New paradigm of green manufacturing for product life cycle based on digital twin

被引：0
作者：
Xiang F. [1 ]
Huang Y. [1 ]
Zhang Z. [1 ]
Jiang G. [1 ]
Zuo Y. [2 ]
Tao F. [2 ]
机构：
[1] School of Machinery and Automation, Wuhan University of Science and Technology, Wuhan
[2] School of Automation Science and Electrical Engineering, Beihang University, Beijing
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2019年 / 25卷 / 06期
关键词：
Digital twin; Five-dimensional digital twin model; Green manufacturing; Manufacturing industry; Product life cycle;
D O I：
10.13196/j.cims.2019.06.018
中图分类号：
学科分类号：
摘要：
With the increasing enhancement of people's consciousness of sustainable development, the traditional manufacturing industry is deeply remolding and transforming into green, intelligent and service-oriented. Manufacturing enterprises had successively applied various advanced information technology (cloud computing, CPS, IoT, simulation modeling) to solve various problems in sustainable manufacturing. With the integration of physical world and virtual world centered on green features, a new paradigm of digital twin driven green manufacturing was proposed, and a five-dimensional digital twin model with green features was established to reconstruct the relationship between physical entities, virtual twins, data, interactive interfaces, services and the green characteristics of elements in green manufacturing process. Then, the application of green material selection, green disassembly, green recycling, green remanufacturing and reverse supply chain under the five-dimensional digital twin model were analyzed. The energy consumption management platform of product life cycle based on energy consumption feature extraction was validated. © 2019, Editorial Department of CIMS. All right reserved.
引用
收藏
页码：1505 / 1514
页数：9
相关论文
共 37 条
  • [1] Tao F., Zhang L., Hu Y., Resource Service Management in Manufacturing Grid System, (2011)
  • [2] Tao F., Zhang L., Laili Y., Configurable Intelligent Optimization Algorithm: Design and Practice in Manufacturing, (2014)
  • [3] Xiang F., Huang Y., Zuo Y., Et al., SLA oriented energy efficiency evaluation of manufacturing service, China Mechanical Engineering, 29, 20, pp. 2401-2407, (2018)
  • [4] Liu F., Cao H., He N., Research status and development trend of green manufacturing, China Mechanical Engineering, 11, pp. 114-119, (2000)
  • [5] Song S., Liu M., Ke Q., Et al., Components optimization design for remanufacturing based on residual strength, Journal of Mechanical Engineering, 49, 9, pp. 121-127, (2013)
  • [6] Xin L., Jia X., Li F., Et al., Green feature modeling for mechanical and electrical product conceptual design, Computer Integrated Manufacturing Systems, 18, 4, pp. 713-718, (2012)
  • [7] Deif A.M., A system model for green manufacturing, Journal of Cleaner Production, 19, 14, pp. 1553-1559, (2011)
  • [8] Jiang Z., Zhang H., Yan W., Et al., An evaluation model of machining process for green manufacturing, Advanced Science Letters, 4, 4-5, pp. 1724-1728, (2011)
  • [9] Jiang Z., Zhang H., Sutherland J.W., Development of multi-criteria decision making model for remanufacturing technology portfolio selection, Journal of Cleaner Production, 19, 17-18, pp. 1939-1945, (2011)
  • [10] Li C., Zhu Y., Li L., Et al., Multi-objective CNC milling parameters optimization model for energy efficiency, Journal of Mechanical Engineering, 52, 21, pp. 120-129, (2016)
1234