對大部分的公司而言，選擇合適的工具機是很重要的決策。在這全球化的環境，正確地採用機器與設備會影響製造的品質與效率，導致降低成本、增加產量並增進各種加工零件的製造彈性。相反地，不正確的選擇將會阻礙公司的生產力。 本研究呈現出以AHP方法選擇四軸CNC切削中心機的程序，包含蒐集選擇機器的文獻、訪談對工具機具豐富經驗的專家、轉換非結構化與不客觀的商業規格書為客觀與階層式的機器選擇之評估準則。為了實證AHP模型的可應用性及了解其在模具設計製造公司中此評估準則之相對重要性，本研究邀請了一家公司作為問卷調查對象。本研究提出的方法具一般性，其亦可應用到其它製造業在選擇工具機的問題上，也期望本研究之成果可做為國內工具機製造公司在發展四軸CNC切削中心機之參考。

Selection of the right machine tools is an important decision for most manufacturing companies. The quality and efficiency of manufacture are affected by the correct adoption of machine and equipment, and it will result in reducing the cost, increasing the production, and enhancing the flexibility for the diverse type of machining parts in this competitive globalized environment. On the contrary, an incorrect selection can retard the productivity of company. This research presents the procedures of AHP method for selecting 4-axis CNC machining centers including searching the literature of selecting machines, consulting experts with abundant experience of machine tool, translating the unstructured and biased commercial specification to the objective and hierarchical evaluation criteria for selecting machines. In order to experiment the applicability of the AHP model as well as to realize the relative importance of the criteria for the mold design and manufacturing company, a company was invited as the survey objective. This method proposed in this research is general in form and can be applied to the selections of other machine tools for other manufacturing industries. Also, it is hoped that the results of this experimental study will provide a reference for the domestic machinery manufacturing company to develop 4-axis CNC machining centers.

TABLE OF CONTENTS

Abstract.........................................................................I
Table of Contents……………………......................IV
List of Tables……………………………..................V
List of Figures………………………………………VI

Chapter 1 Introduction…………………………......1
1.1 Research Background and Motivatio………..1
1.2 Research Objective…………………………....2
1.3 Research Process…………………………….2

Chapter 2 Literature Review……………………...5
2.1 Machine Tools………………………………....5
2.2 Analytic Hierarchy Process………………….16
2.3 Evaluation Criteria for Machines and Equipment.19

Chapter 3 Research Method………………….....21
3.1 Generic Framework……………………….....21
3.2 Establishment of AHP Model……………….24
3.3 Evaluation Criteria of CNC Machine Tools..27

Chapter 4 Data Analysis and Implication……...32
4.1 Case Study .......................................................32
4.2 Data Analysis………………………………....38
4.3 Results and Implication……………………..42

Chapter 5 Conclusion and Suggestion………..43
5.1 Conclusion……………………………………43
5.2 Suggestion……………………………………45

References………………………………………..46

Arslan, M.C., Çatay, B , and Budak, E. (2004). A decision support system for machine tool selection, Journal of Manufacturing Technology Management, 15(1),101–109.
Atmani, A. and Lashkari, R.S. (1998). A model of machine tool selection and operation allocation in flexible manufacturing system, International Journal of Production Research, 36(5), 1339–1349.
Ayağ, Z. and Özdemir, R. G. (2006). “A fuzzy AHP approach to evaluating machine tool alternatives”, Journal of Intelligent Manufacturing, 17, 179–190.
Chang, C. W. et al. (2007). “An application of AHP and sensitivity analysis for selecting the best slicing machine,” Computers & Industrial Engineering, 52, 296–307.
Çimren, C., Çatay, B. ,and Budak, E. (2007). “Development of a machine tool selection system using AHP,” The International Journal of Advanced Manufacturing Technology, 35, 363–376.
Durán, O. and Aguilo (2008), J., “Computer-aided machine-tool selection based on a Fuzzy-AHP approach,” Expert Systems with Applications, 34, 1787–1794.
Expert Choice 2000, Product Brief, http://www.expertchoice.com/productbrief/.
Gerrand, W. (1988). “A Strategy for selecting and introducing new technology/machine tools,” Advanced in Manufacturing Technology III, Proceedings Fourth National Conference on Production Research , 532-536. London.
Kibbe, R. R., Neely, J. E. (1982). Machine Tool Practices, 2nd ed., Wiley , New York.
Krar, S., Gill, A., Smid, P., and Wanner, P. (2003). Machine Tool Technology Basics, 1st ed., Industrial Press Inc., New York.
Lin, Z. C. and Yang, C. B. (1996). “Evaluation of machine selection by the AHP method,” Journal of Material Processing Technology, 57, 253–258.
Luong, L. H. S. (1998). “A decision support system for the selection of computer-integrated manufacturing technologies,” Robotics and Computer-Integrated Manufacturing, 14, 45-53.
Miller, G. A. (1956). “The magical number seven plus or minus two: some limits on our capacity for processing information,” Psychological Review, 63, 81-97.
Myint, S. and Tabucanon, M. T. (1994). “A multiple-criteria approach to machine selection for flexible manufacturing systems,” International Journal of Production Economics, 33, No.1-3, pp. 121-131.
Satty, T. L. (1990). Multicriteria Decision Making: The Analytic Hierarchy Process, RWS Publications, PA.
Saaty, T. L. (1980). The Analytic Hierarchy Process., McGraw Hill, New York.
Smith, G. T. (1993). CNC Machining Technology, Springer-Verlag, London.
Subramanian, G. H. and Gershon, M. (1991). “The selection of computer-aided software engineering tools: a multi-criteria decision making approach,” Decision Science, 22, 1109-1123.
Tabucanon, M. T., Batanov, D. N. and Verma, D. K. (1994). “Intelligent decision support system (DSS) for the selection process of alternative machines for flexible manufacturing systems (FMS),” Computers in Industry, 25,. 131–143.
Wang, T. Y., Shaw, C. F. and Chen Y. L. (2000). “Machine selection in flexible manufacturing cell: a fuzzy multiple attribute decision making approach,” International Journal of Production Reserach, 38( 9), 2079–2097.
Wu, J. H. (1997). “A generic solution framework and a mixed model for selecting an expert system development tool,” Journal of the Chinese Institute of Industrial Engineers, 14( 3), 227-235.
Yurdakul, M. (2004), AHP as a strategic decision-making tool to justify machine tool selection, Journal of Materials Processing Technology ,146, 365–376.