Using machine learning to understand manufacturing control issues

The authors describe how machine learning can be used to help departmental supervisors to operate a factory as an integrated system. The feasibility of predicting potential problems on the shop floor using symbolic machine learning and neural networks is demonstrated with simulated data of a single...

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Bibliographic Details
Main Authors: Whitehall, B.L., Fulkerson, B., Hall, J., Lu, S.C.-Y.
Format: Conference Proceeding
Language:English
Subjects:
Assembly systems
Knowledge engineering
Machine learning
Manufacturing
Neural networks
Paints
Production facilities
Production systems
Rivers
Systems engineering and theory
Online Access:Request full text
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Summary:The authors describe how machine learning can be used to help departmental supervisors to operate a factory as an integrated system. The feasibility of predicting potential problems on the shop floor using symbolic machine learning and neural networks is demonstrated with simulated data of a single department, paint system, and final assembly line. Rules of operation implicit in the simulation model were identified by both methods.< >
DOI:10.1109/CAIA.1992.200029