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First World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022): Monday Plenary
Program Organizers: Taylor Sparks, University of Utah; Michael Dawson-Haggerty, Kerfed, Inc.; Elizabeth Holm, University of Michigan; Jin Kocsis, Purdue University; Adam Kopper, Mercury Marine; Benji Maruyama; James Warren, National Institute of Standards and Technology

Monday 8:30 AM
April 4, 2022
Room: William Penn Ballroom
Location: Omni William Penn Hotel

Session Chair: Adam Kopper, Mercury Marine

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8:30 AM Introductory Comments

8:35 AM  Plenary
Industry 4.0 - Creating the Foundation for Machine Learning in Production Manufacturing: David Blondheim¹; ¹Mercury Marine
    The goal of machine learning projects within manufacturing is the implementation of algorithms within production facilities. Although much research today is predictably focused on the development of these machine learning algorithms, without useful process data, this becomes an exercise in futility. The concepts of Industry 4.0 create the data foundation needed for machine learning applications in manufacturing. The automation of this data collection and storage is crucial for production facilities to successfully implement machine learning predictions. Industry 4.0 presents significant challenges, highlighted by many manufacturers never achieving their implementation goals. Considering many small- and medium-sized manufacturing companies have limited technical staff and resources, implementing machine learning in manufacturing hinges on successful automation of data collection.

9:20 AM Question and Answer Period

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