## 1 Introduction
### Research Framework  
A novel quality defects diagnosis method based on product gene theory and knowledge base was developed to address the problems of the quality defects diagnosis of the manufacturing process for large equipment in this study. First, a product gene model and a sectional encoding method for the quality control of the manufacturing process of large equipment were proposed. In the model, the processing surface was the minimum information granularity to conform the production characteristics of large equipment and to improve the flexibility of the proposed product gene model. Then, a similarity evaluation rule and an optimization method of the weights of elements based on particle swarm optimization (PSO) were addressed to filter the available knowledge of the product gene knowledge base. In terms of the characteristic of many-to-many between quality defects and quality influence factors in some cases, a fuzzy comprehensive evaluation (FCE) method was developed for the further localization of diagnosis knowledge. The experiment applied in this study has shown that the proposed method can effectively support the quality defects diagnosis of the manufacturing process for large equipment. The framework of the method mentioned above is shown in Figure 1.  
In the framework, the proposed method includes two parts: product gene theory and the quality defect diagnosis method. The former is the application foundation of the latter. As shown in Figure 1, the product gene model and encoding method are applied to extract the target gene. The similarity calculation rule is applied to retrieve and filter knowledge genes from the product gene knowledge base, where direct similarity and synthetic similarity are used to filter knowledge genes. In addition, a PSO is developed to optimize the weights of elements in the target gene for calculating synthetic similarity. The fuzzy comprehensive evaluation method is applied to get diagnostic results (i.e., quality defects diagnosis shown in Figure 1). Finally, these results will be validated according to the actual manufacturing information of the defective product, and then a new knowledge gene will be established with the encoding method. The contributions of this study can be summarized as follows:  
(1) A quality gene model and a corresponding encoding method are developed. Compared with the existing studies, the model provides good flexibility in application.  
Figure 1: The research framework of the quality defects diagnosis method based on product gene theory.  
(2) Both similarity evaluation rule and fuzzy comprehensive evaluation are applied in the study to meet the characteristic of many-to-many between quality defects and quality influence factors.  
(3) An optimization of weights based on PSO is developed in the study to improve the calculation method of similarity and obtain more accurate diagnostic results.  
The rest of this paper is organized as follows. Section 2 gives an overview of the related work about product gene theory and its application. Section 3 defines the product gene model, encoding method, similarity calculation rule, and the mode of evolution. Then, a quality defects diagnosis method based on the proposed product gene model and methods is explained in Section 4. In Section 5, an experiment about bearing spacer in an M5018A roller press is applied to illustrate the method proposed in Section 4. Finally, conclusions are drawn in Section 6.