Research on Network Manufacturing Resources Optimization Deployment

Abstract:

Networked manufacturing environment, making the task decomposition and exist out of line manufacturing cell optimization problem, propose a pre-matching rules and genetic algorithm combined with the resources optimal deployment method. In the process the task decomposition process layer by layer from the pre-match rules for task decomposition process and manufacturing units to form the pre-matching set of manufacturing unit, and when complete the task decomposition process generates the appropriate set of pre-matching manufacturing unit and then use genetic algorithm solution to processing costs, transportation costs, processing time and transportation time to build a multi-objective optimization model; to simplify the calculation, the multi-objective problem by the weight method into a single objective problem; calculated from the manufacturing unit eventually chooses the optimal set of manufacturing cells combination, making the process task global optimum processing route. Finally, exemplify the feasibility of the method.

• Periodical: Advanced Materials Research (Volumes 542-543)
• Pages: 485-494
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.542-543.485
• Online since: June 2012
• Authors: Xiao Na Song, Shu Ai Sun, Hai Chao Liu
• Keywords: Matching Rule, Multi-Objective Optimization (MOP), Resource Deployment, Task Decomposition

References

[1] MA Xue-fen, Dai Xu-dong, SUN Shu-dong. Optimization Deployment of Networked Manufacturing Resource [J].Computer Integrated Manufacturing Systems-CIMS, 2004(5) 524-527.

[2] YAO Chang-feng, ZHANG Ding-hua, PENG Wen-li, LI Shan, Resources optimization deployment approach for complicated parts in networked manufacturing [J]. Computer Integrated Manufacturing Systems-CIMS, 2006(7)1061-1067.

[3] ZHOU Ke, LU MIN, WANG Gang, REN Bing-Yin. Collaborative optimization of manufacture task decomposition and resource deployment of manufacturing unit [J]. Journal of Harbin Institution of Technology [J]. 2009(11)48-52.

[4] CAO Jian, ZHOU Gen-gui. Web-based Partner Selection and Evaluation in Agile Virtual Enterprises [J]. CHINA MECHANICAL ENGINEERING,2004,15(22):2010-2017.]

[5] WU Nai-qi, SU Ping. Efficient algorithm for partner selection in agile manufacturing [J]. Computer Integrated Manufacturing Systems-CIMS, 2004,10(8):971-979.]

[6] RAO Yun-qin, ZU Chuan-jun, ZHANG Chao-yong. Resource Integration and Execution System in Shop Floor Supporting Networked Manufacturing [J]. Computer Integrated Manufacturing Systems-CIMS, 2003,9(12):1120-1125.

[7] Sun Zhi-jun, Zhu Jian-ying;, Pan Quan-ke. GENETIC ALGORITHM BASED APPROACH TO THE INTELLIGENT OPTIMUM SCHEDULING OF MULTI-RESOURCES IN THE DYNAMIC ENVIRONMENT [J]. Chinese Journal of Mechanical Engineering,. 2002,38(4):120-125

DOI: 10.3901/jme.2002.04.120

[8] Qu Xilong, Sun Linfu, Zhao Huijuan, FanYushun. Analysis and Realization for the System of Optimal Resources Configuration in Networked Manufacturing [J]. Computer Engineering and Application, 2004(34)18-20.