Defect-Related Knowledge Acquisition for Decision Support Systems in Electronics Assembly

Abstract

Real-time process control and production optimization are extremely challenging areas. Traditional approaches often lack in robustness or reliability when dealing with incomplete, inaccurate, or simply irrelevant data. This is a major problem when building decision support systems especially in electronics manufacturing, where blind feature extraction and data mining methods on large databases are common. Performance of these methods can be drastically increased when combined with knowledge or expertise of the process. This paper describes how defect-related knowledge on an electronic assembly line can be integrated in the decision making process at an operational and organizational level. It focuses in particular on the acquisition of shallow knowledge concerning everyday human interventions on the production lines, as well as on the conceptualization and factory wide sharing of the resulting defect information. Software with dedicated interfaces has been developed for that purpose. Semi-automatic knowledge acquisition from the production floor and generation of comprehensive reports for the quality department resulted in an improvement of the usability, usage, and usefulness of the decision support system.