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

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.

[1]  Li Pheng Khoo,et al.  A web-enhanced dynamic BOM-based available-to-promise system , 2003 .

[2]  Ileana Ober.  More meaningful UML models , 2000, Proceedings 37th International Conference on Technology of Object-Oriented Languages and Systems. TOOLS-Pacific 2000.

[3]  Kai Li,et al.  Research on static service BOM transformation for complex products , 2018, Adv. Eng. Informatics.

[4]  Tao Li,et al.  Energy Consumption Assessment of Remanufacturing Processes , 2013 .

[5]  Nawel Yala,et al.  Towards improving feature extraction and classification for activity recognition on streaming data , 2017, J. Ambient Intell. Humaniz. Comput..

[6]  Fei Tao,et al.  Correlation-aware resource service composition and optimal-selection in manufacturing grid , 2010, Eur. J. Oper. Res..

[7]  Han M. Shih.  Product structure (BOM)-based product similarity measures using orthogonal procrustes approach , 2011, Comput. Ind. Eng..

[8]  Nick Antonopoulos,et al.  Context-aware service utilisation in the clouds and energy conservation , 2012, Journal of Ambient Intelligence and Humanized Computing.

[9]  Ali Dehghantanha,et al.  Detecting crypto-ransomware in IoT networks based on energy consumption footprint , 2018, J. Ambient Intell. Humaniz. Comput..

[10]  Rolf Steinhilper,et al.  Simulation-based Assessment and Optimization of the Energy Consumption in Multi Variant Production , 2016 .

[11]  Qi Jin.  Managing and Mapping Method for BOM Multiple-View Based on Transform-Table , 2008 .

[12]  Yiqiao Cai,et al.  Differential evolution with distributed direction information based mutation operators: an optimization technique for big data , 2015, Journal of Ambient Intelligence and Humanized Computing.

[13]  D D Li,et al.  Feature-based Approach in Product Design with Energy Efficiency Consideration , 2017 .

[14]  Christoph Herrmann,et al.  An implemented framework to estimate manufacturing-related energy consumption in product design , 2013, Int. J. Comput. Integr. Manuf..

[15]  Silvia Giordano,et al.  Location prediction and mobility modelling for enhanced localization solution , 2014, J. Ambient Intell. Humaniz. Comput..

[16]  Ji Guoli,et al.  Analysis and implementation of the BOM of a tree-type structure in MRPII , 2003 .

[17]  Changsang Yun,et al.  Post-consumer energy consumption of textile products during ‘use’ phase of the lifecycle , 2015, Fibers and Polymers.

[18]  Shozo Takata,et al.  BOM based supply chain risk management , 2013 .

[19]  Bahman Shabani,et al.  Energy consumption assessment in a cement production plant , 2015 .

[20]  H. ElMaraghy,et al.  Product family formation by matching Bill-of-Materials trees , 2016 .

[21]  Nilanjan Dey,et al.  Predicting unusual energy consumption events from smart home sensor network by data stream mining with misclassified recall , 2018, J. Ambient Intell. Humaniz. Comput..

[22]  Stefan Biffl,et al.  Explorative UML Modeling - Comparing the Usability of UML Tools , 2007, ICEIS.

[23]  Feng Xiang,et al.  Systematic method for big manufacturing data integration and sharing , 2018 .

[24]  Fei Tao,et al.  Internet of Things and BOM-Based Life Cycle Assessment of Energy-Saving and Emission-Reduction of Products , 2014, IEEE Transactions on Industrial Informatics.

[25]  Andrew Y. C. Nee,et al.  An Internet of things and cloud-based approach for energy consumption evaluation and analysis for a product , 2017, Int. J. Comput. Integr. Manuf..

[26]  Muh-Cherng Wu,et al.  Design of BOM configuration for reducing spare parts logistic costs , 2008, Expert Syst. Appl..

[27]  Yefa Hu,et al.  QoS and energy consumption aware service composition and optimal-selection based on Pareto group leader algorithm in cloud manufacturing system , 2014, Central Eur. J. Oper. Res..

[28]  He Huang,et al.  Towards a Computational Framework for Energy Estimation: Needs, Requirements, and Its Generic Shell , 2010 .

[29]  Gaurav Ameta,et al.  A Novel Pattern for Energy Estimation Framework and Tools to Compute Energy Consumption in Product Life Cycle , 2014, J. Comput. Inf. Sci. Eng..

[30]  Weiming Shen,et al.  A method for transformation of engineering bill of materials to maintenance bill of materials , 2014 .

[31]  Alessandro Tugnoli,et al.  Integrating Life Cycle Inventory and Process Design Techniques for the Early Estimate of Energy and Material Consumption Data , 2018 .

[32]  Feng Xiang,et al.  Green manufacturing service composition in cloud manufacturing system: An introduction , 2016, 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA).

[33]  Fei Tao,et al.  Digital twin-driven product design, manufacturing and service with big data , 2017, The International Journal of Advanced Manufacturing Technology.

[34]  Fei Tao,et al.  Resource Service Composition and Its Optimal-Selection Based on Particle Swarm Optimization in Manufacturing Grid System , 2008, IEEE Transactions on Industrial Informatics.

[35]  Manuele Kirsch-Pinheiro,et al.  Performance improvement of data mining in Weka through multi-core and GPU acceleration: opportunities and pitfalls , 2015, J. Ambient Intell. Humaniz. Comput..

[36]  Sami Kara,et al.  A Framework for Determining the Life Time Energy Consumption of a Product at the Concept Design Stage , 2018 .