Skip to main content

Advertisement

Log in

Research on ECBOM modeling and energy consumption evaluation based on BOM multi-view transformation

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

Combining information technology and green manufacturing theory, the concept of energy consumption bill of materials (ECBOM) are first proposed, which is similar to Manufacturing BOM (MBOM), Plan BOM (PBOM) or other extended BOM for different business scenarios. ECBOM will become an effective informatization aid for green manufacturing in product life cycle including green design, green process, green production, green management, green supply chain, green recycling, green maintenance and green technology. Firstly, this paper defines ECBOM and analyzes the evolution process of its data items, then proposes a BOM multi-view transformation method to convert them into ECBOM. In addition, UML conceptual model of ECBOM and its traversal algorithm are designed to efficiently search data for energy consumption evaluation. Finally, a case study of driving belt mechanism in machine tool is taken as to test the method proposed in this paper and indicates that ECBOM could have a positive impaction green manufacturing.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Afkhami B, Akbarian B, Narges BA, Kakaee AH, Shabani B (2015) Energy consumption assessment in a cement production plant. Sustain Energy Technol Assess 10:84–89

    Google Scholar 

  • Auer M, Meyer L, Biffl S (2007) Explorative UML modeling—comparing the usability of UML tools. ICEIS 2007. In: Proceedings of the ninth international conference on enterprise information systems, pp 466–473

  • Azmoodeh A, Dehghantanha A, Conti M, Choo KKR (2017) Detecting crypto-ransomware in IoT networks based on energy consumption footprint. J Ambient Intell Humaniz Comput 4:1–12

    Google Scholar 

  • Bonvoisin J, Thiede S, Brissaud D, Herrmann C (2013) An implemented framework to estimate manufacturing-related energy consumption in product design. Int J Comput Integr Manuf 26(9):866–880

    Article  Google Scholar 

  • Engel TA, Charão AS, Kirsch-Pinheiro M, Steffenel LA (2015) Performance improvement of data mining in Weka through multi-core and GPU acceleration: opportunities and pitfalls. J Ambient Intell Humaniz Comput 6(4):377–390

    Article  Google Scholar 

  • Fong S, Li J, Song W, Tian Y, Wong RK, Dey N (2018) Predicting unusual energy consumption events from smart home sensor network by data stream mining with misclassified recall. J Ambient Intell Humaniz Comput 2:1–25

    Google Scholar 

  • Guoli J, Daxin G, Tsui F (2003) Analysis and implementation of the bom of a tree-type structure in mrpii. J Mater Process Tech 139(1):535–538

    Article  Google Scholar 

  • Huang H, Ameta G (2010) Towards a computational framework for energy estimation: needs, requirements, and its generic shell. In: American Society of Mechanical Engineering- International Design Engineering Technical Conference-2010/Computers and Information in engineering, pp. 891–897

  • Huang H, Ameta G (2014) A Novel Pattern for Energy Estimation Framework and Tools to Compute Energy Consumption in Product Life Cycle. J Comput Inf Sci Eng 14(1):011002

    Article  Google Scholar 

  • Ibbotson SM, Kara S (2018) A framework for determining the life time energy consumption of a product at the concept design stage. ProcediaCirp 69:704–709

    Google Scholar 

  • Kashkoush M, Elmaraghy H (2016) Product family formation by matching bill-of-materials trees. Cirp J Manuf Sci Technol 12:1–13

    Article  Google Scholar 

  • Kiani SL, Anjum A, Antonopoulos N, Knappmeyer M (2014) Context-aware service utilisation in the clouds and energy conservation. J Ambient Intell Humaniz Comput 5(1):111–131

    Article  Google Scholar 

  • Kim J, Yun C, Park Y, Park CH (2015) Post-consumer energy consumption of textile products during ‘use’ phase of the lifecycle. Fibers Polymers 16(4):926–933

    Article  Google Scholar 

  • Kruse A, Uhlemann HJ, Steinhilper R (2016) Simulation-based assessment and optimization of the energy consumption in multi variant production. ProcediaCirp 40:396–401

    Google Scholar 

  • Li DD, Zhang YJ (2017) Feature-based approach in product design with energy efficiency consideration. Environ Earth Sci 86(1):012022

    Google Scholar 

  • Li T, Zhuang J, Zhang HC, Liu ZC (2013) Energy consumption assessment of remanufacturing processes. In: Re-engineering manufacturing for sustainability, pp. 649–653

  • Liu M, Lai J, Shen W (2014) A method for transformation of engineering bill of materials to maintenance bill of materials. Robot Comput Integr Manuf 30(2):142–149

    Article  Google Scholar 

  • Ober I (2000) More meaningful UML models. In: International conference on technology of object-oriented languages and systems. Tools-Pacific 2000, pp. 146–157

  • Papandrea M, Giordano S (2014) Location prediction and mobility modelling for enhanced localization solution. J Ambient Intell Humaniz Comput 5(3):279–295

    Article  Google Scholar 

  • Peng Z, Liao J, Cai Y (2015) Differential evolution with distributed direction information based mutation operators: an optimization technique for big data. J Ambient Intell Humaniz Comput 6(4):481–494

    Article  Google Scholar 

  • Righi S, Baioli F, Pozzo AD, Tugnoli A (2018) Integrating life cycle inventory and process design techniques for the early estimate of energy and material consumption data. Energies 11(4):970

    Article  Google Scholar 

  • Shih HM (2011) Product structure (BOM)-based product similarity measures using orthogonal procrustes approach. Comput Ind Eng 61(3):608–628

    Article  Google Scholar 

  • Takata S, Yamanaka M (2013) Bom based supply chain risk management. CIRP Ann Manuf Technol 62(1):479–482

    Article  Google Scholar 

  • Tao F, Zhao D, Hu Y, Zhou Z (2009) Resource service composition and its optimal-selection based on particle swarm optimization in manufacturing grid system. IEEE Trans Ind Inf 4(4):315–327

    Article  Google Scholar 

  • Tao F, Hu Y, Zhou Z (2010) Correlation-aware resource service composition and optimal-selection in manufacturing grid. Eur J Oper Res 201(1):129–143

    Article  MATH  Google Scholar 

  • Tao F, Zuo Y, Xu LD, Lv L, Zhang L (2014) Internet of things and bom-based life cycle assessment of energy-saving and emission-reduction of products. IEEE Trans Ind Inf 10(2):1252–1261

    Article  Google Scholar 

  • Tao F, Cheng J, Qi Q, Zhang M, Zhang H, Sui F (2018) Digital twin-driven product design, manufacturing and service with big data. Int J Adv Manuf Technol 94(9–12):3563–3576

    Article  Google Scholar 

  • Wu MC, Hsu YK (2008) Design of bom configuration for reducing spare parts logistic costs. Expert Syst Appl 34(4):2417–2423

    Article  Google Scholar 

  • Xia NC, Hu J, Wang WM, Peng YH, Zhan ZF, Qi J (2008) Managing and mapping method for bom multiple-view based on transform-table. J Shanghai Jiaotong Univ 42(4):584–589

    Google Scholar 

  • Xiang F, Hu Y, Yu Y, Wu H (2014) QoS and energy consumption aware service composition and optimal-selection based on Pareto group leader algorithm in cloud manufacturing system. CEJOR 22(4):663–685

    Article  MATH  Google Scholar 

  • Xiang F, Xu LL, Jiang GZ (2016) Green manufacturing service composition in cloud manufacturing system: An introduction, Industrial Electronics and Applications, pp. 1988–1993

  • Xiang F, Yin Q, Wang Z, Jiang GZ (2018) Systematic method for big manufacturing data integration and sharing. Int J Adv Manuf Technol 94(9–12):3345–3358

    Article  Google Scholar 

  • Xiong M, Shu BT, Li PK, Chen CH (2003) A web-enhanced dynamic bom-based available-to-promise system. Int J Prod Econ 84(2):133–147

    Article  Google Scholar 

  • Yala N, Fergani B, Fleury A (2017) Towards improving feature extraction and classification for activity recognition on streaming data. J Ambient Intell Humaniz Comput 8(2):177–189

    Article  Google Scholar 

  • Zhou C, Liu X, Xue F, Bo H, Li K (2018) Research on static service bom transformation for complex products. Adv Eng Inform 36:146–162

    Article  Google Scholar 

  • Zuo Y, Tao F, Nee AYC (2018) An internet of things and cloud-based approach for energy consumption evaluation and analysis for a product. Int J Comput Integr Manuf 31(4–5):337–348

    Article  Google Scholar 

Download references

Acknowledgements

This work is sponsored by National Natural Science Foundation of China (No. 51505350), Key Laboratory of Metallurgical Equipment and Control Technology (Wuhan University of Science and Technology), Ministry of Education (no. 2015B02), and Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering (Wuhan University of Science and Technology) (no. 2017A07). Sincere appreciation is extended to the reviewers of this paper for their helpful comments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ying Zuo.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xiang, F., Huang, Y., Zhang, Z. et al. Research on ECBOM modeling and energy consumption evaluation based on BOM multi-view transformation. J Ambient Intell Human Comput 10, 953–967 (2019). https://doi.org/10.1007/s12652-018-1053-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-018-1053-3

Keywords

Navigation