關於軍事武器系統的設計研發，由於近年來科技的突飛猛進，使得軍方研發的武器系統之精密複雜性提升，與一般企業產品相比，軍方武器系統之設計流程複雜度更高，且軍事武器系統攸關於國防安全，所以其設計研發階段之時間效率更須加以重視，本研究擬以設計鏈作業參考模型(Design Chain Operations Reference- model, DCOR)為基礎，並利用模糊理論(Fuzzy Theory)的運算，量化專家所評量之定性作業間關聯程度，建立作業間的關聯值，做為作業關聯性解析之依據，再以本體論(Ontology)的知識表達法，透過敘述邏輯(Description Logic)與法則式推論方式(SWRL rule)進行推論，以獲得武器系統設計鏈流程中的知識。
基於上述，本研究之目的為建立一個武器系統設計作業關聯性解析系統，當研發設計階段有作業出現問題時，可有效率地往上游追朔引發問題之作業並且往下游推論相關影響之作業，讓專案管理者利用掌握這些關鍵作業來維持整個設計鏈流程的順暢，提升作業效率。

The R&D processes of either commercial or high tech products have faced severe challenge in the recent years due to the business globalization. Many issues have been raised such as shorten product development time, improve design quality, and reduce design cost ..etc. Among those, managing the design process efficiency is an issue rarely been mentioned. For instance, how to properly identify the previous works that might cause a malfunction design task? How to find the following works that have been affected by that malfunction tasks? In this research, a framework to support the reasoning of the casual relations of a malfunction work to assist the project management will be proposed. The design chain of a military solar cell will be modeled according DCOR（Design Chain Operations Reference- model）. Then, the causal relations among the design activities based on the knowledge of military product design experts will be quantified by using fuzzy method. DWR (Discourse, Worlds, Relations ontology）will be used to represent the ontology of the design chain knowledge. Finally, a reasoning engine will be constructed in the Protégé by integrating the DWR ontology and SWRL rules.

1. USD, “DOD Instruction 5000.2 Operation of the Defense Acquisition System,” 2008.
2. Supply-Chain Council, “Design-chain operations reference-model(DCOR) version 1.0,” Supply-Chain Council, Pittsburgh, PA, 2004.
3. Zhao, W. and Liu, J. K., “OWL/SWRL representation methodology for EXPRESS-driven product information model: Part I. Implementation methodology,” Computers in Industry, Vol.59, No.6, pp.580-589, 2008.
4. Choi, Y., Kim, K., and Kim, C., “A Design Chain Collaboration Framework Using Reference Models,” International Journal of Advanced Manufacturing Technology, Vol.26, pp.183-190, 2005.
5. Fulcher, J., “Supply Chain Council Unveils Model for Developing Products,” Manufacturing Business Technology, Vol.26, pp.10-11, 2006.
6. Wu, W.H., Yeh, S.C., and Fang, L.C., “The Development of a Collaborative Design Chain Reference Model for the Motorcycle Industry,” International Journal of Advanced Manufacturing Technology, Vol.35, No.3-4, pp.211-225, 2006.
7. 陳銘崑, 陳少謙, 賴祈宏, 王瀅涵, “設計產業設計鏈規劃程序之研究,” 2006產學合作產業電子化研討會, 2006.
8. 陳銘崑, 黃依邠, 林泰佑, 廖偉淳, “機能性紡織產業設計鏈規劃模式之研究,” 2006產學合作產業電子化研討會, 2006.
9. Zadeh, L. A. , “Fuzzy Sets,” Information and Control, Vol.8, pp.338-353, 1965.
10. Dubois, D., and Prade, H., “Operations on Fuzzy Number,” International Journal of Systems Science, Vol.9, No.6, pp.613-626, 1978.
11. Zadeh, L.A., “The concept of a linguistic variable and its application to approximate reasoning Part1-Part3,” Information Science, Vol.8, No.2, pp.199-249; Vol.8, No.3, pp.301-357; Vol.9, No.1, pp.43-80, 1975.
12. Sheng, H.T., Gwo, H.T., and Kuo, C.W., “Evaluating Tourist Risks From Fuzzy Perspectives,” Annals of Tourism Rerearch, Vol.24, No.4, pp.796-812, 1997.
13. Thomas, A.R., “Selection of Appropriate Defuzzification Methods Using Application Specific Properties,” IEEE Transactions on Fuzzy System, 1997.
14. Huang, C.C., Chu, P.Y., and Chiang, Y.H., “A fuzzy AHP application in government-sponsored R&D project selection,” International Journal of Management Science, Vol.36, No.6, pp.1038–1052, 2008.
15. Lee, Y.C., Sheu, L.C., and Tsou, Y.G., “Quality function deployment implementation based on Fuzzy Kano model: An application in PLM system,” Computers & Industrial Engineering, Vol.55, pp.48–63, 2008.
16. Masmoudi, M., Hans, and E.W., “Fuzzy tactical project planning: Application to helicopter maintenance,” IEEE Emerging Technologies & Factory Automation, 2011.
17. Liang, T.F., and Cheng, H.W., “Application of fuzzy sets to manufacturing/distribution planning decisions with multi-product and multi-time
period in supply chains,” Expert Systems with Applications, Vol.36, pp.3367–3377, 2009.
18. Wang, Y.M., Luo, Y., and Liang, L., “Fuzzy data envelopment analysis based upon fuzzy arithmetic with an application to performance assessment of manufacturing enterprises,” Expert Systems with Applications, Vol.36, pp.5205–5211, 2009.
19. Zheng, L, Y., Dong, H, F., Vichare, P., Nassehi, A., and Newman, S, T., “Systematic modeling and reusing of process knowledge for rapid process configuration,”Robotics and Computer-Integrated Manufacturing, Vol.24, No.6, pp.763-772, 2008.
20. Ramesh, B., and Tiwana, A., “Supporting Collaborative Process Knowledge Management in New Product Development Teams,” Decision Support Systems, Vol.27, pp.213-235, 1999.
21. 陳致琦, “以本體論及語意網路規則語言為基礎建置代理人審計知識之研究-以銷貨交易知識為例,” 國立中正大學, 會計與資訊科技研究所, 2008.
22. Gruber, T., “A translation approach to portable ontology specifications,” Knowledge Acquisition Vol.5, No.2, pp.199-200, 1993.
23. Borst, W.N., “Construction of engineering ontologies,” PhD Thesis, University of Twenty, Enschede, 1997.
24. Studer, R., Benjamins, V.R., Fensel, D., “Knowledge engineering: principles and methods,” Data and Knowledge Engineering, Vol.25, No.1-2, pp.161-197, 1998.
25. Guarino, N., Oberle, D., and Staab, S., “What Is an Ontology? ,” Handbook on Ontologies, Second Edition, 2008.
26. Staab, S., Schnurr, H.P., Studer, R., and Sure, Y., “Knowledge Processes and Ontologies,” IEEE Intelligent Systems, Vol.16, No.1, pp.26-34, 2001.
27. OWL Web Ontology Language Overview, http://www.w3.org/TR/2004/REC-owl-features-20040210/.
28. Noy, N. F., and McGuinness, D. L.,“Ontology Development 101: A Guide to Creating Your First Ontology,”Stanford Knowledge Systems Laboratory Technical Report, 2001.
29. Noy, N.F., M. Sintek., Decker, M., Crubezy, R. W., Fergerson, and M. A. Musen., “Creating Semantic Web contents with Protege-2000,” IEEE, Vol.16, No.2, pp.60-71, 2001.
30. Uschold, M., and Grueninger, M., “Ontologies: Principles, Methods and Applications,” Knowledge Sharing an Review, Vol.11, No.2, pp.93-136, 1996.
31. Kim, H.M., Fox, M.S., and Grüninger, M., “An ontology for quality management - enabling quality problem identification and tracing,” BT Technology Journal, Vol.17, No.4, pp.131-140, 1999.
32. Marcus, R., “First-Order Logic, Second-Order Logic, and Completeness,” First-Order Logic Revisited, Logos Verlag Berlin, pp.303-321, 2004.
33. 關銘,“以OWL DL及SWRL為基礎建置推論雛形系統-以大學排課問題為例,” 中原大學, 資訊管理研究所, 2004.
34. Xenia, F., Sudarsan, R., Mahesh, M., Steven, J.F., and Ram, D.S., An Evaluation of Description Logic for the Development of Product Models, NISTIR 7481, 2008.
35. Giuseppe, D. G., and Maurizio, L., “TBox and ABox Reasoning in Expressive Description Logics,” AAAI Association for the Advancement of Artificial Intelligence, pp.37-48, 1996.
36. Goix, L.W., Valla, M., Cerami, L., and Falcarin, P., “Situation Inference for Mobile Users: A Rule Based Approach. Mobile Data Management,” International Conference on 1-1, pp.299-303, 2007.
37. Zhao, W., and Liu, J. K., “OWL/SWRL representation methodology for EXPRESS-driven product information model: Part I. Implementation methodology,” Computers in Industry Vol.59, No.6, pp.580-589, 2008.
38. 林信成,“驗證以OWL和SWRL為基礎的監控系統,” 國立中正大學, 資訊工程研究所, 2010.
39. 戚玉樑, “以本體技術為基礎的知識庫建置程序及其應用,” 中央警察大學資訊學報, Vol.5, No.2, pp.1-18, 2005.
40. Christopoulou, E., Goumopoulos, C., and Kameas, A., “An ontology-based context management and reasoning process for UbiComp applications,” In Proceedings of the Joint sOc-EUSAI'2005 Conference, pp.265-270, 2005.
41. Protégé 3.4.4, http://protege.stanford.edu/.
42. Charles, L. F., “Rete: A fast algorithm for the many pattern/many object pattern match problem,” Department of Computer Science, Carnegie-Mellon University Pittsburgh, PA 15213, U.S.A., 1982.
43. Martin, O. C., Holger, K., Samson, Tu., Benjamin, G., Mike, D., William, G., Mark, M., “Supporting Rule System Interoperability on the Semantic Web with SWRL,” Fourth International Semantic Web Conference (ISWC2005), Galway, Ireland, pp.974-986, 2005.
44. Bellman, R.E., and Zadeh, L.A., “Decision-making in a fuzzy environment,” Management Science, Vol.17, No.4, pp.141-146, 1970.
45. Larry, P.E., “Improving Data Warehouse and Business Information Quality,” Wiley Computer Publishing, 1999.