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U.S. Leadership in Adoption of Artificial Intelligence in Advanced Manufacturing 
Mike Molnar |  Director | NIST - Office of Advanced Manufacturing

Artificial Intelligence (AI) technologies promise to be the most powerful tools in generations for expanding knowledge, increasing prosperity, and enriching the human experience. The technologies will be the foundation of the innovation economy and a source of enormous power for countries that harness them. As AI moves from an elite niche science to a mainstream tool, engineering will be as important as scientific breakthroughs. Many of the most important real-world impacts will come from figuring out how to employ existing AI algorithms and systems, some more than a decade old.

The U.S. R&D priorities for federal investment in AI and strategic importance of AI and machine learning in advanced manufacturing are summarized in several government reports. Given the complexity of the issues, the characteristics of the manufacturing industry, and the broadly scoped definition and spectrum of AI possibilities, a comprehensive symposium comprised of a series of three workshops was conducted under the auspices of the National Science and Technology Council, Subcommittee on Advanced Manufacturing.  A summary of findings of this symposium will be discussed with respect to manufacturing competitiveness and realizing resilient manufacturing ecosystems through AI. Furthermore, examples of current research  at NIST related to AI standards and implementation of AI in manufacturing will be provided.

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It’s all about the digital thread!

Making Manufacturing Data More usable for Analytics

Jan de Nijs | Tech Fellow for Enterprise Digital Production | Lockheed Martin

Surprisingly, many large corporations are struggling to create viable and profitable advanced analytics solutions using data produced in the Life Cycle chain of products. The problem is not the volume of data: with the proliferation of connected devices, we are now awash in Life Cycle data. Rather, the problem is that data created by Life Cycle Producers (sources) almost always lacks meta-data information that can be used to create a usable digital thread (missing semantics connectors). In other words, it is very hard to develop generalized solutions that can autonomously interpret Life Cycle data and create insights across the product Life Cycle.

This presentation explains the standards-based approach Lockheed Martin is taking to address this issue. The solution centers around a digital thread that has been defined around specific meta-data tags that allow for an automatic link back to the model-based engineering requirements, and an ecosystem of internationally accepted standards. By implementing this solution across the complete Product Life Cycle, analytics solutions can be created that have the potential to become prescriptive, or even cognitive (“the factory runs itself!”).

Why is this applicable? Manufacturing has a lot of trouble retaining skilled data scientists. The problem is that within manufacturing, data scientists are being used as data janitors (manually cleaning up data), instead of enabling them to do what they are good at: creating big  data analytics solutions.

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US Department of Energy contributions to AI Applications in Advanced Manufacturing and Future Directions 

Brian Valentine | Technical Project Manager | U.S. Department of Energy

US Department of Energy contributions to AI Applications in Advanced Manufacturing and Future Directions

 

The US DOE, through its extensive network of laboratories and research institutions, has invested heavily in AI ever since AI was recognized as a distinct scientific and engineering discipline.  Six years ago, the DOE established an Office of Artificial Intelligence to integrate DOE laboratory capabilities in AI with Department of Energy core missions.  Among those missions is the advancement of US manufacturing capabilities. 

 

The Advanced Manufacturing Office within DOE’s Office of Energy Efficiency and Renewable Energy has supported numerous efforts to apply AI to many Advanced Manufacturing areas, including materials discovery, process design and development, and manufacturing automation.  Some of these contributions will be reviewed, and new directions in Advanced Manufacturing outlined.

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A Brief Case Study: Enabling Digital Cognition to Survive in a World of Exponential Data
Ron Norris | Director Operations Innovation | Georgia Pacific

It’s not just biology vs. digital. It’s your digital intelligence vs. your competitor’s digital intelligence. When we consider that data is projected to grow exponentially over the next few years, how we make decisions while creating knowledge and value at the rate that data grows is becoming the next hurdle for business survival. Developing new dashboards may feel like transformation, but dashboards still require someone to interpret and then act on the data being analyzed… and that is done at the speed of biology. As soon as tomorrow, the strategic advantage will include the ability to make objective decisions based on the shared knowledge and collective intelligence of the entire enterprise – at speeds and accuracies that are orders of magnitudes higher than anything previously possible.

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Achieving Digital Transformation by Improving Quality through AI automation
Mike Hollinger | CTO of Vision and Sensor AI/ML | IBM

This talk will feature Ford’s process in implementing and training IBM’s Maximo Visual Inspection platform.  The Maximo Visual Inspection solution supported Ford’s “no fault forward” initiative with in-station process control and quality remediation at point of installation or assembly. This kind of continuous process improvement is helping Ford lower repair and warranty costs, and improve customer satisfaction, while helping employees play a role in bringing technical innovation to the floor.

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Achieving Federated Device-Specific Predictive Maintenance
- a data engineering roadmap -

Dr. Amir Kashani | Director, AI & Digital Product Development | Stanley Black & Decker
Sundeep Kumar | Head of Products and Big Data Services | Sigmoid

Recent research has shown that automobile vehicle model rollback is a multi billion cost every year. IoT and AI-driven analytics have transformed how companies approach equipment creation, maintenance and production line management. Stanley Black & Decker, has thousands of machines installed across Automobile companies plants to automate processes such as welding and bolting. This session will address Real time flagging of issues with the help of near real time dashboards; Ability to slice and dice the data at various levels to understand fault pattern; Programmatically identify faulty parts and prevent them from being added to the finished vehicle

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Adopting Industrial AI for Smarter Manufacturing
Tara Thimmanaik | Systems Architect | Intel Corp.

In this session, Tara will address why it’s not just about getting AI training right, it’s also about taking the environment in which the AI performs into consideration. How efficient data driven manufacturing can help reduce labor costs, increase quality, and maximize profit, especially with the ongoing labor shortage in the industrial sector. It will also explore Barriers to adoption, and how to navigate them and why an ecosystem of easily scalable, end-to end solutions are essential to successful implementation of AI for smarte manufacturing

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Sundeep Kumar has over a decade of experience in the data & analytics industry and has worked with global IT service giants such Mu Sigma, Cognizant Technology, and Infosys. Sundeep has dedicated his career to using data analytics to improve supply chain management through process automation & excellence. At Sigmoid, he has led multiple MLOps and AI related projects in the manufacturing sector to help drive better business strategy.

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Leveraging Industrial AI Toward Zero-Downtime, Zero-Defects Manufacturing
Dr. Mo Abuali | CEO & Managing Partner | IoTco
Isaac Bennett  | Vice President of IT & Digital Transformation | SAF-Holland

A decrease in unplanned downtime or a few percentages of scrap reduction can yield millions of dollars in savings for manufacturers. Does your organization have the necessary organizational and technical maturity to embark on your Industry 4.0 and predictive analytics journey?

 

This presentation will educate the attendees on the “digital tools of the trade” to realize Industry 4.0 in a systematic approach, with focus on the business case ROI, real time connectivity, and predictive AI-enabled technologies for Maintenance 4.0 and Quality 4.0.  

 


Isaac Bennett  | Vice President of IT & Digital Transformation | SAF-Holland

Formerly with automotive tier suppliers like Detroit Manufacturing Systems (DMS) and Maxion Wheels as their Global IT Innovation Manager. He has worked in the Manufacturing IT field for over 20 years, where he led the automotive IT departments global digital transformation initiative, helping plants around the world implement smart manufacturing projects.

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Industry Panel Session

Dan Isaacs | CTO | Digital Twin Consortium
Stephen Mellor | CTO | Industrial Internet Consortium
Mitch Tseng | Co-Chair | Industrial Internet Consortium

 

Digital Twin Consortium drives the awareness, adoption, interoperability, and development of digital twin technology. Through a collaborative partnership with industry, academia, and government expertise, the Consortium is dedicated to the overall development of digital twins. We accelerate the market by propelling innovation and guiding outcomes for technology end-users.

The Industrial Internet Consortium's mission is to deliver transformative business value to industry, organizations, and society by accelerating adoption of a trustworthy Internet of Things. Since its founding in 2014, the IIC has helped build a technical foundation for the Industrial IoT. We work to help organizations take advantage of IoT technology and achieve positive outcomes. We are focused on driving technology innovation that fosters business transformation. Our goal is to help our members get the best return on their IoT investment.

The Augmented Reality for Enterprise Alliance (AREA) is the only global non-profit, member-based organization dedicated to widespread adoption of interoperable AR-enabled enterprise systems.

Augmented Reality offers tremendous potential for enterprises, promising to increase productivity, lower costs, improve safety, enable expertise to be shared more easily, and more. Whether you view it as the next computing paradigm, the key to new breakthroughs in manufacturing and service efficiencies, or the door to as-yet unimagined applications, it is clear that AR will have an unprecedented impact on enterprises of all kinds.

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Using AI To Unlock the True Potential of Today’s Workforce
Chris Kuntz | VP of Strategic Operations | Augmentir

Today’s manufacturing landscape is a dynamic mix of workforce challenges (including those brought on by Covid and the Great Resignation) and innovative solutions –many of which are powered by AI technology.This session will begin with a look at some dynamics in the manufacturing landscape and then focus on ways that technology (such as AI and connected worker solutions that recognize the variability in today’s workforce) are empowering workers by giving them tools and resources that will set them up for success.

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Don’t get left behind waiting for AI/ML to mature
Sanjay Rajan | Head of Industry Solutions | Tulip

The digital transformation that includes AI/ML as a competitive advantage is the key to growth and scalability, yet the industry continues to see hesitance as manufacturers hold back implementing these technologies. For those whose core competency is executing in a physical world and extracting productivity from their workforce and machines, digital transformation can be overwhelming. IT and OT are still divided, and manufacturers continue to be on the fence regarding affordability, technological maturity and ease of execution.

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The Industrial Metaverse and the Future of Work
Konrad Konarski | Chair | AI Innovation Consortium

​Panelists

  • Konrad Konarski, Chair of AI Innovation Consortium

  • William Aiken PhD Student at University of Ottawa

  • Adam Berg, Director of Learning Solutions at TechnipFMC

  • Can Pu, Researcher and Facebook Augmented Reality labs

  • Mike Burgess, Division President Pace Industries

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Panel
Session

The Future of Manufacturing Panel

Panelists coming soon!

The panel will discuss the future of manufacturing;

  • how AI is changing the manufacturing landscape

  • technologies & best practices enabling production & supply chain efficiencies

  • challenges facing todays manufacturers

  • Lean & advanced manufacturing

  • Cyber security and ransomware attacks