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.
ZHANG Zequn
,
TANG Dunbing
,
JING Yongqiao
,
ZHANG Haitao
. Self-organizing Production Technology for Discrete Workshop Scheduling Driven by Internet of Things[J]. Journal of Mechanical Engineering, 2018
, 54(16)
: 34
-44
.
DOI: 10.3901/JME.2018.16.034
[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.
