The effect of orbit information on the optimality of remanufacturing decision

The remanufacturing process is becoming increasingly critical to the sustainability of closed-loop supply chain systems. The fact that products are now used not only by ownership but also by servicizing has led to the widespread use of product recycling. However, this development has brought about significant challenges for companies in optimizing their remanufacturing processes. In particular, issues such as the number and return rate of used products are among the main difficulties faced by companies. In this study, we aim to show that the number of products in use, which is a long-existing gap in the literature, is an important parameter in the decision optimization of systems subject to remanufacturing. First, we compared a decision policy in the literature that does not take into account the number of products in use with our Markov Decision Process model, which we run with a value iteration algorithm and takes into account the number of products in use. In our subsequent study, we examined a system where certain returns to the inventory exists for used products. In the first study, it was determined that the model we created gave optimal results, while the decision policy taken from the literature gave suboptimal results. In addition, we observed that in the system that works with a decision policy that does not take into account the number of products in use, the cost increases as the average number of products in use increases, but this information cannot be accessed by the relevant policy since it does not consider the number of products in use. In our second study, we observed that the system stopped producing after reaching a certain product level, turning the manufacturing cost into a transient cost. In conclusion, as a result of these studies, we can reveal that the number of products in use is a parameter that should be taken into account when creating a decision policy.