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A Data-Driven Approach for Improving Sustainable Product Development

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  • Marcin Relich

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

Abstract

A product’s impact on environmental issues in its complete life cycle is significantly determined by decisions taken during product development. Thus, it is of vital importance to integrate a sustainability perspective in methods and tools for product development. The paper aims at the development of a method based on a data-driven approach, which is dedicated to identifying opportunities for improving product sustainability at the design stage. The proposed method consists of two main parts: predictive analytics and simulations. Predictive analytics use parametric models to identify relationships within product sustainability. In turn, simulations are performed using a constraint programming technique, which enables the identification of all possible solutions (if there are any) to a constraint satisfaction problem. These solutions support R&D specialists in finding improvement opportunities for eco-design related to reducing harmful impacts on the environment in the manufacturing, product use, and post-use stages. The results indicate that constraint-satisfaction modeling is a pertinent framework for searching for admissible changes at the design stage to improve sustainable product development within the full scope of socio-ecological sustainability. The applicability of the proposed approach is verified through an illustrative example which refers to reducing the number of defective products and quantity of energy consumption.

Suggested Citation

  • Marcin Relich, 2023. "A Data-Driven Approach for Improving Sustainable Product Development," Sustainability, MDPI, vol. 15(8), pages 1-18, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6736-:d:1125185
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    References listed on IDEAS

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    Cited by:

    1. Kurniawati, 2023. "Sustainable Textile Practices by Integrated Viscose Rayon and Yarn Producers: An Empirical Study," GATR Journals jfbr210, Global Academy of Training and Research (GATR) Enterprise.

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