AI-based generation of production engineering labor standards

Increased automation of manufacturing is necessary to compete in today's worldwide markets. The role of artificial intelligence (AI) techniques for incorporating the automation with changing manufacturing environments needs to be investigated. AI techniques can assist in meeting the challenge of transforming shop floor production engineering data into appropriate production engineering labor standards in a timely, consistent, and cost effective manner. Production heuristics can be incorporated into an expert system that can learn from the changing manufacturing environment. This paper presents a prototype expert system which transfers the knowledge of experienced methods engineers into a rule-based system to develop the appropriate job elements and standard times for each engineering task. Manufacturing data taken from a leading US company are used for the testing and validation of the prototype system. The prototype system demonstrated the applicability of automated generation of knowledge transfer to the decomposition of the job into tasks. Further implications of the automated systems are discussed.<
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