Using machine learning to understand manufacturing control issues

Abstract

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.<>