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研究生:林照挺
研究生(外文):Chao-Ting Lin
論文名稱:以特徵式模型建構塑膠射出成形產品成本預估及產品雛型設計價值分析系統
論文名稱(外文):Building a Cost Estimation of Plastic Injection Products and Value Analyze System for Concept Products by Feature-Based Models
指導教授:王河星王河星引用關係
指導教授(外文):He-Sing Wang
口試委員:陳琨太車振華
口試委員(外文):Kun-Tai ChenZhen-Hua Che
口試日期:2006-12-15
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:工業工程與管理系所
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2006
畢業學年度:95
語文別:中文
論文頁數:146
中文關鍵詞:塑膠射出成形成本預估類神經網路決策支援系統
外文關鍵詞:Plastic injection partsTarget costingCost estimatingNeural networkDecision support systems
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塑膠射出產品已廣泛地應用於各項日常生活中必需品及高科技商品。然而在現今激烈的競爭環境下,從事塑膠射出產品生產之企業為具優異的競爭力勢必著力於縮短新產品的開發時間,於其他競爭者之前將新產品引入市場,以滿足客戶需求。如此,不僅可快速地佔有廣大的目標市場,亦可具有引導價格的優點。目標成本途徑是一種在新塑膠射出產品開發過程中能有效降低與控制成本的創新程序。而特徵式模型(Feature-Based Models)架構則是目前研發工程師普遍地應用於表現新產品概念的3D建構工具。因此,本研究將結合特徵式模型及目標成本以建構新塑膠射出產品成本評估模式,並開發產品雛型設計決策支援系統,以有效地協助設計/工程師提昇概念評估決策品質與縮短新產品開發時間。
本研究首先將利用特徵式模型結合類神經網路建構塑膠射出成形件之新產品概念成本估價程序,並配合目標成本途徑以發展結合產品功能及價值的產品結構成本之估算模式,使新產品的概念評估既能符合市場/客戶的需求,亦可達成企業獲利的目標。最後將完成以產品為主軸的各類成本屬性資料庫,作為決策支援系統的主要資料來源,進而開發具使用者介面之產品結構成本專家評估系統,以輔助決策人員快速且精確地獲得新產品之開發時間及成本資訊。
The major objective of concurrent engineering is to consider the related downstream manufacturing information during the design stage. Among those, estimating manufacturing cost during the early design stage is one area which has been drawn little attention by the researchers. However, if the product manufacturing cost can be estimated during the design stage, designers can modify a design to achieve proper function and reasonable cost in the early product development process.
The purpose of research is utilizing the concept cost evaluation decision support system to assist designer to make a correct decision and shorten the time of the cycle of new product development. We will use the Feature-Based Models and neural network to construct the process of cost estimation about the new product of plastic injection parts. The first, the target costing is an innovative control system to minimize those costs that are determined in product development. And we will integrate target-costing process with Feature-Based models property in cost estimation during the early stage of concept development process. In this paper, we discuss to estimate the cost of the plastic injection parts by neural network. It is a system of profit planning and cost reduction that control costs before they incurred, is committed to continual improvement in product and process designs, is externally focused on customers and competition, and systematically relates complex web of value-chain and cross-function relationships into a cohesive and integrated planning and execution system. The last, we will construct a database that includes every kind of cost in order to become the major source of decision support system.
摘 要 i
ABSTRACT ii
誌 謝 iv
目 錄 v
表目錄 vii
圖目錄 ix
第1章 研究動機與目的 1
1.1 研究背景與動機 1
1.2 研究目的 6
第2章 文獻探討 9

2.1 產品目標成本 9
2.1.1 成本預估 9
2.1.2 目標成本的意義與目的 10
2.1.3 產品開發中目標成本階段性任務 11
2.1.4 目標成本的執行工具與技術 12
2.1.5 品質機能展開 13
2.1.6 價值工程 19
2.1.7 分析層級程序法 20
2.2 塑膠射出成形 22
2.2.1 塑膠射出成形基礎製程 23
2.2.2 產業界塑膠射出成本計算法則 24
2.3 類神經網路 27
2.3.1 類神經網路簡介 27
2.3.2 類神經網路架構 28
2.3.3 類神經網路類型 29
2.3.4 類神經網路之優點 35
2.4 決策支援系統 37
2.4.1 使用者介面 38
2.4.2 模式管理 39
2.4.3 資料管理 39
第3章 研究方法 41
3.1 問題描述與定義 41
3.2 研究架構 41
3.3 研究方法及進行程序 43
3.3.1 塑膠射出成形件成本預估 45
3.3.2 產品結構成本預估 55
3.3.3 產品雛型設計價值分析 60
3.3.4 產品結構成本決策支援系統 73
第4章 塑膠射出成形成本預估模組 80
4.1 零件特徵資料蒐集及資料前處理 81
4.1.1 塑膠射出產品影響成本的因素資料蒐集 81
4.1.2 資料前處理 83
4.2 類神經網路架構設定 84
4.2.1 預設網路架構 85
4.2.2 學習速率與慣性因子測試 88
4.2.3 學習週期之測試 92
4.3 權重值輸出 96
4.4 預測模型之精確度分析 97
第5章 系統分析與開發 101
5.1 系統假設 101
5.2 系統開發流程 101
5.3 系統模型 103
5.4 資料庫建置 104
5.5 模式庫建置 107
5.5.1 AHP權重評估模型 108
5.5.2 塑膠射出成形成本預估模型 110
5.5.3 產品結構成本預估模型 111
5.5.4 產品雛型設計價值分析模型 111
5.6 建構使用者介面 112
第6章 案例導入 122
6.1 案例選擇 122
6.2 新雛型產品開發導入 124
6.2.1 目標成本與顧客需求產生 125
6.2.2 產品雛型設計與選擇 126
6.2.3 建置相關度評估矩陣 132
6.2.4 目標成本評估及零組件設計決策建議 134
第7章 結論 136
7.1 塑膠射出成形件的成本預估模型 136
7.2 成本預估與產品雛型設計價值分析決策支援系統 137
參考文獻 139
[1]Alter, S., “A Taxonomy of Decision Support Systems,” Sloan Management Review, vol.19, no.3, 1977, pp. 39-56.
[2]Ansari, S. L., Bell, J. E. and the CAM-I Target Cost Group, “TARGET COSTING,” IRWIN Press, vol. 24, 1997, pp.128.
[3]Azadivar, F., Ordoobadi, S. and Xue, Y., “A Decision Support System for the Initiation of Technological Innovation in Small Manufacturing Enterprises,” Industry & Higher, vol. 14, no. 4, 2000, pp.249-253.
[4]Basheera, I. A. and Hajmeerb, M., “Artificial neural networks: fundamentals, computing, design, and application,” Journal of Microbiological Methods, vol.43, 2000, pp. 3-31.
[5]Bina, R. S., Robert, C. C. and Sidharta, S., “Neural networks for cost estimation (Part 2),” AACE International Transactions, 2003, pp. 14.1-14.10.
[6]Bode, J., “Neural networks for cost estimation: simulations and pilot application,” International Journal of Production Research, vol.38, 2000, pp.1231-1254.
[7]Bode, J., “Decision support with neural networks in the management of research and development: concepts and application to cost estimation,” Information & Management, vol. 34, 1998, pp.33-40
[8]Carter, W. K., Usry, M. F. and Hammer, L. H., Cost accounting: planning and control, 10Rev Ed edition, Kentucky: South-Western Educational Publishing, 1999.
[9]Cavalieria, S., Maccarroneb, P. and Pinto, R., “Parametric vs. neural networkmodels for the estimation of production costs: A case study in the automotive industry,” International journal of Production Economics, vol. 91, 2004, pp. 165-177.
[10]Chau, K.W., “Particle swarm optimization training algorithm for ANNs in stage prediction of Shing Mun River,” Journal of Hydrology, in press, 2006, doi:10.1016/j.jhydrol.2006.02.025.
[11]Chen, M. Y. and Chen, D. F., “Early Cost Estimation of Strip-Steel Coiler Using BP Neural Network,” Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, Piscataway, NJ, vol. 3, 2002, pp. 1326-1331.
[12]Chiang, W. K. and Zhang, D., Zhou, L., “Predicting and explaining patronage behavior toward web and traditional stores using neural networks: a comparative analysis with logistic regression,” Decision Support Systems, vol. 41, 2006, pp.514-531.
[13]Cooper, R. and Slagmulder, R., Target Costing and Value Engineering﹐Illinois: Productivity Press﹐1997.
[14]Defazio, Thomas, L., Alexander, C. Edsall, &Richard, E. Gustavson, Concurrent Design of Products & Processes, Ohio: McGraw-Hill, 1989.
[15]Donald, G. B., and Dimitris, I. C., “Polymer Processing Principles and Design,”John Wiley & Sons, Inc., vol. 4, 1998.
[16]Georgy, M. E. and Barsoum, S. H., "Artificial neural networks model for parametric estimating of construction project costs," Journal of Engineering and Applied Science, vol. 52, iss. 6, 2005, pp. 1050-1066.
[17]Günaydın, H. M. and Doğan, S. Z., “ A neural network approach for early cost estimation of structural systems of buildings,” International Journal of Project Management, vol. 22, 2004, pp. 595-602.
[18]Hanson, S. J., “Backpropagation: some comments and varianetworktions,” In: Rumelhart, D.E., Yves, C. (Eds.), Backpropagation: Theory, Architecture, and Applications. Lawrence Erlbaum, NJ, 1995, pp. 237–271.
[19]Hashem, A. T., Alex, P. and Maha, T., "Preliminary cost estimation of highway construction using neural networks," Cost Engineering, vol. 41, iss. 3, 1999, pp. 19-6.
[20]Hauser J. R. and Donald, C., “The House of Quality,” Harvard Business Review, vol.66, 1988, pp.63-73.
[21]Hundal, Mahendra S., Systematic Mechanical Designing: A cost and management perspective, New Yorr:American Society of Magazine Editors (ASME), 1997.
[22]Ikeda, M. and Hiyama, T., “ANN based designing and cost determination system for induction motor,” IEE Proceedings-Electric Power Applications, vol. 152, no. 6, 2005, pp. 1595-1602.
[23]Keen, G. W. and Scott, M. S. Decision Support Systems: An Organizational Perspective, John Wiley & Sons, 1985.
[24]Kim, G. H., Yoon, J. E., An, S. H., Cho, H. H. and Kang, K. I., “Neural networkmodel incorporating a genetic algorithm in estimating construction costs,” Building and Environment, vol. 39, 2004, pp. 1333-1340.
[25]Kim, W. C., Mauborgne R. , Blue ocean strategy:How to Creat Uncontested Market Space and Make the Competition Irrelevant, United States of America:Harvard Business School Pubishing Corporation, 2005.
[26]Looney, C. G., “Advances in feedforward neural networks- Demystifying knowledge acquiring black boxes, ” IEEE Transactions on Knowledge and Data Engineering, vol. 8, no. 2, 1996, pp.211-226.
[27]McKim R. A., “Neural Network Applications to Cost Engineering,”Cost Engineering, vol. 35, no.7, 1993, p p. 31-35.
[28]Niazi, A. and Dai, J. S., Balabani, S., and Seneviratne, L., “Product Cost Estimation: Technique Classification and Methodology Review,” Journal of Manufacturing Science and Engineering, vol. 128, no. 2, 2006, pp. 563-575.
[29]Pahl, G. and Beitz, W., Engineering Design-A Systematic Approach, 2nd edn., London: Spring-Verlag, 1996.
[30]Park, J. H. and Seo, K. K., ” Incorporating life-cycle cost into early product development,” Proceedings of the Institution of Mechanical Engineers: Part B : Journal of Engineering Manufacture, vol. 218, no. 9, 2004, pp. 1059-1057.
[31]Poh, H. L., A Neural Network Approach for Marketing Strategies Research and Decision Support, PhD thesis, Stanford University, 1991.
[32]Rush, C. and Roy, R., "Analysis of cost estimating processes used within a concurrent engineering environment throughout a product life cycle," 7th ISPE International Conference on Concurrent Engineering: Research and Applications, Lyon, France, July 17th - 20th, 2000, pp. 58-67.
[33]Saaty, T.L., The Analytic Hierarchy Process, Ohio: McGraw-Hill, 1980.
[34]Scott Morton,Decision Making, Division of Research, Cambridge MA, 1971.
[35]Seo, Kwang-Kyu, Ahn, B. J., “A learning algorithm based estimation method for maintenance cost of product concepts,” Computers & Industrial Engineering, vol. 50, 2006, pp. 66-75.
[36]Shelly, Cashman, Rosenblatt, Systems Analysis and Design, Fifth Edition, Thomson Course Technology, 2003.
[37]Shneiderman, B., Designing the User Interface, Massachusetts: Addision Wesley Longman Inc., 1998.
[38]Shtub, A. and Versano, R., “Estimating the cost of steel pipe bending, a comparison between neural networks and regression analysis,” International Journal of Production Economics, vol. 62, 1999, pp. 201-207.
[39]Shtub, A. and Zimerman, Y., “A Neural-Network-Based Approach for Estimating the Cost of Assembly Systems,”International Journal of Production Economics, vol. 32, no. 2, 1993, pp. 189-207.
[40]Sprague, R. H. Jr. and Carlson, E. D., Building Effective Decision Support System, New Jersey: Prentice Hall, 1982.
[41]Stewart, R., Wyskidsa, R. and Johannes, J., Cost Estimator''s Reference Manual, 2nd ed., New Jersey: Wiley Interscience, 1995.
[42]Tan, P. N., Stinbach, M., Kumar, V., Introduction to Data Mining, Boston: Pearson Education, 2006, pp.101-105.
[43]Tani, T., Hiroshi, Nobumasa, O., Yoshihide, S. I., Junji, F. and Shiran, C. “Target Cost Management in Japanese companies: Current State of The Art,” Management Accounting Research, 1994, pp.67-81.
[44]Takahiro, A., “Plastic Age,” Tokyo: Plastics Age, vol. 46, 2000.
[45]Taylor, I. M., "Cost engineering-a feature based approach," 85th Meeting of the AGARD Structures and Material Panel, Aalborg, Denmark, October 13-14, 1997, pp. 14:1-9.
[46]Turban, E. and Aronson, J. E., Decision Support Systems and Intelligent Systems, 6th edition, Prentice Hall, New Jersey, 2001.
[47]Ullman, D.G., The mechanical design process, New York: McGraw-Hill, 1992.
[48]Ulrich, K. T. and Eppinger, S. D., Product Design and Development, 2e, New York: McGraw-Hill, 2000.
[49]Vrbsky, S. V., “A data model for approximate query processing of real time database”, Data & Knowledge Engineering, vol.21, 1997, pp.79-102.
[50]Ward System Group, Neuroshell 2 User’s Manual, Fourth Edition, Ward System Group, Inc., 1996, pp. 109.
[51]Wasserman, G. S., “On How Prioritize Design Requirements during the QFD Planning Process”, IIE Transactions, vol.25, 1993, pp.59-65.
[52]Zhang, Y. F. and Fuh, J. Y. H., “A neural network approach for early cost estimation of packaging products,” Computers & Industrial Engineering, vol. 34, no. 2, 1998, pp. 433-450.
[53]Zhang, Y. F., Fuh, J. Y. H. and Chan, W. T., “Feature-Based Cost Estimation for Packaging Products Using Neural Networks,” Computers in Industry, vol. 32, 1996, pp. 95-113.
[54]Zhou, L. P. and Hu, Z. F., “The application of neural network in the cost estimation of construction,” Xi''an Jianzhu Keji Daxue Xuebao/Journal of Xi''an University of Architecture and Technology, vol. 37, no. 2, 2005, pp. 262-264.
[55]Zurada, J. M., Introduction to Artificial Neural Networks, St. Paul: West Publishing Company, 1992.
[56]丁一賢、陳牧言,資料探勘,台北:滄海書局,2005。
[57]王河星,「型態管理之變更管制電腦輔助系統之建構」,國立台北科技大學,台北科技大學學報,第35卷,第2期,2002,第137-146頁。
[58]王河星,「型態管理模式中工程管制發工系統之建構」,國立台北科技大學,台北科技大學學報,第29卷,第2期,1996,第10_1-10_8頁。
[59]王河星、車振華、林照挺,「塑膠射出產品之成本估算系統架構」,2005知識與價值管理學術研討會,2005,第162-168頁。
[60]赤尾洋二著,新產品開發品質機能展開之實際應用,台北:中國生產力中心,1991。
[61]車振華,主從式可靠度提昇型資料庫之系統架構-建模研究,碩士論文,國立成功大學製造工程研究所,台南,1999。
[62]辛其亮,「如何應用價值工程成本分析法於工程計劃成本控管」,應用價值工程撙節交通建設經費研討會,2001,台北。
[63]財團法人中衛發展中心,資訊運籌管理-CALS 100問,經濟部技術處,台北,1998。
[64]康永成,印刷電路板製造資料模型建構與成本分析,碩士論文,元智大學工業工程與管理研究所,桃園,2002。
[65]張永彥,實用塑膠模具學,台北:全華科技圖書,2004。
[66]張芝明,品牌策略、品牌權益、通路策略對品牌績效之研究—化妝品產業實證,碩士論文,國立台北科技大學工業工程與管理學系,台北,2006。
[67]張斐章,張麗秋,類神經網路,台北:東華書局,2005。
[68]張榮語,射出成形模具設計-操作實務,台北:高立圖書有限公司,2001。
[69]陳柏州,「低利潤時代來臨如何追求高成長」,管理雜誌,第345期,哈佛企業管理顧問公司,2003。
[70]智偉,塑膠模具設計與機構設計,台北:全華科技圖書,1996。
[71]曾懷恩、李榮貴,「以AHP 模式作為評估設計案的決策方法」,設計學報,第三卷,第一期,1998,第43-54頁。
[72]黃東鴻,薄殼射出件翹曲變形與殘留應力研究,碩士論文,成功大學航空太空工程研究所,台南,2002。
[73]楊金聲,利用類神經網路與線性迴歸進行成本預測之研究-以印刷電路板產業為例,碩士論文,中原大學資訊管理學系,桃園,2005。
[74]葉怡成,應用類神經網路,第三版,台北:儒林,2001。
[75]葉怡成,類神經網路模式應用與實作,第八版,台北:儒林,2004。
[76]葉基光, VE價值工程,台北:徐氏基金會,1992。
[77]詹文男、張萬權、王勝宏、高鴻翔、林羿分、秦素霞、陳文棠、楊中傑、戴基峰、張奇、黃麗虹,決勝關鍵-新產品篩選與評估,台北:財團法人資訊工業策進會,2006,第119頁。
[78]資策會資訊市場情報中心(MIC),解讀產業成功密碼2006-2008,台北:財團法人資訊工業策進會,2006,第86-87頁。
[79]趙善中、趙薇、尤柄文,軟體工程,台北:儒林出版社,2003。
[80]劉勝傑,運用階層分析法之產品生態效益評估-以桌上型顯示器為例,碩士論文,國立成功大學資源工程學系碩士論文,台南,2002。
[81]吳安妮,「策略性成本管理的下一領域—目標成本」,會計研究月刊,第140、142期,1997。
[82]黃淳毅,產業特性與新產品開發流程關係之研究,碩士論文,國立清華大學工業工程與工程管理研究所,新竹,2003。
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