An important consideration for a manufacturer is how to select, evaluate, observe, and finally create a cooperative relationship with existing or new suppliers. Previous research in this area indicates that most enterprises tend to evaluate their suppliers mainly based on quality, delivery performance, and cost. However, it is ineffective for an enterprise to only consider one of these factors when faced with an all-round competitive environment. An analysis tool that can simultaneously integrate numerical decision criteria would be more useful, especially for the machine tool industry with its high proportion of outsourcing operations, short lead times, multiple component categories, and small batches. In an effort to meet this need, an integrated performance evaluation model, using multiple indices that construct a suppliers' integrated evaluation chart (SIEC), is presented in this study. This model can aid managers to understand the problems encountered by their suppliers and lead them to solutions for these problems that are mutually beneficial. Finally, this study offers an illustration of a Taiwanese machine tool manufacturer's use of the SIEC in a practical application.
A suitable set of test data can improve test efficiency and automatic level in automated testing. This paper presents an automatic generation method of test data based on improved particle swarm optimization algorithm, which can significantly improve the efficiency of automated testing.
Software test metric is a quantitative analysis in the software test processes. This paper introduces the method that applies fuzzy logic in software test metric, making software test metric more accurate and efficient. This method can increase liability and accuracy in software test and it is regarded as a practical software metric test. 1
KEYWORDSFuzzy logic; Testing metric; Software test
FUZZY LOGICFuzzy logic was first proposed by LotfiZadeh in 1965, which applies fuzzy set and fuzzy rules to inference through imitating uncertainty concept judgment and reasoned thinking of human brain. Fussy logic solves plenty of uncertain problems derived from the lack of logoic "descipline". Therefore, it can judge and decide effectively in uncertain environment.
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