THE OPTIMAL LOCATION OF INSPECTION STATIONS USING A RULE-BASED METHODOLOGY

The location of inspection stations is a significant component of production systems. In this paper, a prototype expert system is designed for deciding the optimal location of inspection stations. The production system is defined as a single channel of n serial operation stations. The potential inspection station can be located after any of the operation stations. Non-conforming units are generated from a compound binomial distribution with known parameters at any given operation station. Traditionally Dynamic programming, Zero-one integer programming or Non-linear programming techniques are used to solve this problem. However a problem using these techniques is that the computation time becomes prohibitively large when the number of potential inspection stations are fifteen or more. An expert system has the potential to solve this problem using a rule-based system to determine the near optimal location of inspection stations. The prototype expert system is divided into a static database, dynamic database and knowledge base. Based on defined production systems, the sophisticated rules are generated by the simulator as part of a knowledge base. A generate-and-test inference mechanism is utilized to search the solution space by applying appropriate symbolic and quantitative rules. The goal of the system is to determine the location of inspection stations while minimizing total cost.