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Therblig-embedded value stream mapping method for lean energy machining

Author

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  • Jia, Shun
  • Yuan, Qinghe
  • Lv, Jingxiang
  • Liu, Ying
  • Ren, Dawei
  • Zhang, Zhongwei

Abstract

To improve energy efficiency, extensive studies have focused on the cutting parameters optimization in the machining process. Actually, non-cutting activities (NCA) occur frequently during machining and this is a promising way to save energy through optimizing NCA without changing the cutting parameters. However, it is difficult for the existing methods to accurately determine and reduce the energy wastes (EW) in NCA. To fill this gap, a novel Therblig-embedded Value Stream Mapping (TVSM) method is proposed to improve the energy transparency and clearly show and reduce the EW in NCA. The Future-State-Map (FSM) of TVSM can be built by minimizing non-cutting activities and Therbligs. By implementing the FSM, time and energy efficiencies can be improved without decreasing the machining quality, which is consistent with the goal of lean energy machining. The method is validated by a machining case study, the results show that the total energy is reduced by 7.65%, and the time efficiency of the value-added activities is improved by 8.12%, and the energy efficiency of value-added activities and Therbligs are raised by 4.95% and 1.58%, respectively. This approach can be applied to reduce the EW of NCA, to support designers to design high energy efficiency machining processes during process planning.

Suggested Citation

  • Jia, Shun & Yuan, Qinghe & Lv, Jingxiang & Liu, Ying & Ren, Dawei & Zhang, Zhongwei, 2017. "Therblig-embedded value stream mapping method for lean energy machining," Energy, Elsevier, vol. 138(C), pages 1081-1098.
    • Handle: RePEc:eee:energy:v:138:y:2017:i:c:p:1081-1098
    DOI: 10.1016/j.energy.2017.07.120
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    References listed on IDEAS

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    Cited by:

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    5. Shun Jia & Qingwen Yuan & Wei Cai & Qinghe Yuan & Conghu Liu & Jingxiang Lv & Zhongwei Zhang, 2018. "Establishment of an Improved Material-Drilling Power Model to Support Energy Management of Drilling Processes," Energies, MDPI, vol. 11(8), pages 1-16, August.
    6. Qi Lu & Qi Zhang & Guanghui Zhou, 2023. "Low-Carbon-Driven Product Life-Cycle Process Optimization Framework for Manufacturing Equipment," Sustainability, MDPI, vol. 15(9), pages 1-19, May.
    7. Nailiang Li & Caihong Feng, 2021. "Research on Machining Workshop Batch Scheduling Incorporating the Completion Time and Non-Processing Energy Consumption Considering Product Structure," Energies, MDPI, vol. 14(19), pages 1-26, September.
    8. Jia, Shun & Cai, Wei & Liu, Conghu & Zhang, Zhongwei & Bai, Shuowei & Wang, Qiuyan & Li, Shuoshuo & Hu, Luoke, 2021. "Energy modeling and visualization analysis method of drilling processes in the manufacturing industry," Energy, Elsevier, vol. 228(C).
    9. Chen Peng & Tao Peng & Yi Zhang & Renzhong Tang & Luoke Hu, 2018. "Minimising Non-Processing Energy Consumption and Tardiness Fines in a Mixed-Flow Shop," Energies, MDPI, vol. 11(12), pages 1-15, December.
    10. Zhiqiang Yan & Jian Huang & Jingxiang Lv & Jizhuang Hui & Ying Liu & Hao Zhang & Enhuai Yin & Qingtao Liu, 2022. "A New Method of Predicting the Energy Consumption of Additive Manufacturing considering the Component Working State," Sustainability, MDPI, vol. 14(7), pages 1-23, March.
    11. Wen, Xuanhao & Cao, Huajun & Hon, Bernard & Chen, Erheng & Li, Hongcheng, 2021. "Energy value mapping: A novel lean method to integrate energy efficiency into production management," Energy, Elsevier, vol. 217(C).
    12. Shun Jia & Shang Wang & Jingxiang Lv & Wei Cai & Na Zhang & Zhongwei Zhang & Shuowei Bai, 2021. "Multi-Objective Optimization of CNC Turning Process Parameters Considering Transient-Steady State Energy Consumption," Sustainability, MDPI, vol. 13(24), pages 1-23, December.
    13. Shuai Wang & Jizhuang Hui & Bin Zhu & Ying Liu, 2022. "Adaptive Genetic Algorithm Based on Fuzzy Reasoning for the Multilevel Capacitated Lot-Sizing Problem with Energy Consumption in Synchronizer Production," Sustainability, MDPI, vol. 14(9), pages 1-24, April.
    14. Ardamanbir Singh Sidhu & Sehijpal Singh & Raman Kumar & Danil Yurievich Pimenov & Khaled Giasin, 2021. "Prioritizing Energy-Intensive Machining Operations and Gauging the Influence of Electric Parameters: An Industrial Case Study," Energies, MDPI, vol. 14(16), pages 1-39, August.
    15. Chiuhsiang Joe Lin & Rio Prasetyo Lukodono, 2021. "Sustainable Human–Robot Collaboration Based on Human Intention Classification," Sustainability, MDPI, vol. 13(11), pages 1-26, May.
    16. Keyan He & Huajie Hong & Renzhong Tang & Junyu Wei, 2020. "Analysis of Multi-Objective Optimization of Machining Allowance Distribution and Parameters for Energy Saving Strategy," Sustainability, MDPI, vol. 12(2), pages 1-32, January.

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    More about this item

    Keywords

    Energy efficiency; Lean energy machining; Value-added; Non-valued added; Therblig-embedded value stream mapping;
    All these keywords.

    JEL classification:

    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other

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