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Failure Mode and Effect Analysis (FMEA) is an important method to ensure the effectiveness of manufacturing process, which can prevent the happening of various potential failure. If the knowledge of FMEA can be accumulated and utilized reasonably, the quality management in manufacturing process will get decision support timely, and the efficiency of product quality problem analysis also can be improved. But, it is impossible to integrate the dispersive FMEA knowledge in the manufacturing process because there is a lack of unified management criterion of FMEA knowledge. In order to satisfy the requirement to share, reuse, and maintain FMEA knowledge, the representation method of FMEA knowledge based on ontology is put forward in this study. The structure of FMEA knowledge ontology can be described via visual modeling toolUnified Modeling Language. In this study, the FMEA repository has been built and the acquisition, storage and searching of FMEA knowledge has been researched to satisfy the need of sharing and reusing of the FMEA knowledge in the manufacturing process.

SPC provides statistical techniques and graphical displays control charts to enable the quality of conformance to be monitored and special causes of process variability to be eliminated(Montgomery D.C. 2005). Combining with computer technology and the automatic control technology, SPC has realized the product quality on-line control. With online SPC system, a large amount of manufacturing process quality data can be collected and stored in SPC database. These data can be visited via the operation in SPC database, and many kinds of quality reports can be generated for specific using. However, this technology has not been all well applied in enterprises(Venkatesan G., 2003). In practical manufacturing process, after the operators getting the analyzed results from SPC system, they need to make decision to eliminate the fluctuation in manufacturing process. But it is largely dependent on the personal knowledge and experience level of the operator on-site. Under this specific situation, the decision results are uncertain, and it may also lead to the quality problems can’t be solved in time. So, it is very important to find appropriate methods to support the operators’ decision making, especially the techniques which can facilitate the operators make right decision in time. Considering the existing limitations discussed above, this research is prompted by the need to have a technique that will enable the intelligent acquisition of Failure Mode and Effects Analysis (FMEA) knowledge for the decision making in the quality control process. The study specifically looks at the intelligent knowledge searching and reasoning in FMEA repository, which can facilitate the operators decision making. In this chapter, FMEA knowledge sharing in the manufacturing process quality control will be discussed after the brief review of FMEA, and an application system named IQCS has been developed to manage the FMEA knowledge for the manufacturing process quality continual improvement.