D machine vision and AI.

In this session, we’ll explore how robotic scanning, 3D sensors, and intelligent software combining rules-based and AI-driven analysis enable fast, reliable detection of defects like porosity, pitting, burn-through, undercut, and spatter. Learn about the key components of an AI-enabled weld inspection system, how it's deployed in real-world applications, and what it means for the future of welding quality control.

Join us to discover how automation is transforming weld inspection and ensuring precision, efficiency, and confidence in every weld.

SightBase®, a Software-as-a-Service (SaaS) platform, revolutionizes the design-in process for machine vision systems, empowering users to create robust solutions with minimal expertise. With intuitive navigation, a physics-based virtual lab, and an unbiased ecosystem approach, SightBase accelerates vision design, turning months of complexity into confident design-in hours.

Design-In Process Barriers
Machine vision technologies have revolutionized industries by enabling automation, quality control, and process optimization. However, the complexity of configuring imaging systems pose barriers such as limited expertise, and months or years of testing.

Who we are?
Teledyne FLIR IIS designs, develops, manufactures, markets, and distributes industrial-grade technologies that enhance productivity and development.

What is our solution for these barriers?
Physics-Based Simulation: SightBase leverages advanced physics-based modeling to generate realistic images based on selected camera components. Users can confidently explore imaging system configurations without extensive technical knowledge.

Virtual Lab: The platform includes a virtual lab where users can experiment with camera, lens, and lighting configurations. This interactive environment accelerates the design-in cycle by drastically reducing the time needed to test and approve imaging configurations.

Machine Vision Ecosystem: A wide selection of area scan cameras ensures compatibility and optimal results with an unbiased and accurate imaging performance representation.

How does the Machine Vision community benefit?
Accelerated Design Cycle: By simulating the imaging design configurations, SightBase removes the need for lengthy trial-and-error cycles that lead to expensive mistakes. User Empowerment: Users with limited knowledge can confidently choose imaging components.

This session is designed for engineers, automation professionals, and industry leaders looking to advance their robotic processes. Join this session to explore the integration of robotics with production machines and machine tools. Subject matter experts will share: how PLC enables programming and control of versatile robotic applications; virtual validation through digital twins and real-time simulations to optimize robotic processes before implementation; and integration of CNC solutions with robotic systems to automate complex machining tasks.

AI-powered automation is advancing at breakneck speed, but there’s one fundamental roadblock: data. AI systems need massive, high-quality, and diverse datasets to learn, but collecting real-world data is an expensive, time-consuming slog riddled with issues—privacy concerns, inherent bias, and the inability to capture rare or edge-case scenarios. Without the right data, AI models hit a wall.

That’s where synthetic data changes everything. Instead of spending months curating datasets, AI teams can generate exactly what they need—instantly with faster, cheaper, and more precise data. Whether it’s rare edge cases, extreme conditions, or diverse environments, synthetic data accelerates AI training and unlocks new possibilities across robotics, manufacturing, and autonomous systems.

Leading this transformation is Symage—a platform that generates custom, photorealistic synthetic datasets with automated, precision labeling, slashing data acquisition time by 90% while boosting model accuracy. Flexible, scalable, and designed for any scenario, Symage empowers AI teams to train smarter, iterate faster, and push automation further—beyond the limits of real-world data.

In this session, we’ll demystify synthetic data—what it is, how it works, and why it’s rapidly becoming an essential tool for AI development. We’ll break down best practices for integrating synthetic data into your training pipelines, key considerations for improving model accuracy, and the trade-offs you need to know. Whether you’re tackling data scarcity, struggling with model generalization, or just looking to optimize your AI workflows, this session will give you the insights to make synthetic data work for you.

Manufacturers today face unprecedented challenges in automation:

• Labor Shortages: 65% of companies report labor constraints.
• Higher Targets: 80% of companies have yield optimization goals for the upcoming year.
• Fewer Resources: Sustainability goals push 70% of companies to do more with less.

Traditional vision systems, while effective, are built on fixed algorithms that cannot adapt to new challenges or uncover insights beyond their initial programming. This is where Vision AI offers manufacturers new capabilities to address these challenges head-on. This presentation will focus on:

The power of continuous retraining, which allows Vision AI models to improve and adapt over time, enhancing efficiency and resilience in dynamic manufacturing environments.

Strategic workforce deployment: Freeing data scientists to focus on innovation while enabling floor operators to directly control and improve models.

Uncovering new data and insights: companies can use vision AI to find value in unexpected places through Vision AI.

Emerging Technologies, such as:

Hyperspectral Sensors: Pushing the boundaries of traditional vision systems by capturing data beyond the visible spectrum—revealing chemical compositions, material properties, and defects previously undetectable.

LLMs and Agentic AI: As companies gain access to advanced Large Language Models, their ability to leverage Vision AI expands dramatically. These models will assist in generating insights from complex data, automating decision-making, and enhancing productivity through agentic AI—where AI systems act autonomously within predefined goals to optimize manufacturing processes.

Join Don Rahrig, CEO of Rain Engineering, for an insightful talk on 'The Roadmap to Smart Factories: Overcoming Barriers to MES Adoption and Integration.' Discover practical strategies to implement MES systems effectively, avoid common pitfalls, and achieve long-term ROI. Learn how to streamline operations, move orders faster, and continuously improve quality with proven methodologies. Don’t miss this opportunity to gain actionable insights from a leader in manufacturing innovation.

Rota Technologies is an exclusive distributor for Keenon Robotics. Keenon was founded in 2010 in China and has a 60% market penetration in the country. Our robots serve the restaurant, hotel, grocery/supermarket/retail, and manufacturing industries.

I’ll be presenting our T10, T9, W3, C30, and S100 robots and how they serve each industry.

There are many things to consider when selecting an industrial automation partner. Selecting the right automation partner goes beyond “can-they-do-it,” to understanding their level of experience and expertise from product development through volume manufacturing and validation.

This session shares insights and critical factors to consider when evaluating and selecting a partner for your next automation project or project expansion.

AI, Digital Twin, Industry 4.0... All these terms are thrown around without a clear understanding or definition. camLine has been highly involved in the digitalization and automation of factories, warehouses, and micro-fulfillment centers, and has a clear perspective on the functional applications of these popular topics.

One of the key applications of Digital Twins that has not yet been fully utilized is Digital Twins used for Simulation. Currently, Simulation is a necessary evil; everyone uses some level of simulation, and everyone is dissatisfied with the accuracy of simulation predictions. Digital Twins enable users to re-create their factory, and importantly, plug in their production control software that makes the important intra-logistical decisions to drive the next generation of simulation.

Join us for a groundbreaking presentation where we'll unveil how Siemens is revolutionizing machine building through the convergence of AI and comprehensive digital twin technology. Discover how machine builders can achieve up to 30% faster time-to-market and reduce engineering costs by leveraging our end-to-end digital thread - from initial concept through virtual commissioning. Whether you're looking to enhance machine efficiency, reduce downtime, or create more flexible production systems, this session will showcase practical applications that are transforming the future of machine building today. Don't miss this opportunity to learn how you can stay ahead of the competition in Industry 4.0 while delivering superior value to your customers through intelligent, connected machines. 

In Kence Anderson’s career, he saw advanced AI that was completely inaccessible to the people who keep our economy running—engineers who design, build, and maintain the physical products that make up much of our world. There are about 100 million of these "engineers of industry"—mechanical, process, industrial, chemical, and electrical engineers—outnumbering software engineers by a factor of ten. Kence started asking himself how he could apply social science concepts on how skills evolve to make AI more accessible. How he could frame AI in terms of teaching so that highly technical but non-programming engineers could leverage it? He founded Composabl to solve the needs and—to align AI with the way engineers think and work. Engineers build from modular components, whether it’s a factory, a rocket ship, or a bulldozer. The Composabl platform brings the same modular, structured approach to AI, making it easier to understand, test, validate, and deploy.

A platform of intelligent building blocks that engineers can use to create powerful, autonomous systems without needing a background in AI development is desperately needed in industrial & large scale processes. The real impact comes from scaling this—enabling millions of people to adopt machine teaching and extend their own expertise. Kance has seen firsthand how AI can accelerate careers, with people earning multiple promotions by leveraging these tools. AI isn’t about replacing workers; just like the internet, databases, and the cloud, it’s a tool that empowers them. By capturing and preserving high-value skills, AI can support the manufacturing resurgence in the U.S. and beyond. At the core of Composabl is this vision: equipping engineers to build intelligent systems that drive real-world impact.

We are living in an exciting era where the industrial landscape is transforming at an unprecedented pace due to rapid advancements in robotics and automation. Visualize production lines optimized by real-time data insights, robots collaborating seamlessly, and material waste minimized. This isn't just a vision, it is a reality we are building together with our partners and customers.

Robots are the icon of the digital era and are one of the most important interfaces bridging AI and the physical world. Thanks to advances in Artificial Intelligence, edge computing and intelligent sensing, the physical, digital, and biological worlds are merging at an accelerated speed. This is transforming the pace of innovation, as well as the complexity and interdependence of systems.

To thrive in today’s rapidly evolving manufacturing landscape, manufacturers require a seamlessly connected and flexible manufacturing environment. Leveraging intelligent edge technologies will allow manufacturers to embrace automation and the use of robots/cobots, capitalizing on access to new data streams and advanced AI solutions to deliver a resilient factory of the future. Join this talk to explore core technologies upon which future solutions will depend and to learn more about how Analog Devices is accelerating robotic platform developments to unlock truly dynamic production flows and hyper-agile manufacturing.

The session delves into the vital role of vulnerability management in securing interconnected OT/IT environments and protecting industrial operations and automation. It highlights the distinct cybersecurity challenges within OT systems in manufacturing and offers insights into solutions that mitigate common vulnerabilities to strengthen operational resilience and maintain business continuity. The discussion also addresses compliance with regulatory frameworks such as NIST, while presenting practical strategies to enhance OT/IT security in the face of an increasingly complex threat landscape.

As manufacturers face increasing demands for higher accuracy, faster deployment of automated visual inspection systems, and greater adaptability, AI-powered inspection is transforming quality control. This session will introduce Generative AI’s role in manufacturing inspection, showcasing how to enable 100% defect detection with only 3 defect images as training data, reducing deployment time to 1 week, and achieving the best OEE of the production line. Learn how Generative AI expands defect datasets and software-defined lighting optimizes inspections across multiple materials and surfaces. Discover how these technologies drive higher OEE, fewer defect escapes, and seamless integration with existing automation systems.

With the rapid growth of digitalization, 5G, and AI, data has become the driving force behind industry transformation, empowering businesses to innovate, optimize operations, and maintain a competitive edge. As industries generate vast amounts of data, storage solutions play a crucial role in managing, analyzing, and protecting it, ensuring a seamless and secure digital evolution while preparing for future challenges.

While we think of the Automation industry as a large market - it pales in size to other markets like Consumer Electronics and Automotive. In fact, many of the building block components of Automation are driven primarily by the volume of those other markets - especially Automotive. In this discussion, we’ll take a look at some of the latest innovations in the Automotive Industry and how they could impact Automation in the future.

Despite AI advances, commissioning physical AI applications remains challenging and time-consuming due to fragmented toolchains and dependence on expert intervention. Additionally, maintenance and operations rely on the tribal knowledge of experienced engineers and operators, making onboarding new operators difficult and expensive.

Siemens and NVIDIA have collaborated to introduce an end-to-end virtual commissioning platform that simultaneously integrates automation and AI modules. This reduces commissioning time compared to traditional methods and lessens the reliance on specialized experts by leveraging advanced simulation platforms like NVIDIA Omniverse and Siemens Process Simulate. Operational capabilities are enhanced through the LLM-based Siemens Industrial Co-Pilot for Operations with live access to technical documentation and real-time operational data. A non-invasive camera-to-VLM circuit provides for additional vision-based reasoning and environmental awareness.

Security has long been treated as a bolt-on function in networking. Traditionally, networks were designed to focus on speed and reliability, with security considerations coming later. Each client or device was responsible for its own protection, creating significant security gaps. Networks prioritize fast switching capacity, often making them "dumb networks." While this design maximizes efficiency, it also creates vulnerabilities where viruses, malware, and unauthorized access can spread rapidly, leading to downtime, equipment damage, and data breaches.

The Role of Segmentation in Cybersecurity
Network segmentation is a powerful strategy to limit the lateral movement of threats. By dividing the network into controlled segments, firewalls can monitor and restrict traffic flow. Deep packet inspection (DPI) strengthens security by analyzing data packets and enforcing stricter security policies. However, while segmentation and DPI improve security, they present implementation and maintenance challenges.

Challenges of Traditional Segmentation
Many security controls focus on north-south traffic, leaving east-west (device-to-device) communication exposed. This lack of segmentation creates blind spots for cyber threats. Even when implemented, segmentation is often ineffective due to complex security policies and resource constraints. Traditional firewalls segment in large zones, allowing threats to spread once inside, compromising multiple devices.

The Burden on Network Operators
Network operators have long faced these trade-offs. VLANs provide some segmentation but add complexity and high costs. In industrial settings, the challenge is greater—OT networks rely on legacy protocols with little security, leaving devices exposed. Unlike IT, OT networks can't afford frequent downtime, as disruptions risk financial losses, safety hazards, and regulatory violations. Strengthening security while ensuring uptime is essential.

The Case for OT-SDN Segmentation
To overcome these challenges, Operational Technology Software-Defined Networking (OT-SDN) is emerging as a game-changer. OT-SDN brings a software-defined approach to segmentation, allowing for dynamic, policy-based security controls that are far more flexible and scalable than traditional methods.

With OT-SDN, network operators can:

• Implement micro-segmentation at the device level, preventing unauthorized lateral movement.
• Automate security policies, reducing manual effort and minimizing human error.
• Gain real-time visibility into network traffic for proactive threat detection.
• Minimize downtime by applying security updates without disrupting operations.

By leveraging OT-SDN, organizations can integrate security into the network architecture, enhancing cyber resilience while maintaining service availability and operational continuity.

Conclusion: Security & Uptime Go Hand-in-Hand
Traditional security methods no longer suffice. OT-SDN segmentation offers a scalable, automated solution to protect critical infrastructure while ensuring uptime. By adopting intelligent segmentation strategies, organizations can strengthen cyber resilience, reduce operational overhead, and maintain reliable service delivery.

The presentation will discuss AI and the role of cloud-based AI training the manufacturing sector. This new approach allows manufacturers to leverage vast amounts of data more efficiently, facilitating real-time insights and improving operational efficiencies. By integrating AI tools into existing processes, companies can enhance predictive maintenance, optimize supply chains, and increase overall productivity.

The integration of 7th axis robot transfer units (RTUs) significantly expands the operational range and versatility of robotic systems. RTUs enable robots to travel along linear and rotary tracks, transforming a single robotic unit into a handling system capable of servicing multiple work cells over a wide area. This advancement allows manufacturers to automate entire assembly processes that were previously constrained by fixed robotic work envelopes. Additionally, RTUs enable a single robot to perform multiple tasks, further enhancing operational efficiency. By extending a robot's reach, RTUs maximize utility and cost-effectiveness in manufacturing.

The successful implementation of 7th axis RTU systems relies on the seamless integration of best-in-class mechanical track systems and motor controls within the robot’s native programming environment. To ensure optimal utility, flexibility, and reliability, the 7th axis must fit effortlessly into the development, deployment, and operational workflow. Bishop-Wisecarver offers a 7th axis solution featuring its patented Dual-Vee guide wheels and a modular track system with self-cleaning capabilities, making it ideal for harsh environments. The control system is fully integrated into the robot pendant programming environment, providing users with a proven, long-term mechanical solution and controls that match the robot's programming flexibility.

Fully dynamic. mobile and configurable manufacturing with autonomous automation in flexible unmanned factories will soon become the standard to meet sustainability goals for a better, more productive & more resilient planet. To enable this, ultra-reliable connectivity, complex synchronous control, and precise, real-time edge sensing have the combinatorial impact to drive efficiency and sustainability improvements for brownfield and new digital factory installations. This requires the seamless integration of wired and wireless connectivity, forming a hybrid network of real-time sensing, complex control, and AI-generated insights. The strident advances with wired connectivity are now being complemented by advances in wireless solutions, especially private 5G, where dedicated spectrum provides secure and scalable wireless industrial connectivity solutions.

Dr Olive Murphy, Director for Industrial Innovation at Analog Devices will do a deep dive into the value, challenges, and opportunities of a hybrid networking approach to integrating private 5G and advanced ethernet for flexible and mobile manufacturing.

Manufacturing processes performed by hand are often dependent on manual inspection and manual QA processes. While automated inspection technology using smart cameras and computer vision offers improved accuracy, real-time analysis, and increased throughput, the variability of hand-assembled products—such as wired assemblies with complex and irregular configurations—has historically challenged traditional automated inspection methods.

Recent advancements in Sony's Vision AI technology are transforming this landscape. These innovations reduce the complexity and costs traditionally associated with deploying Vision AI, making it possible to automate visual inspection of hand-assembled products without requiring complex programming or infrastructure.

This presentation explores how these technologies are overcoming the challenges of manual inspections and providing manufacturers with scalable, accurate, and efficient solutions.

Robotics is undergoing a renaissance, with countless innovations shaping industries at a frenzied pace. Intel® RealSense™ has been at the forefront of this revolution, enabling breakthroughs in Autonomous Mobile Robots (AMRs), Autonomous Guided Robots (AGRs), and other AI-driven applications across industrial environments, distribution, warehousing, retail, transportation, and beyond.

In this session, Chris Matthieu, Chief Developer Evangelist for Intel RealSense, will explore the fascinating developments in computer vision and the future of automation. We’ll dive deep into the innovations that have helped move the industry forward over the past five years and share what we foresee on the horizon. From advancements in industrial vision applications to new breakthroughs in robotics, this discussion will give you a firsthand look at how Intel RealSense is transforming industries and accelerating the next wave of automation.

Explore Software Defined Automation through Schneider Electric's EcoStruxure Automation Expert. Learn about the three pillars transforming industrial control: open ecosystems for hardware-independent code, virtualized control systems, and seamless digital continuity. Through case studies spanning multiple industries, discover how this approach has delivered up to 25% engineering efficiency gains, 65% waste reduction, and 15% maintenance savings while breaking down traditional automation barriers and enabling true digital transformation.

Basic science enables automation technology, but automation is slow to come to basic science. This is an enormous waste of researchers' time and budget while contributing to the replication crisis of science. We present AutoLab, a robot that automates a wide range of repetitive tasks for scientists.

Two-dimensional (2D) materials such as graphene, discovered in 2004, are being extensively studied for their potential uses as next-generation semiconductors, quantum computing qubits, and biomedical sensors. But scientists working on 2D materials are burdened with an almost impossible task. Imagine a room with 1000 LEGO pieces of all sorts of shapes and colors scattered on the floor, and your job is to organize them neatly and then build a castle strictly according to the instruction sheet!

AutoLab automates the searching, cataloging, and stacking of 2D material flakes, the LEGO pieces of the nanoscale world, using advanced computer vision algorithms. AutoLab’s hardware consists of a microscope, a heater stage, and an “arm”, which enables AutoLab to be used in scenarios much wider than 2D materials.

AutoLab has interfaces that can be easily integrated with Large Language Models (LLMs) and with other scientific instruments. We envision a future with AutoLab where science is done in a manner much more manner much more relatable and convertible to industrial production than handcrafting.

Welcome to the next evolution of manufacturing in which human workers and AI agents–your new digital coworkers–collaborate seamlessly across the entire production lifecycle. These intelligent digital agents can autonomously author recipes, execute processes, evaluate quality, and optimize manufacturing workflows within carefully defined parameters.

By implementing these AI collaborators, organizations can exponentially enhance team capabilities—increasing throughput while simultaneously reducing costs of goods sold through significant decreases in waste, human error, and process defects. The result: improved yield and superior product quality.

Today's manufacturers face unprecedented challenges, including critical labor shortages, escalating operational costs, and impending tariffs. Strategic AI deployment offers a compelling solution to these pressures, providing a clear path through operational uncertainties.

The integration of digital coworkers represents a pivotal step toward the widespread adoption of AI-driven manufacturing approaches. This transformation is already redefining innovation boundaries and revolutionizing production environments. AI agents create unified, optimized ecosystems that connect systems, teams, and facilities—delivering benefits across the entire manufacturing process chain.

Humanoid robots have long captured the imagination, but the path to making them truly autonomous in real-world environments remains one of the most complex technical frontiers. In this session, David Goldberg, founder of Red Rabbit Robotics, breaks down the roadmap to full autonomy for humanoid robots. He’ll explore the current limitations of traditional automation, the role of AI foundation models, and the importance of deploying robots in the wild to gather the right data. Attendees will walk away with a clear understanding of what it will take to reach a “ChatGPT moment” for physical-world AI and general purpose humanoid robots.