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Energy consumption optimization for sustainable flexible robotic cells: Proposing exact and metaheuristic methods

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  • Mazyar Ghadiri Nejad
  • Reza Vatankhah Barenji
  • Güldal Güleryüz
  • Seyed Mahdi Shavarani

Abstract

Many manufacturing companies are always looking for a way to reduce energy consumption by utilizing energy-efficient production methods. These methods can be different depending on the type of products and production technology. For instance, one of the ways to increase energy efficiency and keep the precision of production is to use robots for the transportation of the parts among the machines and loading/unloading the machines. This technology is affordable compared to the technologies used in manufacturing companies. Manufacturing companies that rely on robotics technology must have a strategy to reduce energy costs and at the same time increase production by adjusting the intensity of processing or controlling the production rate. This study presents an exact solution method for flexible robotic cells to control the production rate and minimize energy consumption, which aims to both reduce electricity prices and minimize greenhouse gas (GHG) emissions under a lead time of production. Then, considering the NP-hardens nature of the problem, a heuristic solution method based on the genetic algorithm (GA) is proposed. Using the proposed approach, manufacturing companies will be able to make more accurate decisions about processing intensity and process scheduling while ensuring sustainability.

Suggested Citation

  • Mazyar Ghadiri Nejad & Reza Vatankhah Barenji & Güldal Güleryüz & Seyed Mahdi Shavarani, 2025. "Energy consumption optimization for sustainable flexible robotic cells: Proposing exact and metaheuristic methods," Energy & Environment, , vol. 36(3), pages 1271-1289, May.
  • Handle: RePEc:sae:engenv:v:36:y:2025:i:3:p:1271-1289
    DOI: 10.1177/0958305X231193868
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    1. Garwood, Tom Lloyd & Hughes, Ben Richard & O'Connor, Dominic & Calautit, John K. & Oates, Michael R. & Hodgson, Thomas, 2018. "A framework for producing gbXML building geometry from Point Clouds for accurate and efficient Building Energy Modelling," Applied Energy, Elsevier, vol. 224(C), pages 527-537.
    2. Mao Tan & Bin Duan & Yongxin Su, 2018. "Economic batch sizing and scheduling on parallel machines under time-of-use electricity pricing," Operational Research, Springer, vol. 18(1), pages 105-122, April.
    3. Shijin Wang & Zhanguo Zhu & Kan Fang & Feng Chu & Chengbin Chu, 2018. "Scheduling on a two-machine permutation flow shop under time-of-use electricity tariffs," International Journal of Production Research, Taylor & Francis Journals, vol. 56(9), pages 3173-3187, May.
    4. Rubio, Francisco & Llopis-Albert, Carlos & Valero, Francisco, 2021. "Multi-objective optimization of costs and energy efficiency associated with autonomous industrial processes for sustainable growth," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    5. Mao Tan & Hua-li Yang & Bin Duan & Yong-xin Su & Feng He, 2017. "Optimizing Production Scheduling of Steel Plate Hot Rolling for Economic Load Dispatch under Time-of-Use Electricity Pricing," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-13, March.
    6. Zhao, Xiancong & Bai, Hao & Shi, Qi & Lu, Xin & Zhang, Zhihui, 2017. "Optimal scheduling of a byproduct gas system in a steel plant considering time-of-use electricity pricing," Applied Energy, Elsevier, vol. 195(C), pages 100-113.
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