Introduction 

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• Toward a Roadmap for AI Enabled Manufacturing, Mark Maybury (Stanley Black & Decker)

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• Keynote1: The Future of and Work. Dr. Doug Maughan. Convergence Accelerator, National Science Foundation.

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AI for Human Upskilling and Reskilling

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• AI-Enabled Training in Manufacturing Workforce Development. Beverly Woolf, Aritra Ghosh, Andrew Lan, Shlomo Zilberstein and Tom Juravich (U Mass Amherst).

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• Building Ethical AI for Workforce Empowerment, Upskilling, and Reemployment in Manufacturing. Huiling Ding (North Carolina State University) National Science Foundation Convergence Accelerator. 

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• Towards AI-Assisted Smart Training Platform for Future Manufacturing Workforce. Weichao Wang (UNC Charlotte), Xintao Wu (University of Arkansas), Pu Wang (UNC Charlotte), Mark Maybury (SBD) and Aidong Lu (UNC Charlotte).

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• Empowering a Digital Technology Workforce through Alignment and Coordination of Upskilling and Reskilling Opportunities.  National Science Foundation Convergence Accelerator. Jennifer Thornton (Business-Higher Education Forum) and Stephanie Blockinger (Business-Higher Education Forum).

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• Keynote 2: The Elephant in the AI- enabled Factory: Data Integrity. Brad Keywell (Uptake Technologies). ​

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AI to Enhance Sensors and Analytics

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• Real-Time Analytics for IIOT. Bijan Sayyarrodsari (Rockwell Automation) and Tom O'Reilly (Rockwell Automation).

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• Sensors and AI for Factory Automation. Ron Stuver (SICK, Inc), Dave Adams (SICK, Inc) and Kam Yuen (SICK, Inc).

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• AI Applications in Manufacturing Operation. Vivek Diwanji (Cognizant Technology Solutions), Phani Bhushan Sistu (Cognizant Technology Solutions) and Sharath Prasad (Cognizant Technology Solutions).

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• Keynote 3: Old MacDonald Automated His Farm... AI, AI, Oh. Marshall Monroe, MM Magic Productions

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AI for Generative Design and Additive Manufacturing

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• Democratizing Innovation through Design Automation, ‘One-Click’ Manufacturing Services and Intelligent Machines. Binil Starly (North Carolina State University), Atin Angrish (North Carolina State University), Deepak Pahwa (North Carolina State University), Mahmud Hasan (North Carolina State University), Akshay Bharadwaj (North Carolina State University) and Paul Cohen (North Carolina State University).

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• Automatic Volumetric Segmentation of Additive Manufacturing Defects with 3D U-Net. Vivian Wen Hui Wong (Stanford University), Max Ferguson (Stanford University), Kincho H. Law (Stanford University), Yung-Tsun Tina Lee (National Institute of Standards and Technology (NIST)) and Paul Witherell (National Institute of Standards and Technology (NIST)).

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AI for Machining, Assembly/Process Control and Optimization

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• AI Enabled Manufacturing for Those Who Make the WorldTM.  Mark Maybury, Sudhi Bangalore, Eric Cohen and Ashley Baron (Stanley Black and Decker).

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• Stanley Black & Decker: A Case Study in Using Edge AI for Scrap Reduction. Sastry Malladi (FogHorn).

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• Next-Generation of Weld Quality Assessment Using Deep Learning and Digital Radiographic Images. M-Mahdi Naddaf-Sh, Sadra Naddaf-Sh, Hassan Zargaradeh (Phillip M. Drayer Electrical Engineering Department, Lamar University) and Mohammad R. Zahiri and Amir R. Kashani (Artificial Intelligence Lab, Stanley Oil & Gas)

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• Physics-Guided Machine Learning for Self-Aware Machining. Noel Greis (North Carolina State University), Monica Nogueira (North Carolina State University), Sambit Bhattacharya (Fayetteville State University) and Tony Schmitz (University of Tennessee Knoxville).

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• AccuWave: A stochastic Process Model for Accurate and Real-time Ocean Wave Prediction. Zhao Li (Hohai University), Yan Tang (Hohai University) and Zequan Guo (Hohai University). (The article was submitted and accepted. We just don’t have permission to disseminate it)

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AI for Mobility & Human-Robot Cooperation

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• Autonomous Robotic Exploration and Mapping of Smart Indoor Environments With UWB-IoT Devices. Tianyi Wang (Purdue University), Ke Huo (Purdue University), Muzhi Han (Tsinghua University), Daniel McArthur (Purdue Univeristy), Ze An (Purdue University), David Cappeleri (Purdue University) and Karthik Ramani (Purdue University).

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• Developing Metrics and Evaluation Methods for Assessing Artificial Intelligence Enabled Robots in Manufacturing. Adam Norton, Amy Saretsky, and Holly Yanco (New England Robotics Validation and Experimentation (NERVE) Center, University of Massachusetts Lowell).

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• A Common Platform for Semantic Annotation of Manufacturing Data for Machine Learning. Kellehr Guerin, Luke Tuttle  and Jacob Huckaby (READY Robotics)

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Reports 

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• Trust workshop Report