AUTOMATE CONFERENCE AGENDA

Christina Pierce

Sales Operations Manager
Panasonic IIoT Solutions

Though the manufacturing industry generally accepts the need to automate, the barrier to entry can cause hesitation. However, there are clear baby steps manufacturers can take to begin their journey to automation. In this session, we’ll look at several initial steps in the manufacturing process that can be improved with IIoT, including paper-based operations, improving material flow, and locating inventory. In greater detail, we’ll dive into each step and how IIoT can be implemented in a simple way to essentially “test the waters” before investing in all-out transformation across the business. For example, eliminating paper and printing costs by replacing paper-based picking operations with an electronic workflow. Finally, we’ll discuss best practices for presenting these ideas to executives, including elevator pitches and ROI benefits, and both the short-term and long-term (obtaining real-time data to generate insights into your operation) benefits of implementing IIoT.

Chris Liu

Edge Product Marketing Manager
Siemens

The volume of data in industry continues to grow. How can you acquire knowledge from this vast amount of information so you can make the right decisions and take fast action? Industrial Edge is an integral part of the Digital Enterprise portfolio that serves to transform endless volumes of data into limitless opportunities. Join us for more information including overview and architecture, benefits and use cases, and where to start with Siemens Industrial Edge.

Max Versace

CEO and Co-Founder
Neurala

The manufacturing world is facing old and new challenge. Companies are facing irregular patterns in consumer demands and heightened pressures on machine utilization, production efficiencies, and quality control – and they need to address all of this with fewer people on the factory floor. In this session, Dr. Massimiliano Versace, CEO and Co-Founder of Neurala, will discuss how deep learning – the branch of AI derived from neural networks - is already enabling manufacturers to meet demand challenges, increase productivity and maintain their competitive advantage. Advances in deep learning are allowing the deployment of AI that’s based on the unique needs (and data) of each manufacturer. This is lifting the typical requirements for large amounts of data, expensive hardware or specialized AI expertise. With less data required and faster training, emerging solutions can automate quality inspection processes that were previously not viable – improving inspection rates, decreasing human intervention, and allowing smaller batches to be inspected – all helping increase ROI.

Christine Boles

VP, Internet of things Group - GM, Industrial Solutions Division
Intel

Manufacturers are always seeking new ways to optimize their operations and reduce costs. Now, as sustainability continues to become top of mind for many organizations, it can seem like a competing objective. However, it’s possible to achieve both business and sustainability goals by adopting a data-driven strategy to fuel AI and machine learning applications. Today, most factories still only leverage a fraction of their operational data due to latency, security, and privacy limitations. However, AI and Machine Learning running at the edge offer manufacturers the ability to connect their equipment and analyze data to gather actionable insights in real-time -- allowing them to maximize throughput, minimize downtime and decrease their environmental footprint. This session will cover strategies for the successful adoption and implementation of AI and machine learning at the edge, common pitfalls and how to avoid them, and highlight real-world use cases.

Paul Santi

General Manager - Automation Systems Group
FANUC America

Sara Masoud

Assistant Professor of Industrial and Systems Engineering Principal Research Scientist
Wayne State University

DIntent prediction also known as intention recognition or detection is one of the core components of social cognition. Human beings, from age of 18 months, have been shown to be able to extrapolate intentions from observed actions. A key technical component for intent prediction from observed bodily movements is the discovery and utilization of the spatiotemporal patterns behind those movements. Although here the focus is on improving human robot interaction in manufacturing, intent prediction can be extended to contribute to active fields of research such as mobility (e.g., intention prediction of human drivers for autonomous driving) and healthcare (i.e., surgeons’ error prevention). In manufacturing, the futuristic vision of robotics and artificial intelligence, where humans and robots can optimally work together, can evolve to reality by developing intention prediction frameworks, by developing algorithms that make collaborative robots smarter while satisfying the safety concerns. To ensure safe data collection and performance evaluation, this project uses the virtual testbed in the Unity game engine, where users can wear HTC Vive sensors to emerge in virtual environment to safely interact with virtual robots. While virtual reality represents detail movements/interactions of the standard robotic arms and humans, deep learning techniques (i.e., a hybrid integration of exogenous Long Short-Term Memory and Graph Convolutional Networks) are used to predict the underling intention behind the observed movement patterns. The proposed methodology and framework will lead to training robots with better HRI, where not only are robots required to be as precise and accurate as possible in fulfillment of human commands, but also are expected to act faster by predicting the intentions of the collaborating humans.

Nathan Bivens

CTO
FORT Robotics

Safety & Security: the Key to Building Trust in Autonomous Systems

Trust is the key to safe, successful robot deployments. But how do we build trust when robots work with people in unpredictable environments? And how can we establish a common trust between multiple machines from different manufacturers? In this session, we will discuss the importance of building trust through functional safety and cyber security. Learn how safety and security form the foundation of trust for autonomous systems, and why you can’t have one without the other. By taking a holistic approach, we can build a common foundation that allows different machines to work safely together while protecting the people around them.

Corey Ryan

Director of Medical Robotics
KUKA Robotics

Ethics and Bias in AI - Understanding the risks

This session will provide a brief overview of AI and how bias impacts the models -- along with the ethical considerations in most models.

• A 10,000 foot view of how it works, and the current status of most AI technologies.
• The importance of data, what it means and its limitations.
• The impact of human designs in the AI world.
• Ethical considerations from a technology and real-world perspective.

Dominik Boesl

Managing Director
Micropsi Industries

Robotics and AI Governance: What’s Needed Today to Drive Sustainable Technologies for Humanity Tomorrow

Robotics is changing the world, unleashing the same if not an even more disruptive and transformational power within the next 50 years as mainstream IT-technology and the Internet have over the last half a century. Nurtured by technological breakthroughs in industrial automation, robotics will exhaustively permeate all domains of the human living realm. Hence, our grandchildren will grow up in a society that is enriched and enhanced by assistive technologies in every imaginable way. They’ll be Robotic Natives (Generation-R), without fear of these new technologies. Even now the role of robotics is rapidly growing in importance in non-industrial application domains, affecting society, economy and the environment. While robot systems are typically developed to address a specific technical, service type or economical need, their broader impact is often insufficiently investigated, if at all.

Compared to the evolution of the Internet, we are facing one big chance: The internet more or less just "happened." With robotics, automation and artificial intelligence, we can still address potential issues in advance. Involving self-regulation in the sense of robotics and AI governance, these challenges have to be discussed on a broad, fact based and interdisciplinary level. Nevertheless, in order to enable sustainable technologies and responsibly drive "Technology for Humanity" (as the IEEE claims it can), we all have to change the way we are thinking, in part identifying the mainstream directions in the field that enable the UN Sustainable Development Goals (SDGs) and encourage their development.

This presentation will further address the challenges and potential solutions being discussed around robotics and AI governance to ensure a responsible and sustainable technologies for humanity for years to come.

Juan Aparicio

VP Product
Rapid Robotics

In this session, the speaker will identify industrial manufacturing and robotic manipulation challenges that can most benefit both from recent academic progress and advances in AI, while at the same time highlight where traditional automation and robotic approaches may perform better.

Leah Dodson

Principle Programmatic Advisor
NextLink Labs

Jeremy Dodson

CISO
NextLink Labs

Jay Korpi

Principle Cybersecurity Advisor
NextLink Labs

Today’s cybersecurity landscape has organizations across the globe on edge. The rise of organized cybercrime has provided attackers more resources than ever before, resulting in critical vulnerabilities being identified and exploited almost daily. How can your organization support modern growth and digital transformation while protecting the security and safety of your assets?

Secure digital transformation in smart manufacturing takes special consideration. As Information Technology (IT) and Operational Technology (OT) become more closely intertwined on both the manufacturing floor and out in the field, organizations are pressed to ensure they are building from a secure foundation. Clear, consistent visibility into your environment is a vital component of a strong foundation, and is a key proactive measure to address a growing attack surface.

Gaining visibility into your environment and enumerating your assets is crucial when undergoing digital transformation and migrating to smart manufacturing processes. Join Cybersecurity Team Jeremy Dodson, Jay Korpi, and Leah Dodson as we answer:

• Who should be involved in asset enumeration and environment visibility activities?
• What business advantages can these core foundational steps unlock for your organization?
• How can clear, consistent environment visibility empower your responsible parties to make better-informed decisions?
• How can asset enumeration help your organization better manage growing supply chain risk?

Niall Mottram

Cambridge Consultants

Details to come.

Matt Wicks

Director of Robotics
Celestica

There is no shortage of excitement in the logistics space today – pandemic-driven e-ccommerce and consumer expectations for same-day delivery, increased by online and curbside pick-up service options as well as the rise of urbanization, and escalating labor challenges. It’s no wonder companies are turning to robotics to help solve these challenges. And yet, with billions of items moved, picked and packed everyday by logistics workers, it takes fleets of hundreds (if not thousands) of robots to drive greater efficiency. This session examines the unique challenges faced by companies exploring robotics solutions and how experienced engineering and manufacturing partners can help you to build at scale – from design to delivery – to drive the desired efficiency gains.

Anthony Navarro

Senior Technical Product Manager
Unity

Simulation is a powerful tool in robotics system development allowing you to design a system that performs in diverse environments, adapts to changes, and operates safely, saving both time and money. This talk will cover the advantages of using simulation in robotic systems development and deployment and explore strategies used in simulation that enable robust and efficient systems.

The real world is an ever-changing, complex environment with many variables to address to deploy a robotic system successfully. While it is possible to start with the physical environment and robots, this approach usually doesn’t scale easily or adapt well to change. Integrating simulation into the design, test, and operational phases allows you to experiment with different designs early, even before purchasing your robots or operating in a physical environment.

Designing the system in simulation allows you to import your CAD models, warehouses, and other assets into a digital environment to represent your intended use case. Simulation can help you determine the systems you need, evaluate space requirements, and experiment with different layouts and configurations. Solutions requiring computer vision can take advantage of synthetic data, allowing automatic generation and labeling of relevant data for machine learning model training.

Creating scenarios in simulation enables testing for every major and minor change made. Learning what works and what needs additional work faster and more efficiently saves both time and money. The real world isn’t static, and test scenarios shouldn’t be either. Domain randomization ensures that solutions don’t just work with a single robot, environment, or object. Dynamic changes in configuration, layout, function, and object placement occur instantly for verification and validation in various scenarios. Simulation easily allows you to apply an infinite range of possibilities, ensuring a robust and adaptable system.

Finally, when the physical system is deployed and operational, it is critical to have the ability to adjust and incorporate changes while maintaining uptime. Simulation allows you to make changes and verify against scenarios to validate proper operation before deploying on the physical system. Adaptation and learning quickly are critical for the longevity of a complex system in a fast-changing and competitive environment.

Tom Knauer

Global Industry Manager – Factory Automation
Balluff

Condition Monitoring And Predictive Maintenance – Application Success Stories

Condition monitoring and predictive maintenance are “hot topics” in factory automation. The number and range of solutions is growing, and knowing where to start and finding the “right” solution can be confusing and difficult. We will discuss some findings based on customer feedback and research the: 1) top customer concerns - unplanned down time, challenging/costly to implement Condition Monitoring solutions, etc.; 2) general phases, symptoms and severities as a machine starts to fail; 3) most commonly monitored machine characteristics (vibration, temperature, etc.); and 4) top assets/machines which are monitored (motors, pumps, spindles, etc.). We will present some “real-life” Condition Monitoring application examples/success stories for these most common assets/machines.

Zach Gomez

Senior Director, Global Logistics Business
Realtime Robotics

Planning for Unplanned Downtime

If you’re in the manufacturing, supply chain or logistics industry you’ve come to understand that downtime is a given. Be it planned or unplanned, there will always be interruptions in the normal flow of business. 100% uptime is a myth; planned downtime due to maintenance or upgrades, and unplanned downtime due to malfunctions, collisions or poor planning, are the reality.

But accepting this industry-wide reality doesn’t mean there is nothing you can do about it; there are ways to get smart about it and shorten how long it lasts.

To solve a problem, you have to understand it. The same can be said of unexpected downtime. Common types of downtime include power outages, breakdowns in equipment, alarm or alert failure, human error, software bugs, poor equipment calibration, or robot collisions, to name a few. Any one of these can be an issue by itself, but some can escalate them, creating a progressing chain of problems. For example, a software update that wasn’t installed in a timely fashion (or at all) can cause a robot to malfunction, driving it to collide with another robot, damaging goods, halting production and necessitating cleaning and recalibration. A small issue quickly grew into a days-long stoppage and a sizable loss of revenue.

Part of minimizing the effect of unplanned downtime is to actively manage the risk of downtime from happening in the first place. There are several areas to concentrate on if you are looking to get ahead of potential problems before they surface and have the potential to become disasters. This presentation will cover where to concentrate your efforts, how to manage your overall downtime risk, and will also share best practices on minimizing downtime by being well-prepared to deal with it.

Amit Goel

NVIDIA

Everything will become smarter in the factory floor, from machines to handlers and from ground vehicles to conveyor belts. Edge AI and Robotics are playing a vital role to transform industrial automation processes to fully autonomous systems in manufacturing and logistics. Adding intelligence at the edge enables machines in production to sense the environment, act autonomously and make critical decisions. Learning, reasoning and reflecting, the AI models deployed in machines and robots can evolve over time with better accuracy and performance. In this session, Amit Goel, will discuss a wide varieties of use cases that have been developed with Nvidia’s AI platform to improve productivity, safety and skills of autonomous machines.

Gerard Andrews

NVIDIA

Details to come.

Prasad Akella

Founder & CEO
Drishti

Jeffrey Liker

Author "The Toyota Way"
Drishti

From pandemics and global warming to changing market dynamics, myriad challenges mean companies need to be ready to alter production at a moment's notice. Manufacturers agree that humans are more adaptable than automation, but human workers present variability. Manufacturers can gain adaptability while error-proofing their workers using AI and video analytics.
 

In this presentation, attendees will learn about:

• Practical assembly uses for AI, computer vision and machine learning.
• How video analytics can reduce training times, decrease defect rates and increase productivity.
• The importance of adaptability in an increasingly competitive industry, and how video analytics can provide a more robust production system.

Join Dr. Prasad Akella, founder and chairman of Drishti, as he discusses what the uncertain future of manufacturing looks like and the technology that will guide us.

Rajat Gupta

Sr. Director, Business Development
Microsoft

The presentation will focus on two aspects of Mixed Reality in the Enterprise

1. How Mixed Reality (Augmented Reality and Virtual Reality) is being adopted in the enterprise? What is working, and what is not? Share what needs to be true for ubiquitous deployment.
2. How Mixed Reality and Metaverse are different? Share Microsoft's view of the Metaverse, and how the industry can come together to develop a human centered Metaverse.

For a deep dive on Microsoft’s perspective of ecosystem, industry and technical forces coming together to empower and transform robotics, automation, and the industries they serve, please see Dan Rosenstein’s “Automation & Robotics in the time of the Industrial Metaverse” Automate presentation in the AI & Smart Automation track.

Piyush Modi

NVIDIA

Prasad Akella

Drishti

Martin Bufi

Musashi AI North America

Quinn Killough

Landing AI

Baris Erol

Siemens

Products flying by on conveyor belts, forklifts speeding across the factory floor and machines busily assembling products - this is a typical scene at manufacturing plants around the globe. In order to implement safer conditions for workers and more efficient processes, manufacturers are automating their environments with sensors. These sensors, such as video cameras, generate vast amounts of data that, when combined with the power of AI, produce valuable insights which manufacturers can use to make their factories safer and more optimized.

Join us for our panel discussion to learn how the world’s leading companies are using vision AI applications to advance operations. Gain insight into solutions that are improving quality control, reducing wastage and minimizing risk factors for workers.

Dan Rosenstein

Group Product Manager
Microsoft

There is a lot of momentum and buzz around the Industrial Metaverse: and why not? It's awesome! And while Mixed Reality gets the most attention, there is also a lot happening that benefits automation and robotics in the Industrial Metaverse.

Join Dan as he walks through how ecosystem heterogeneity, digital transformation and multiple technology enablers (Cloud & Edge, AI, IoT, Digital

Twins, Simulation and Mixed Reality) are coming together to empower and fundamentally transform robotics, automation and the industries they serve in the time of the Industrial Metaverse.

For a deep dive on Microsoft’s perspective of Mixed Reality and the Industrial Metaverse, please see Rajat Gupta’s “Industrial Metaverse & Mixed Reality” Automate presentation in the AI & Smart Automation track.

Xiyang Yeh

CTO
Flexiv Robotics Inc

To meet the demands for increasingly flexible automation environments in manufacturing, healthcare, and agriculture, robots need to truly perceive the environments and utilize the gathered information to synthesize complex intelligent behaviors and reactively adapt to uncertainties during execution. Over the years, there has been significant development in the fields of robotics and machine learning in this direction. In this talk, we will present a brief history of industrial robots and how they have evolved over time. Next, we will highlight key challenges that the next generation of robotic systems will need to address to accomplish difficult to automate tasks such as connector plug-in, precision assembly, and surface finishing. Finally, we will discuss how to meet these challenges through the integration of perception-driven adaptation capabilities in our hardware and software architectures. We will share various technologies and how they have empowered our automation solutions.

Adam Gluck

Founder & CEO
Copia Automation

DevOps tools have transformed how business software is built, but there were barriers in introducing the same toolsets to industrial automation due to the unique nature of PLC programming. Recently, however, companies are starting to embrace Git-based source control to manage their automation projects. Git-based source control enables greater collaboration between teams, suppliers, and customers. It reduces errors, improving quality. And it ensures greater operational optime. We will discuss the advantages of these new approaches and look at specific use cases from leading system integrators, machine designers and manufacturers.

Rogerio Bonatti

Senior Researcher
Microsoft

Natural language is the most intuitive medium for us to interact with other people when expressing commands and instructions. However, using language is seldom an easy task when humans need to express their intent towards robots, since most of the current human-machine interfaces require rigid templates with a static set of action targets and commands. In this work, we provide a flexible language-based interface for human-robot collaboration, which allows a user to reshape existing trajectories for an autonomous agent. We take advantage of recent advancements in the field of large language neural models to encode the user command, and then combine these features with trajectory information, treating the trajectory generation process as a sequence prediction problem.

We evaluate the system in multiple simulated trajectory scenarios, and show a significant performance increase of our model over baseline approaches. In addition, our real-world experiments with a robot arm show that users significantly prefer our natural language interface over traditional methods such as kinesthetic teaching or mouse-keyboard interfaces such as drawing and programming. Our study shows how the field of robotics can take advantage of large pre-trained language models towards creating more intuitive interfaces between robots and machines.

YJ Lim

Sr. Technical Robotics Product Manager
MathWorks

As the demand for highly complex robotics and autonomous systems applications grows, so too does the need for high-performance, easy-to-use, fully integrated development environments that can support robotics developers. And engineers who work on robotics and autonomous systems often run into challenges with modeling and simulation of the complex robotics system to predict robot performance, designing and testing autonomy algorithms in various scenarios before deploying into real industry setting, and running trade-off studies to determine the impact on the mission or requirements given a sensor, algorithm, or component choice. Simulation with Model-Based Design (MBD) is a key capability to help understand the behavior of complex designs of robotics and autonomous systems. This talk will discuss a complete autonomous robotics system development workflow that allows an engineer to easily learn and apply the many functional domains of robotics.

Glenn Saunders

Senior Research Engineer
Rensselaer MIC

In this session, we will discuss a multi-robot system that was developed in response to the COVID-19 pandemic. The pandemic brought to light a significant number of needs and shortcomings. Early on, one need that became readily apparent was that for Emergency Medical Facilities (EMF) that can be set up quickly to serve a variety of health care services, in a variety of settings such as urban and rural. Tent structures have a long and successful history as rapidly deployable, flexible solutions to address this type of need, and thus were selected as the fundamental technology for this project. Manufacturing the type of tent used in EMF applications however, has its own set of challenges. The fabrics used in large tents are strong and heavy to withstand environmental specifications such as snow and wind loads. Manufacturing tents requires joining cut pieces of this heavy material using a variety of processes such as sewing, ultrasonic welding and Radio Frequency (RF) welding. In many cases, large pieces of heavy, dense fabric must be moved through a stationary welder multiple times. As smaller pieces of tent fabric are joined, the pieces that have to be moved or wrangled becomes larger and larger. In general, wrangling these large pieces of heavy, dense material is done manually. This manual wrangling of the heavy tent material is hard, strenuous work. In this project, we develop robotic technologies to assist the direct labor in wrangling large, heavy pieces of tent material to produce Emergency Medical Facilities that address health care needs of the SARS-CoV-2 pandemic.

ARM Institute Technology Project Impact

In this presentation, Dr. Chuck Brandt (ARM Institute Vice President, Technical Initiatives) will outline how the ARM Institute funds and catalyzes robotic technology projects that address critical needs in manufacturing and sustainment. Dr. Brandt will share the process for soliciting and funding projects, key ARM Institute technical focus areas, and a few success stories of projects that are impacting industry.

The ARM Institute is a Manufacturing Innovation Institute (MII) funded by the Office of the Secretary of Defense and part of the Manufacturing USA® network. Since its inception in 2017, the ARM Institute has catalyzed more than 120 projects and leverages its 340+ member organization consortium to solve critical issues inhibiting U.S. manufacturing through robotics and workforce development. Learn more at www.arminstitute.org.

Chuck Brandt

Vice President, Technical Initiatives
ARM Institute

Critical Initiatives in Artificial Intelligence for Advanced Manufacturing Robotics Systems

The Advanced Robotics for Manufacturing (ARM) Institute, the leading national consortium for Robotics and AI, has been working with its 300+ members to identify and prioritize initiatives that make AI/ML more accessible to U.S. Manufacturers. Hear from experts at the ARM Institute and its consortium as they highlight findings and resulting activities from their research, with an emphasis on the role of data, human interaction, and sensory and perception technologies.

Goals of Panel:

1. Discuss what roles Robotics and AI play within organizations and at ARM
2. Discuss the use of AI in ARM research projects
3. Discuss the areas where AI can add value to manufacturing, relative to robotics
4. Discuss challenges
5. Final thoughts on the use of AI in Robotics

Michael Skocik

Program Manager
Advanced Robotics for Manufacturing Institute

Satyandra K (SK) Gupta

Smith International Professor
University of Southern California

Kel Guerin

Chief Innovation Officer
READY Robotics

Michael Skurla

Chief Product Officer
Radix IoT

The IoT acronym has given rise to a myriad of products flooding the market. The actual application and advantage of these technologies, however, has been a convoluted topic within all verticals. IoT devices offer abstract promises of data, but the reality is that much of the conversation on IoT has been on the wrong side of the equation. Built infrastructure whether in buildings, factory automation, logistics, or really any application is a combination of many subsystems, all of which offer a tremendous amount of data now (IoT coined or not). Regrettably, much of the data has been locked up in proprietary ecosystems to date and has been unable to be harnessed for higher purposes collectively. IoT platforms have emerged to address this disjointed architecture allowing a more comprehensive and I.T. friendly way to enable actionable business intelligence. IoT ‘things’ certainly add more data points, but the ability to collect and communicate with everything into one location, while also having real-time and historical data is the key to creating business altering solutions from data.

The primary learning objectives of this program include:

• Define an IoT Platform and how it differs from building management systems (BMS/EMS), SCADA solutions and individual control solution. It truly is not a replacement of any of these.
• Discuss the practical definition of IoT in the constructed world and the idea of a sensory network of players in any application.
• Define Hot data (compared to cold data), and how it relates to an ROI story, and the advantages beyond just simple payback - including what is organically driving this shift by end users and the use within buildings beyond simple energy savings.
• Recognize a ‘platform’ and how it differentiates from a ‘system’, and what advantages a layer such as this plays particularly in multisite operations. (Including case studies)

Teresa Martins

CEO
Neadvance Machine Vision

Throughout history, humankind has always been dependent on technology. People used the technology they had available to help make their lives easier and, at the same time, try to perfect it and bring it to the next level. This was (and still is) the very basic foundation of every industrial revolution. Today we are living the exciting journey of the fourth industrial revolution where data, connectivity and cyber-physical systems are taking their part on every factory, farm, hospital… in the end, in our lives.

In embarking towards cyber-physical systems with unprecedented capabilities, it becomes clear that complexity is increasing and that we do need to find ways to deal with it. The literature shows that relying on traditional architectures and skilled people or process approaches will no longer be compatible with the available resources. In fact, the lack of qualified people is an all-new challenge itself!

The role of model-based and computer-aided engineering will become even more essential, and design methodologies will need to deeply consider interwoven systems and software aspects, including the hidden costs of software. In order to hide complexity, increase quality, reduce human effort needs and, significantly, reduce response times, we need to bring reusability and low code principles from traditional software development to support us dealing with the current revolution. According to Forbes, low code platforms have 14 distinct benefits which can be summarized in three big topics: speed, democratization of software development, and quality.

When we apply low code techniques, automatic program generation/validation tools and machine automation patterns (reusable solutions for recurrent problems) to cyber-physical systems it is clear that it is possible to reduce up to 60% on time-to-line, and potentially up to 68% of the costs while increasing quality by ~25%.

Low code also allows for the introduction of machine learning and deep learning tools in a simple and ubiquitous way. Merging the power of computer vision, robotics and machine learning in a simple and easy to use interface democratizes the use of a very powerful set tools to non-experts maintaining the quality and the control required for their applications. Low code-based approaches should make systems development so easy and fast (for a wide range of contexts) that even a teenager can do it!