Construction of Double-Layer Knowledge Coordination Network for Product Quality Problem Solving

Abstract

Product quality problems are becoming increasingly complex with the increasing richness of product types and functions, making it challenging to solve quality problems with only personal knowledge effectively. Thus, we propose an approach to extract solution knowledge from quality problem-solving data to improve the efficiency of quality problem-solving. Specifically, by analyzing the characteristics of the data, a method for calculating the membership degree of quality knowledge nodes is first designed. The corresponding quality knowledge triads are constructed based on the relationship between the data structures. Subsequently, we build a double-layer knowledge coordination network (DL-KCN) composed of a problem layer and a solution layer. Finally, using the quality problem-solving data generated during the stamping production process of the body-in-white of an automobile manufacturing enterprise, a DL-KCN with practical application significance is constructed. The DL-KCN is beneficial for problem-solvers to address product quality problems.