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A review of energy simulation tools for the manufacturing sector

Author

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  • Garwood, Tom Lloyd
  • Hughes, Ben Richard
  • Oates, Michael R.
  • O’Connor, Dominic
  • Hughes, Ruby

Abstract

Manufacturing is a competitive global market and efforts to mitigate climate change are at the forefront of public perception. Current trends in manufacturing aim to reduce costs and increase sustainability without negatively affecting the yield of finished products, thus maintaining or improving profits. Effective use of energy within a manufacturing environment can help in this regard by lowering overhead costs. Significant benefit can be gained by utilising simulations in order to predict energy demand allowing companies to make effective retrofit decisions based on energy as well as other metrics such as resource use, throughput and overhead costs. Traditionally, Building Energy Modelling (BEM) and Manufacturing Process Simulation (MPS) have been used extensively in their respective fields but they remain separate and segregated which limits the simulation window used to identify energy improvements.

Suggested Citation

  • Garwood, Tom Lloyd & Hughes, Ben Richard & Oates, Michael R. & O’Connor, Dominic & Hughes, Ruby, 2018. "A review of energy simulation tools for the manufacturing sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 895-911.
    • Handle: RePEc:eee:rensus:v:81:y:2018:i:p1:p:895-911
    DOI: 10.1016/j.rser.2017.08.063
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    2. Marcin Relich, 2023. "Predictive and Prescriptive Analytics in Identifying Opportunities for Improving Sustainable Manufacturing," Sustainability, MDPI, vol. 15(9), pages 1-14, May.
    3. Justyna Smagowicz & Cezary Szwed & Dawid Dąbal & Pavel Scholz, 2022. "A Simulation Model of Power Demand Management by Manufacturing Enterprises under the Conditions of Energy Sector Transformation," Energies, MDPI, vol. 15(9), pages 1-27, April.
    4. Qiang Li & Mo Tong & Mian Jia & Jie Yang, 2022. "Towards Low Carbon: A Lightweight Design of Automotive Brake Hub," Sustainability, MDPI, vol. 14(22), pages 1-17, November.
    5. Bonilla-Campos, Iñigo & Nieto, Nerea & del Portillo-Valdes, Luis & Manzanedo, Jaio & Gaztañaga, Haizea, 2020. "Energy efficiency optimisation in industrial processes: Integral decision support tool," Energy, Elsevier, vol. 191(C).
    6. João M. R. C. Fernandes & Seyed Mahdi Homayouni & Dalila B. M. M. Fontes, 2022. "Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review," Sustainability, MDPI, vol. 14(10), pages 1-34, May.
    7. Ahmed, Wahhaj & Asif, Muhammad, 2021. "A critical review of energy retrofitting trends in residential buildings with particular focus on the GCC countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    8. Kočí, Jan & Kočí, Václav & Maděra, Jiří & Černý, Robert, 2019. "Effect of applied weather data sets in simulation of building energy demands: Comparison of design years with recent weather data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 22-32.
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    11. Cai, Wei & Wang, Lianguo & Li, Li & Xie, Jun & Jia, Shun & Zhang, Xugang & Jiang, Zhigang & Lai, Kee-hung, 2022. "A review on methods of energy performance improvement towards sustainable manufacturing from perspectives of energy monitoring, evaluation, optimization and benchmarking," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
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