Leveraging Computer Vision for Sustainable Manufacturing: Potentials, Challenges and Future Perspectives

Abstract

Sustainable and circular manufacturing practices have become imperative for modern industries due to the escalating environmental challenges, stricter regulatory policies, and shifting consumer preferences towards more sustainable products. Among the multitude of technological advancements that enable this transition, Computer Vision (CV) is rapidly emerging as a game-changer. However, a comprehensive investigation is required to understand the role and impact of CV in the context of data-driven and servitized manufacturing. This review paper provides a thorough analysis of the relationship between CV and sustainable manufacturing. It highlights the various ways that CV improves sustainability by leveraging a rich corpus of academic studies as well as industry case studies. This covers the function of CV in enhancing resource efficiency, decreasing waste, enabling predictive maintenance, and assuring product quality. Nevertheless, there are several challenges in integrating CV technologies into manufacturing. Therefore, this paper offers a detailed analysis of these issues, ranging from technical complexities to data privacy and skills gap. Consequently, this study proposes potential solutions and strategies, turning these challenges into avenues for future research and innovation. Through this paper, our endeavor is not only to enrich the academic discourse around this topic but also to catalyze future research and provide actionable insights for practitioners at the intersection of technology and sustainability in manufacturing.

Keywords: Sustainable Manufacturing, Circular Manufacturing, Computer Vision, Artificial Intelligence, Industrial AI

DOI: 10.54941/ahfe1004321