Advisory Support System for Effective Statistical Process Control

Continuous increase in the competition and customer expectations has directed the manufacturing operations in an organization to focus on quality related matters and statistical techniques so as to interpret the data as captured at various stages of manufacturing. The developed advisory decision support system uses generic methods to address various problems of quality control and would analyze the enormous volume of data as generated and aid in making quality related decision. In conventional statistical process control applications, the analyzed results have to be interpreted by very experienced operators or quality control engineers. In automated unmanned manufacturing environments, based on Manufacturing Execution Systems (MES), this has been a major drawback. This inherent bottleneck has been overcome by incorporating interpretation expertise in the system. The developed system would help in configuring various rule sets, on violation of which various exceptions would be generated by the system and the expert system would advice for appropriated remedial actions, hence, would act as an advisory support system. The concerned quality control engineers could interactively change these rule definitions. Subsequently, the possible causes of the violations of various rules would be configured as Violation Causes. The set of causes of the rule violation would be associated with a certain type of variable.