Product-assisted Optimization Method Based on Fault and Patent Knowledge Extraction

Abstract

With the shortening of product life cycles, accelerating the efficiency of product optimization is crucial for companies. For this reason, a method for optimizing the design of auxiliary products with product maintenance data and patent information as the core is proposed. In this method, the text mining technology is used to extract the product maintenance knowledge hidden in the maintenance records, establish a product failure demand matrix to analyse the technical maturity of related fields. According to the patented technology efficacy information, a product knowledge service model for optimization design is established based on patent knowledge and product maintenance information. This model is constructed to provide technical personnel with product optimization knowledge services, which improves the efficiency of product failure optimization and the core competitiveness of the enterprise.