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Identifying Improvement Opportunities in Product Design for Reducing Energy Consumption

Author

Listed:
  • Marcin Relich

    (Faculty of Economics and Management, University of Zielona Gora, 65-417 Zielona Gora, Poland)

  • Arkadiusz Gola

    (Department of Production Computerisation and Robotisation, Faculty of Mechanical Engineering, Lublin University of Technology, 20-618 Lublin, Poland)

  • Małgorzata Jasiulewicz-Kaczmarek

    (Faculty of Management Engineering, Poznan University of Technology, 60-965 Poznan, Poland)

Abstract

The paper is concerned with predicting energy consumption in the production and product usage stages and searching for possible changes in product design to reduce energy consumption. The prediction of energy consumption uses parametric models based on regression analysis and artificial neural networks. In turn, simulations related to the identification of improvement opportunities for reducing energy consumption are performed using a constraint programming technique. The results indicate that the use of artificial neural networks improves the quality of an estimation model. Moreover, constraint programming enables the identification of all possible solutions to a constraint satisfaction problem, if there are any. These solutions support R&D specialists in identifying possibilities for reducing energy consumption through changes in product specifications. The proposed approach is dedicated to products related to high-cost energy use, which can be manufactured, for example, by companies belonging to the household appliance industry.

Suggested Citation

  • Marcin Relich & Arkadiusz Gola & Małgorzata Jasiulewicz-Kaczmarek, 2022. "Identifying Improvement Opportunities in Product Design for Reducing Energy Consumption," Energies, MDPI, vol. 15(24), pages 1-19, December.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9611-:d:1007155
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    References listed on IDEAS

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    Cited by:

    1. Cosmina-Simona Toader & Ciprian Ioan Rujescu & Andrea Feher & Cosmin Salasan & Lavinia Denisia Cuc & Karoly Bodnar, 2023. "Generation Differences in the Behaviour of Household Consumers in Romania Related to Voluntary Measures to Reduce Electric Energy Consumption," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 25(64), pages 710-710, August.
    2. Marcin Relich, 2023. "Predictive and Prescriptive Analytics in Identifying Opportunities for Improving Sustainable Manufacturing," Sustainability, MDPI, vol. 15(9), pages 1-14, May.

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