A knowledge diagnostic system for product defects

Abstract

The need to fulfill customer satisfaction and increase product quality has motivated many manufacturing firms to investigate and diagnose their product failure. To gain a correct and accurate diagnostic, the entire processing root must be recorded and controlled in every step of the manufacturing process. In this research, a prototype system has been developed for a tile manufacturing company to diagnose tile defects and to recommend actions for improvement. This system consists of two main components, the knowledge base and inference engine. The knowledge base has been developed by capturing data and information that are related to tile defects, such as symptoms, probable causes, types of defects, processes, sub processes, tile classifications, etc. On the other hand, the inference engine has been built by implementing the forward chaining and depth first searching methods to search for the causes of defects. The analysis proves that this system can help the workers in the company to diagnose tile defects and solve the problems. Besides this, the system can also help to share and transfer knowledge among the knowledge workers in the company.