Abstract
The green process planning model was a necessary research field of the green manufacturing, which has drawn increasing attention from many scholars. This study proposes a multi-method [Backus–Naur Form (BNF) frame, binary tree,production rules, and objective-oriented methodology] hybrid frame model of process planning and reasoning mechanism. In this model, the hierarchical BNF frame was applied to modeling the structure of parts, the stages of process decisions and the existing green process indicators set. Then, two “procedure” programs were designed for the information exchange among the above models. This green-process planning model was proposed based on the traditional intelligent process planning model and was intended to introduce an overall (compared with the traditional partial green-process planning model) green-process decision mode. In the last section of this paper, a case study of the green-process planning for a stepped shaft is provided along with a number of essential knowledge models to illustrate the feasibility of this hybrid knowledge model.






Similar content being viewed by others
References
Del Prete, A., Primo, T., & Franchi, R. (2013). Super-nickel orthogonal turning operations optimization. Procedia CIRP, 8, 164–169.
Dong, Y., & Xu, J. (2009). Structure coding method for parts. Computer Integrated Manufacturing Systems, 15(8), 1562–1570.
Jain, P. K., & Gupta, V. K. (2005). Operation sequencing using ant colony optimization technique. In: Proceedings of IEEE international conference on system, man and cybernetics, Waikoloa, HI (pp. 270–275).
Jiang, Z., Zhang, H., & Sutherland, J. W. (2012). Development of an environmental performance assessment method for manufacturing process plans. Journal of Advanced Manufacturing Systems, 58, 783–790.
Kendal, S. L., & Creen, M. (2007). An introduction to knowledge engineering. London: Springer.
Kumar, C., & Deb, S. (2012). Generation of optimal sequence of machining operations in setup planning by genetic algorithms. Journal of Advanced Manufacturing Systems, 11(1), 67–80.
Li, C., Tang, Y., Cui, L., & Yi, Q. (2013). Quantitative analysis of carbon emission of cnc-based machining systems. In: Proceedings of 2013 10th IEEE international conference on networking, sensing and control, ICNSC 2013 (pp. 869–874). France: Evry.
Li, S., Liu, Y., Li, Y., & Landors, R. G. (2013). Process planning optimization for parallel drilling of blind holes. Journal of Intelligent Manufacturing, 24, 791–804.
Li, X., Gao, L., & Wen, X. (2013). Application of an efficient modified particle swarm optimization algorithm for process planning. Journal of Advanced Manufacturing Systems, 67, 1355–1369.
Liu, F., Cao, H. J., & Zhang, H. (2005). The theory and technology of green manufacturing. Beijing: Science and Technology Press.
Munoz, A. A., & Sheng, P. (1995). An analytical approach for determining the environmental impact of machining processes. Journal of Materials Processing Technology, 53, 736–758.
Sun, B., & Zhao, R. (2011). Computer aided process planning techonolgy and application. Beijing: Chemical Industry Press.
Venkata Rao, R., & Kalyankar, V. (2013). Multi-pass turning process parameter optimization using teaching-learning-based optimization algorithm. Scientia Iranica, 20(3), 967–974.
Xiao, Y. (2002). Intelligent information processing technology in CAPP. Changsha: National Universit of Defense Technology Press.
Zhang, H., Gen, M., & Seo, Y. (2006). An effective coding approach for multiobjective integrated resource selection and operation sequences problem. Journal of Intelligent Manufacturing, 17, 385–397.
Zhang, H., & Zhang, J. (2013). The Theory and practice of green manufacturing system engineering. Beijing: Science Press.
Zhao, R., & Sun, B. (2003). Computer aided process planning (CAPP). Beijing: Mechanical Industry Press.
Acknowledgments
The authors are grateful to the Technical Editor and all the Reviewers for their valuable and constructive comments. The research is supported by the National Natural Science Foundation of China (NSFC) under Grant No. 51205429, and the National Science and Technology Pillar Program during the 12th Five-year Plan Period of China under Grant No. 2012BAF01B01.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lei, Q., Wang, H. & Song, Y. Hybrid knowledge model of process planning and its green extension. J Intell Manuf 27, 975–990 (2016). https://doi.org/10.1007/s10845-014-0928-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10845-014-0928-1