随着个性化定制的需求越来越高,离散车间作为企业从事机械零部件生产活动的物理实体将首先应对这种趋势带来的挑战。个性化定制任务随机性强,订单到达时车间状态不定,调度模型难以确立,需要一种摒弃传统调度模型的自动化生产方法。为此,结合物联制造技术和完全动态调度理论,研究如何实现车间层自组织生产,在没有初始调度模型的情况下完成实时动态调度。以离散车间为研究对象,搭建面向实时制造过程的无线射频识别物联环境。并以此为基础,建立面向物理资源的智能个体,使设备本身成为具有通讯、分析、决策能力的独立智能单元。同时引入系统监管类智能个体,克服传统完全动态调度过程中系统全局性难以兼顾的缺点,完善调度性能。最后,研究成果应用于某实验室中的微型工厂,证明了方法可以进行个性化订单的自组织生产,并能有效整合生产资源。
With the increasing requirement for personalized customization service, discrete workshop as a unit in manufacturing system will first have to deal with this challenge which is caused by the personalized customization service. Personalized customization task is stochastic, and the status of shop floor is uncertain before the order arrival. Therefore, it is difficult to establish the traditional scheduling model, and an automated production method is needed. Based on the manufacturing technology of internet of things and the theory of completely dynamic scheduling, the method of self-organization production in job shop layer and real-time dynamic scheduling without scheduling model are studied. The discrete workshop is selected for the study, and the instrumented environment based on Radio Frequency Identification for real-time manufacturing process is constructed. On this basis, the individual intelligent of physical resource oriented is established, and the goal is to make the device becoming an intelligent unit with the capacity of communication, analysis and decision-making. In addition, due to the fact that a system supervisor intelligent individual is introduced, the weakness that the global performance of the scheduling mechanism is difficult to raise in traditional fully dynamic scheduling can be overcome. Finally, the proposed approaches are applied to a micro-factories in a laboratory, the result show that the self-organizing production of individual orders can be carried out and it can effectively integrate production resources.
[1] BKWANGYEOL R, MOOYOUNG J. Agent-based fractal architecture and modelling for developing distributed manufacturing systems[J]. International Journal of Production Research, 2003, 41(17):4233-4255.
[2] 张富强, 付颖斌. 制造物联驱动的工序物流动态规划框架[J]. 计算机集成制造系统, 2016, 22(5):1315-1322. ZHANG Fuqiang, FU Yingbin. Dynamic planning architecture for process logistics driven by Internet of manufacturing things[J]. Journal of Mechanical Engineering, 2016, 22(5):1315-1322.
[3] PAOLO R. Multi-agent based scheduling in manufacturing cells in a dynamic environment[J]. International Journal of Production Research, 2011, 49(5):1285-1301.
[4] ZHANG Y, WANG J, LIU S, et al. Game theory based real-time shop floor scheduling strategy and method for cloud manufacturing[J]. International Journal of Intelligent Systems, 2017(32):437-463.
[5] LEITÃO P, RESTIVO F. A holonic approach to dynamic manufacturing scheduling[J]. Robotics & Computer Integrated Manufacturing, 2008, 24(5):625-634.
[6] BANNAT A, BAUTZE T, BEETZ M, et al. Artificial cognition in production systems[J]. IEEE Transactions on Automation Science & Engineering, 2011, 8(1):148-174.
[7] OUELHADJ D, PETROVIC S. A survey of dynamic scheduling in manufacturing systems[J]. Journal of Scheduling, 2009, 12(4):417-431.
[8] LEITAO P, COLOMBO A W, RESTIVO F J. ADACOR:a collaborative production automation and control architecture[J]. IEEE Intelligent Systems, 2005, 20(1):58-66.
[9] 刘国宝, 张洁. 基于改进滚动时域优化策略的动态调度方法[J]. 机械工程学报, 2013, 49(14):182-190. LIU Guobao, ZHANG Jie. Dynamic schedule method based on improved rolling time domain optimization strategy[J]. Journal of Mechanical Engineering, 2013, 49(14):182-190.
[10] GAO K Z, SUGANTHAN P N, PAN Q K, et al. An improved artificial bee colony algorithm for flexible job-shop scheduling problem with fuzzy processing time[J]. Expert Systems with Applications, 2016, 65:52-67.
[11] KAO H A, JIN W, SIEGEL D, et al. A cyber physical interface for automation systems-methodology and examples[J]. Machines, 2015, 3(2):93-106.
[12] LEITÃO P, KARNOUSKOS S, RIBEIRO L, et al. Smart agents in industrial cyber-physical systems[J]. Proceedings of the IEEE, 2016, 99:1-16.
[13] MCFARLANE D C. Effective RFID-based object tracking for manufacturing[J]. International Journal of Computer Integrated Manufacturing, 2009, 22(7):638-647.
[14] DIMITROPOULOS P, SOLDATOS J. RFID enabled fully automated warehouse management:Adding the business context[J]. International Journal of Manufacturing Technology & Management, 2010, 21(3-4):269-288.
[15] 刘群垚. 制造业的"数字化"未来[J]. 电气工程学报, 2014(3):18-20. LIU Qunyao. The "digital" future of the manufacturing industry[J]. Journal of Electrical Engineering, 2014(3):18-20.
[16] SEIDENMAN P, SPANOVICH J D. RFID在维修中的应用[J]. 航空维修与工程, 2015(9):43-44. SEIDENMAN P, SPANOVICH J D. High-memory RFID applied in maintenance[J]. Aviation Maintenance & Engineering, 2015(9):43-44.
[17] 张映锋, 赵曦滨, 孙树栋, 等. 一种基于物联技术的制造执行系统实现方法与关键技术[J]. 计算机集成制造系统, 2012, 18(12):2634-2642. ZHANG Yingfeng, ZHAO Xibin, SUN Shudong, et al. Implementing method and key technologies for IoT-based manufacturing execution system[J]. Computer Integrated Manufacturing Systems, 2012, 18(12):2634-2642.
[18] HUANG G Q, QU T, FANG M J, et al. RFID-enabled gateway product service system for collaborative manufacturing alliances[J]. CIRP Annals-Manufacturing Technology, 2011, 60(1):465-468.