| 研究生: |
張佳蓉 Chang, Chia-Jung |
|---|---|
| 論文名稱: |
考慮模糊多目標之產品可靠度設計 Fuzzy multi-objective linear programming models for the design of product reliability |
| 指導教授: |
陳梁軒
Chen, Liang-Hsuan |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 工業與資訊管理學系 Department of Industrial and Information Management |
| 論文出版年: | 2010 |
| 畢業學年度: | 98 |
| 語文別: | 中文 |
| 論文頁數: | 73 |
| 中文關鍵詞: | 模糊理論 、可靠度 、品質機能展開 、模糊迴歸分析 、模糊多目標規劃 |
| 外文關鍵詞: | Fuzzy sets, Reliability, Quality function deployment, Fuzzy regression model, Fuzzy multiple objective optimization |
| 相關次數: | 點閱:110 下載:4 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
鑒於新科技技術之競爭策略逐漸以快速導入市場為特點,因此如何確保高顧客滿意之新產品能「即時上市(Time to Market)」,便成為新產品開發與規劃之重要課題之一。新產品之可靠度驗證成敗對整體發展規劃常具有舉足輕重的影響,而其所面臨的挑戰有:第一、來自新材料或新製程導入之知識有限,造成驗證結果的高度不確定性;第二、無法有效結合專家經驗或相關表達方式於產品之可靠度預測上。
本研究欲使用品質機能展開之品質屋為溝通平台,以建構可靠度驗證項目與各設計需求之關係矩陣,使可靠度設計準則之口語型態資料轉換為可分析之線性方程式,由於模式中結合各專家意見使其在應用上大幅提高模式之預測彈性,藉由破壞性檢測或壽命測試等驗證程序來獲得數據,並以模糊迴歸分析法求得各方程式之配適係數,使之對設計準則產生回饋機制藉以修正或穩健準則。隨著產品設計的複雜度越來越高,直覺判斷已逐漸無法因應管理者之多目標決策需求,為了解決可靠度測試之表現差異過大與目標相互衝突的問題,本研究在考慮成本限制與目標之重要性偏好下,於模糊多目標規劃模式中引入新的決策變數,以獲得可靠度之平均滿意度較大與滿意度之離散程度盡可能小的最佳設計需求執行度組合,最後以半導體封裝元件之產品可靠度設計實例來驗證此模式的可行性。
The competitive strategies in developing new technologies should consider short product design cycles. Therefore, the way to introduce new products of high customer satisfaction in the "Time to Market" becomes an important topic at the new product development and planning stage, in which the new product reliability certification usually plays an important role for the success of new products. Two challenges are generally faced with management. Firstly, knowledge on new materials or new process development is limited. In addition, it is difficult to effectively integrate expert’s experience or knowledge for the product reliability prediction.
This study employs quality function deployment as the communication platform to construct the relationship matrix between reliability qualification requirements and design requirements, in order to transform experts’ linguistic information into the mathematical models to increase their applications on the prediction. The destructive test or the reliability life test is implemented to collect the data to build up the optimal fuzzy regression models. Each regression model is considered as a fuzzy goal. A fuzzy goal programming is established to achieve the optimal solution by maximizing the average of achievement degrees of all fuzzy goals and also minimizing the deviation between fuzzy goals under the constraints of cost and preemptive priorities. We finally demonstrate the feasibility of the proposed models by the example of semiconductor packages.
葉峰廷(民 92):品質機能展開之產品規劃模糊目標規劃模式。國立成功大學工業與資訊管理研究所碩士論文。
“Failure Mechanisms and Models for Semiconductor Devices”, JEP-122E, JEDEC Solid State Technology Association, March 2009.
Arikan, F. & Zűlal Gűngőr, 2007, A two-phase approach for multi-objective programming problems with fuzzy coefficients, Information Sciences, 177, 5191-5202.
Bellman, R.E. & Zadeh, L.A., 1970, Decision-making in a fuzzy environment, Management Science, 17, 141-164.
Chen, R.Y., 2009, A problem-solving approach to product design using decision tree induction based on intuitionistic fuzzy, European Journal of Operational Research, 196, 266–272.
Chen, L.H. & Hsueh, C.C., 2007, A mathematical programming method for formulating a fuzzy regression model based on distance criterion, IEEE Transactions on Systems Man and Cybernetics - Part B - Cybernetics, vol. 37, no. 3, 705-712.
Chen, L.H. & Ko, W.C., 2009, Fuzzy linear programming models for new product design using QFD with FMEA, Applied Mathematical Modelling, 33, 633-647.
Chen, L.H. & Tsai, F.C., 2001, Fuzzy goal programming with different importance and priorities, European Journal of Operational Research, 133, 548–556.
Chan, L. K. & Wu, M. L. 2002, Quality function deployment: A literature review, European Journal of Operational Research, 143, 463–497.
Dubois, D. & Prade, H. 1978, Operations on Fuzzy Numbers, International Journal of System Science, 9, 613-626.
Huang, H.Z., Gu, Y.K., Du, X., 2006, An interactive fuzzy multi-objective optimization method for engineering design, Engineering Applications of Artificial Intelligence, 19, 451-460.
Jiang, R. & Murthy, D.N.P., 2009, Impact of quality variations on product reliability, Reliability Engineering and System Safety, 94, 490-496.
Jimenez, M. & Bilbao, A., 2009, Pareto-optimal solutions in fuzzy multi- objective linear programming, Fuzzy Sets and Systems, 160, 2714-2721.
Li, S. & Hu, C., 2009, Satisfying optimization method based on goal programming for fuzzy multiple objective optimization problem, European Journal of Operational Research, 197, 675–684.
Li, B., Zhu, M., Xu, K., 2000, A practical engineering method for fuzzy reliability analysis of mechanical structures, Reliability Engineering and System Safety, 67, 311–315.
Mahapatra, G.S. & Roy, T.K., 2006, Fuzzy multi-objective mathematical programming on reliability optimization model, Applied Mathematics and Computation, 174, 643-659.
Murthy, D.N.P., Rausand, M., Virtanen, S., 2009, Investment in new product reliability, Reliability Engineering and System Safety, 67, 1593–1600.
Peck, D. S. & Trapp, O. D., 1987, Accelerated Testing Handbook, Technology Associates & D. S. Peck Consulting, Corp.
Sohn, S.Y. & Choi, I.S., 2001, Fuzzy QFD for supply chain management with reliability consideration, Reliability Engineering and System Safety, 72, 327–334.
Surapati, P. & Roy, T.K., 2008, Multiobjective transportation model with fuzzy parameters: Priority based fuzzy goal programming approach, Journal of Transportation System Engineering and Information Technology, vol. 8, Issue 3, 40-48.
Tang, J.R., Fung, Y.K., Xu, B., Wang, D., 2002, A new approach to quality function deployment planning with financial condition, Computers & Operations Research, 29, 1447-1463.
Yadav, O.P., Singh, N., Chinnam, R.B., Goel, P.S., 2003, A fuzzy logic based approach to reliability improvement estimation during product development, Reliability Engineering and System Safety, 80, 63–74.
Zadeh, L.A., 1965, Fuzzy Sets, Information and Control, 8, 338-353.
Zadeh, L.A., 1975, The concept of a linguistic variable and its application to approximate reasoning, Part 1, 2, and 3, Information Science, 8, 199-249; 8, 301-357; 9, 43-80.
Zhang, G., Wu, Y.H., Remias, M., Lu, J., 2003, Formulation of fuzzy linear programming problems as four-objective constrained optimization problems, Applied Mathematics and Computation, 139, 383-399.
Zimmermann, H.J., 1978, Fuzzy programming and linear programming with several objective functions, Fuzzy Sets and Systems, 1, 45-55.