# Fuzzy Supplier Selection Method Based on Smaller-The-Better Quality Characteristic
## 2 Literature Review  
The supplier selection model developed by this study adopts the industrial division of labor in the industrial chain as a background and quality as a basis. At the same time, to solve the practical limitation that the sample is so small that the traditional statistical testing accuracy is insufficient, this study develops the fuzzy testing method based on the confidence interval. Subsequently, this study will review the literature according to the above description. There are two important industrial chains in Taiwan, tool machines and electronics, of which the information and communication technology (ICT) has established itself as a crucial player in the global electronics industry [24; 33]. In fact, Taiwan has formed a complete industrial ecological chain from IC design, wafer foundry, packaging and testing to production and assembly [34]. In addition, central Taiwan is an industrial settlement of tool machines. In the face of increasingly fierce global competition, enterprises have paid more and more attention to their specialized core technologies and gradually outsourced non-core components to other manufacturers, or purchased them from suppliers. This type of strategy has become a trend in business models [1; 2; 35]. The selection of suppliers is built on the basis of suppliers' performances. [PERSON] et al. [36] used a questionnaire designed by [PERSON] [37] to investigate the frequency of 23 criteria appearing in different literature and sorted out the most commonly adopted selection criteria in order--delivery time, quality, and capacity. [PERSON] [38] pointed out that product quality, price, delivery time, sales support, equipment and technology, order status, and financial status are seven criteria for the supplier evaluation. According to [PERSON] and [PERSON] [39], the actual transaction data demonstrated that \"quality\", \"price\" and \"delivery time\" of the product are the key factors in selecting suppliers. Besides, many studies have also suggested that a supplier's process quality is very important, as it will affect the quality and functionality of the end-product. Therefore, to ensure the quality of the end-product,suppliers must be selected with caution [12; 25; 27]. Furthermore, nowadays the industry emphasizes the professional division of labor, and the relationship between enterprises and suppliers has evolved from a purely transactional relationship to a strategic partnership. Enterprises can help suppliers improve their production capacity and performance through the partnership of co-prosperity and co-existence, in order to ensure the product quality of all components, as well as the quality of the end-products [40]. The process capability index (PCI) adopts a method of unit-free value quantization to evaluate the process quality level [41; 42; 43]. Plenty of scholars are exploring the relationship between the process capability index and the six sigma quality level to facilitate industrial applications [5; 7; 10; 21; 22]. [PERSON] et al. [11] proposed a six sigma quality index, based on the relationship between PCI and the six sigma quality level. This index can directly reflect the process quality level, as well as the process yield. When the quality level is higher, the process yield is higher as well. Since the evaluation indicators usually contain unknown parameters, the research, which must estimate, by means of sample data, indicated that the sample size is usually not enormous, due to the cost and timeliness considered by the industry [28; 29]. The fuzzy selection model developed based on the confidence interval can solve the inconsistencies of evaluations [28; 29; 30; 31]. In addition, [PERSON] et al. [44] applied the business procurement knowledge base to establish a fuzzy decision support system (DSS) to carry out a more objective supplier selection.