## 6 Conclusions  
To address the problem of quality defects diagnosis for large equipment, a novel quality defects diagnosis method based on product gene theory and knowledge base was developed. In the method, a product gene model and an encoding method based on processing surface were developed, whose mode of evolution was also defined. To apply the proposed product gene theory, a similarity calculation rule of attribute was proposed. A similarity evaluation rule and an optimization method of weights of elements based on PSO were addressed to filter the available knowledge of product gene from the knowledge base. Focusing on the characteristic of many-to-many between quality defects and causes, an FCE method was proposed for further localization of causes of defects. This method provides a different and valuable way for managers to optimize their quality control of manufacturing. According to the experimental process and results in this study, it can be concluded as follows: First, the data as shown in Tables 4 and 6 showed that the proposed product gene model and encoding method can describe the quality information of a product in large equipment manufacturing enterprises reasonably, and it also has good applicability; second, the knowledge genes obtained by filtering with direct similarity and synthetic were verified to be appropriate, so the design of the filtration method in this study is reasonable, in addition, the PSO was also proved to be n effective method to optimize weights of elements in target gene; finally, multiple factors were found to be the causes of defects in the target gene and there are differences in different gene units, thus the proposed quality defects \begin{table}
\begin{tabular}{c c} \hline \hline
**Cause** & **Analysis and Conclusion** \\ \hline \multirow{4}{*}{**om11**} & The ages of machines of rough turning (or semi-finish turning) in \(GU(1)\) is 12 years, \(GU(2)\) is 7 years, and \(GU(3)\) is 8 years. Generally, the processing capacity of a machine older than 10 years will be greatly affected in building material equipment enterprise. Therefore, the “om11” is one of the causes of “sr” in \(GU(1)\). \\ \hline \multirow{2}{*}{om13} & The ages of machines of finish turning in \(GU(1)\) is 5 years, \(GU(2)\) is 8 years, and \(GU(3)\) is 3 years. Therefore, the “om13” should be excluded. \\ \hline \multirow{2}{*}{mat, **mt**} & These two causes can be verified by inspecting the quality of material and measuring tools. In this experiment, the material is qualified, while some of measuring tools are unqualified. Therefore, the “mat” should be excluded and the ‘mt’ should be one of the causes of defects. \\ \hline \multirow{2}{*}{**pw11**} & The capabilities of workers of rough turning (or semi-finish turning) in \(GU(1)\), \(GU(2)\) and \(GU(3)\) are 3, 4, 5, where 4 is the median. Therefore, the “pw11” is also one of the causes of “sr” in \(GU(1)\). \\ \hline \multirow{2}{*}{**cm1**} & The structure of the casting mold is found to be unreasonable. Therefore, the “cm1” is one of the causes of defects. \\ \hline \multirow{2}{*}{cm2} & No impurities are found on the part, therefore, the “cm2” should be excluded. \\ \hline \multirow{2}{*}{**ht1**} & Generally, the holding time of quenching of the part should be about 3.5 minutes. Therefore, the “ht1” should be one of the causes of defects. \\ \hline \multirow{2}{*}{tem1} & The temperature of quenching is reasonable, therefore, the “tem1” should be excluded. \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Analysis of possible causes in the experiment of this study. diagnosis method can meet the characteristic of many-to-many quality defects and causes, and it also has strong flexibility. Therefore, the theories and approaches proposed in this study are effective in quality defects diagnosis. However, there is still much to be studied further, in the future, it would be interesting to build product gene knowledge base with big data and apply product gene theory to other industries for improving its application level and value.