Measuring process capability index Cpmk with fuzzy data and compare it with other fuzzy process capability indices

The index Cpmk is a well-known loss-based process capability index. It can reveal more information about the location of the process mean compared with other classic process capability indices. This index is also more sensitive than other capability indices to any deviations from process mean. When there are some uncertainties in observations, fuzzy logic can be employed to manage these uncertainties. There is some research on different fuzzy process capability indices and this paper is an extension of Tsai and Chen (2006), Chen, Lin, and Chen (2003) for the process capability index Cpmk of fuzzy numbers. In order to find the membership function of process capability index Cpmk, the α-cuts of the fuzzy observation were employed. An example of fuzzy process capability Cpmk calculator was illustrated and compared with other classic fuzzy process capability indices Cp,Cpl,Cpu,Cpk and Cpm . Results showed that fuzzy Cpmk has the advantages of both Cpk and Cpm . Since the index Cpmk is a more sensitive index compared with other classic indices, the fuzzy process capability index Cpmk can be a more sensitive fuzzy index compared with Cp,Cpl,Cpu,Cpk and Cpm

Development of quality criteria for supplier selection

In supply chain management, supplier selection is one of the most important components of production and logistics management for many companies. Selecting the right suppliers based on high quality and reliability will significantly reduce purchasing costs and other costs related to purchasing indirectly. Consequently, the selection of a wrong supplier could be enough to upset the companies' functional and operational position. There are many criteria III order to assess supplier such as quality, delivery, performance and price. Quality is the ongoing process of producing and sustaining relationship by assessing, anticipating and fulfilling stated and implied needs. The methods for assessing the quality of products for suppliers can be divided to qualitative methods such as continuous improvement programs, certifications, technical and design level, and quality for customer and quantitative methods such as yield rate, process capability indices, reliability and rate of rejects. Since each method can evaluate just one aspect of an organization and cannot evaluate the whole production process, they are not suitable to assess the product's quality of supplier selection process. Therefore to address this problem, this study aims to define a real cost-based objective function for assessing suppliers. In order to form the objective function of the model, three main criteria, quality, price and transportation cost were selected. In this method each of quality costs, price and transportation costs were used as parameters. Revised Taguchi loss function was used to assess the quality of products whereas were used a simple linear programming (LP) model and SOLVER software were used to determine the parameters. There are other loss functions such as inverted normal loss function, asymmetric inverted normal loss function, and revised inverted normal loss function. The concepts of them are the same and based on loss, but their formulas and applications are different. This model was also developed by other loss functions. Data were taken from an Iranian Plastic Company and proved that it is workable and beneficial. Finally, a sensitivity analysis was conducted in order to compare the usage of different loss functions. The proposed model has some advantages such as simpler operations research model, integration of quality cost, purchasing cost and transportation cost and better estimation of quality compared with old methods such as rate of rejects

Supplier evaluation and selection using revised Tagichi loss function.

Assessing quality as one of the main criteria for supplier selection is so important. Literature review showed that in order to evaluate the quality of suppliers, some methods such as rate of rejects, quality certification, easy to repair, reliability and process capability indices are so common. These methods can assess just one aspect of an organization and are not appropriate tools for assessing the real quality of the product supplied by the supplier, while loss functions are suitable tools to evaluate the quality. To overcome this problem and because of features of revised Taguchi loss function, this study proposes the use of the revised Taguchi loss function for supplier evaluation and selection. After assessing the quality, using the expected value of the revised Taguchi loss function and integrating of this function with the cost of purchasing and transportation, a simple Linear Programming (LP) model will appear. A numerical example provides the explanation. This model is a very simple linear programming model with excellent estimation of quality, which integrates the quality of supplier, cost of purchasing and transportation costs