Abstract
During the course of inter-enterprise processing network quality control, for judging and analyzing the others process quality influence of the abnormal process quality, especially key process quality influence, and servicing whole the multi-processes quality control course, the inter-enterprise multi-processes quality control method based on processing network by means of inter-enterprise quality control model based on fractal network is proposed. In the method, multi-processes processing network is constructed by process mapping, the key process can be figured out based on the analysis of processing network sensitivity. To the key process, depending on multi-processes cost function based on cost influence coefficient among processes, the method can establish the comprehensive optimizing object function including cost and error propagation. Depending on the optimum solution of the object function solved by genetic algorithm, the key process can correct to regulate and distribute the control parameters to decrease accumulative error, to avoid false alarm and misstatements originated from the abnormal process. This application course of method could be applied with a multi-processes manufacturing example.
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References
Yang, M., Zhang, Y.: Intelligent Integrated Control Method in Manufacturing Process. In: IEEE International Conference on Automation and Logistics, August 2007, pp. 1640–1645 (2007)
Kano, M., Nakagawa, Y.: Data-based Process Monitoring, Process Control, and Quality Improvement: Recent Developments and Applications in Steel Industry. Computers & Chemical Engineering 32, 12–24 (2008)
Bayazita, O., Karpak, B.: An analytical Network Process-based Framework for Successful Total Quality Management (TQM): an Assessment of Turkish Manufacturing Industry Readiness. International Journal Production Economics 105, 79–96 (2007)
Lopez-ortega, O., Ramirezr, M.: A STEP-based Manufacturing Information System to Share Flexible Manufacturing Resources Data. Journal of Intelligent Manufacturing 16, 287–301 (2005)
Liu, D., Jiang, P.: E-quality Control Architecture for Multistage Machining Processes. Computer Integrated Manufacturing Systems 13, 782–790 (2007) (in Chinese)
Sun, H., Jiang, P.: Complex Weighted Networks-Based Analysis of Mobile Collaboration Space. Journal of Xi’an Jiaotong University 40, 573–576 (2006) (in Chinese)
Dey, S., Stori, J.A.: A Bayesian Network Approach to Root Cause Diagnosis of Process Variations. International Journal of Machine Tools & Manufacture 45, 75–91 (2005)
Wang, H., Pramanik, N., Roy, U., et al.: A Scheme for Mapping Tolerance Specifications to Generalized Deviation Space for Use in Tolerance Synthesis and Analysis. IEEE Transacion on Automation Science and Engineering 3, 81–91 (2006)
Choongyeun, C., Daeik, D.K., et al.: Decomposition and Analysis of Process Variability Using Constrained Principal Component Analysis. IEEE Transaction on Semiconductor Manufacturing 21, 55–61 (2008)
Loose, J., Zhou, S., Ceglarek, D.: Kinematic Analysis of Dimensional Variation Propagation for Multistage Machining Processes With General Fixture Layouts. IEEE Transacion on Automation Science and Engineering 4, 141–152 (2007)
Qin, Y., Zhao, L., Yao, Y., Xu, D.: A Study on Inter-enterprise Quality Control Function Self-organization Reconfiguration Based Fractal Networks. In: Proceedings of the 2007 IEEE International Conference on Robotics and Biomimetics, Sanya, China, December 2007, pp. 1733–1737 (2007)
Wang, L.: The Research on the Construction Method for the Quality Assurance System of the Manufacturing Network. Tianjin University, Tianjin China (2006) (in Chinese)
Zhang, M., Djurdjanovic, D., Ni, J.: Diagnosibility and Sensitivity Analysis for Multi-station Machining Processes. International Journal of Machine Tools and Manufacture 47(3), 646–657 (2007)
Du, S., Xi, L., Ni, J., Ershun, P., Liu, R.: Product Lifecycle-Oriented Quality and Productivity Improvement Based on Stream of Variation Methodology. Computers in Industry 59, 180–192 (2008)
Lin, Y., He, L., et al.: Stochastic Physical Synthesis Considering Prerouting Interconnect Uncertainty and Process Variation for FPGAs. IEEE Transaction on Verylarge Scale Integration (VLSI) System 16, 141–152 (2008)
Du, S., Xi, L., Pan, E.: Modeling and Controlling of Dimensional Variation in Multi-Stage Manufacturing System. Journal of Shanghai Jiaotong University 40, 583–587 (2006) (in Chinese)
Zheng, L., Yang, X.M., Zhang, Z.H., Liu, T.I.: A Web-based Machining Parameter Selection System for Life Cycle Cost Reduction and Product Quality Enhancement. Computers in Industry 59, 254–261 (2008)
Mok, P.Y., Porter, B.: Evolutionary Optimization of Hedging Points for Unreliable Manufacturing Systems. International Journal of Advanced Manufacturing Technology 28, 205–214 (2006)
Gupta, S., Tiwari, R., Nair, S.: Multi-objective Design Optimization of Rolling Bearings Using Genetic Algorithms. Mechanism and Machine Theory 42, 1418–1443 (2007)
Gao, Z.: The Study and Development of the CAPP System of the Engine Air-cylinder Jackets. Central South University of Forestry and Technology, Changsha (2006) (in Chinese)
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Qin, Y., Zhao, L., Yao, Y., Xu, D. (2008). Inter-enterprise Multi-processes Quality Dynamic Control Method Based on Processing Network. In: Xiong, C., Liu, H., Huang, Y., Xiong, Y. (eds) Intelligent Robotics and Applications. ICIRA 2008. Lecture Notes in Computer Science(), vol 5315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88518-4_12
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DOI: https://doi.org/10.1007/978-3-540-88518-4_12
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