Process Planning Support System Considering Product Quality

Abstract

This paper proposes a new process planning method to achieve intended product quality. The design for the product quality is achieved by total designing and planning of production process considering both good factors and bad factors that affect product quality in the production process. The representation model of quality related production knowledge that is directly used in the computational design method is proposed. The discrete quality related behavior of product in process is modeled. Input information of the proposed design method consists following information: 1) a product structure; 2) feasible operations of the production process; 3) possible quality related causalities in the production process. The design method calculates the space of quality state automatically by this method. Final output information from this method is a good production process (good operations and good sequence) that achieves the intended quality state of final product. In order to develop this production process planning method for keeping the intended quality, this paper proposes a computational representation model of the quality related information in production process. Based on the production process model, a computational recommendation algorithm of production process that can achieve the intended product quality state is developed. The representation, sharing and reuse of production knowledge and know-how are realized based on the proposed production process model. A prototype system for planning a production process without failures of final product is implemented for the purpose of examination and validation for proposed method. A practical design example of a production process planning for one component of an auto-circuit breaker is demonstrated. The methodology proposed in this research addresses: (1) how the product quality in production process should be modeled; (2) how to design good operations and a good process in production that can achieve the intended product quality; and (3) how to apply the proposed method to a practical planning problem of an actual production process.