Using Fuzzy Multi-Criteria Decision Making in Supplier Selection – A Case Study of Mobile Communication Laboratory

• Main Authors: Wan-Yu Ting, 丁婉玉
• Other Authors: Ren-Jieh Kuo
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/39848804030472068565

碩士 === 國立臺灣科技大學 === 工業管理系 === 100 === In recent decades, the mobile communications industry is growing rapidly. From the early 1980s the first generation analog mobile communication systems to today's fourth-generation mobile broadband technology- Long Term Evolution (LTE), industry members continuously develop and upgrade the wireless communication technology to create business opportunities. With the rapid development of mobile communications industry, the relevant regulations are promulgated accordingly. Prior to entering the market, the product not only has to comply with the mandatory regulation published by governments, but also need to perform the conformance testing, even performance testing (Over the Air OTA). After the certificates issued, the product can be successfully sold in the market. These testing and certification are only allowed to performe in the accredited mobile communication laboratory. Manufacturers in selecting mobile communications laboratories need to consider many factors, such as professionalism, price, delivery and so on. Since mMost of the criteria are with qualitative resistance, the decision-makers can not make a judgment on the precise value and different criteria degree of importance can not be a clear distinction. Besides, experts usually make decisions with hesitation (Szmidt and Kacprzyk, 2000) and it causes that expert’s opinion can not be precisely measured as well as reduce the decision-making efficiency. Therefore, mobile communications laboratory selection can be treated as a fuzzy multiple criteria decision making (MCDM) problem. There are three purposes in this study. Firstly, identify the mobile communications laboratory selection criteria through literature review and expert interview. Secondly, use fuzzy AHP to evaluate the selection criteria weights. Finally, use the weight values evaluted by fuzzy AHP to integrate with fuzzy ideal solution similar for order preference (Fuzzy TOPSIS) for mobile communication laboratory performance ranking and propose appropriate management recommendations for each laboratory. Basically, this study can provide a systematic laboratory selection mode so that the mobile manufacturers can have a more objective and impartial tool during the testing and certification laboratory selection.