Study on Analysis of Failure in the Touch Panel Network Printer by Application of Intuitionistic Fuzzy Sets in Conjunction with Failure Mode and Decision Making Trial and Evaluation Laboratory

• Main Authors: Bai-Ling Ou-Yang, 歐陽百伶
• Other Authors: Ching-Hsin Wang
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/06259627616375148337

碩士 === 國立勤益科技大學 === 專案管理研究所 === 102 === In the face of global competition environment, product innovation and fulfillment of customer needs are issues today's businesses make much account of, whereas failure mode and effects analysis, FMEA is an analytical method for identifying potential failure modes and their effects in order to avoid occurrence of failure or cut down their incidence rate, which is therefore widely used in the product design and manufacturing process. However, there still exist some problems in this model, such as: collected information usually is expressed by subjective language. Risk priority number among factors of severity (S), occurrence ratio (O), and detection (D) may be the same, and the importance amid factors is not necessarily the same and other issues. Hence, the study is to develop the application of decision making trial and evaluation laboratory, DEMATEL to intuitionistic fuzzy sets, IFS in conjunction with FMEA, so as to develop new intuitionistic fuzzy failure assessment. First, this study applies analytic network process, ANP to compute the weight of failure factors and to filter important failure factors, followed by application of intuitionistic fuzzy failure assessment modes, to consider the intuitionistic fuzzy semantics embodying "approval", "objection" and "neutrality" cases, solving problems that risk priority number may be equal or similar. Lastly, combine with the failure causality of DEMATEL to come by the final key failure factor sequencing, and take development and design of "touch panel network printer" as an example to illustrate its application. Through assessment model developed in this study, we can assist engineers in time of product design so that they can more objectively analyze and identify potential failure factors, in order to cut back the probability of failure and lift product quality.