In this study, we first analyze the usability of recycling products, and use the fuzzy set method to determine the main impact on recycling items and their corresponding weights by using the Analytic Hierarchy Process (AHP) to identify various impact recycling levels. The Group Decision Supporting System (GDSS) determines the test standards for the recycling rating. It provides a convenient way for recyclers or manufacturers to classify their own products and use fuzzy numbers to select a set of test standards. It can deduce the recovery rate and remanufacturing rate of different recycling processing levels through the Markov chain model to find out the inventory model and total cost. In the numerical analysis, we found that a recycling rate of more than 90% is probably a necessary decision. Since the processing cost of the 100% recovery rate is doubled, the inventory level and total cost will increase with it. Therefore, this study was combined with the reverse logistics method to find the appropriate decision-making strategy and plan, such as the optimal inventory level and recovery rate.
This study develops an integrated supplier–remanufacturer and customer (downstream manufacturer) inventory model that takes into account three-echelon system with correlated demands and remanufacturing products allowing a backorder goods condition. This paper improves the observable fact that the first model system customer might select two sources from remanufactured products or supplier products without defective items. The second model further considers the defective items during the screening duration. The results are examined analytically and numerically to show that the policy of single shipment in large lot sizes results in less total cost than a frequent shipments policy. We also explore the impact of recovery rate on the economic benefits of the inventory system. In addition, we also perform sensitivity analysis to study the impact of seven important parameters (transportation cost, recovery rate, screening rate, annual demand, defect rate, and backorder rate, holding cost,) on the optimal solution. Management insights were also discussed.
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