Development of assist system for analysis of operation data in manufacturing industry using bayesian network.

Abstract

UACJ Corporation manufactures and sells aluminum rolled products and controls the properties of the oil used for rolling to ensure product quality. In the manufacturing industry, there is a tendency for domain knowledge to become genus-specific, resulting in a cognitive bias that domain knowledge is correct. Therefore, in this study an assist tool proposed that can visualize domain knowledge and reflect/reframe hypotheses using pLSA and Bayesian network. The analysis of the oiliness data allows us to gain new insights through clustering and to propose new hypotheses based on the insights. However, using this assist tool is a hurdle it is difficult and labor-intensive. Therefore, an operational system is conceived with functions and UI that would allow easy use of this assist tool.