Moradi, M., and M.G. Mehrabi
Presented in this poster is development of a new methodology for fault identification and root-cause analysis of complex assembly systems. A combination of a knowledge-based system and fuzzy set theory is used to develop this new technique which in essence is an intelligent system that mimics the behavior of an expert in the field and therefore can trace back the source(s) of the fault to the relevant station.
Presented are the concepts of faults; their detection in an assembly line (as an example); and their generic characteristics. Study of their fundamental properties reveals that there are certain levels of uncertainty involved in describing them. This has led us to the adoption of fuzzy sets theory as a fundamental tool for development of this new technique. Examples from Ford assembly operations are provided to show the effectiveness of the approach.