Decision support tool for diagnosing the source of variation

Abstract

Identifying the source of unnatural variation (SOV) in manufacturing process is essential for quality control. The Shewhart control chart patterns (CCPs) are commonly used to monitor the SOV. However, a proper interpretation of CCPs associated to its SOV requires a high skill industrial practitioner. Lack of knowledge in process engineering will lead to erroneous corrective action. The objective of this study is to design the operating procedures of computerized decision support tool (DST) for process diagnosis. The DST is an embedded tool in CCPs recognition scheme. Design methodology involves analysis of relationship between geometrical features, manufacturing process and CCPs. The DST contents information about CCPs and its possible root cause error and description on SOV phenomenon such as process deterioration in tool bluntness, offsetting tool, loading error, and changes in materials hardness. The DST will be useful for an industrial practitioner in making effective troubleshooting.