Enhancing remanufacturing operations: A review on Decision-Making models and their implementation challenges

Abstract

This paper reviews operational decision-making models and tools in the field of remanufacturing. Past research on this subject highlighted a predominance of strategic and tactical decision tools. However, operational decision-making represents an open issue for the remanufacturing process. For this reason, this review employs a systematic methodology to update existing literature surveys, evaluate the recent advancements made on the subject, and identify the main barriers that limit the application of existing models in real industrial remanufacturing contexts. The results highlight significant advancements in decision-support tools, particularly in the inspection and disassembly phases, where modern technologies, such as machine learning and robotics, can enhance decision-making processes. Despite these advancements, several barriers to the industrial implementation of existing models persist, mainly related to the availability of data for their application. This often leads to other sub-problems, such as the omission of uncertainties typical of the remanufacturing process. The paper concludes by analysing potential future research trends in this area, emphasising the necessity of systems that gather and utilise data for decision-making across all remanufacturing phases. A preliminary proposal for such a system is presented.