Optimal acquisition and remanufacturing policies considering the effect of quality uncertainty on carbon emissions

With the intensification of global warming, various policies are being proposed globally to reduce the emission of greenhouse gases, thereby causing the cost of carbon emissions to be an important factor in deciding the acquisition and remanufacturing policies. In a remanufacturing system, the highly variable quality of the end-of-life products not only results in uncertain remanufacturing costs, but also leads to different carbon emissions during remanufacturing. Therefore, in this study, a model considering the effect of quality uncertainty on carbon emissions is proposed to determine the optimal acquisition and remanufacturing policies of the independent remanufacturing system. To better depict the effect of quality uncertainty on carbon emissions and apply this property to the decision-making processes, the remanufacturing time is defined to describe the quality of acquired cores. Since the optimal sorting policy is independent of the remanufacturing quantity, the problem-solving process is divided into two sub-problems, namely, the sorting problem and remanufacturing problem. In the sorting problem, the optimal threshold of remanufacturing processing time is derived using a dichotomy method. In the remanufacturing method, the optimal acquisition quantity and remanufacturing quantity are obtained with the sorting policy derived above. In order to explore the difference with previous studies in which the effect of quality uncertainty on carbon emissions is ignored, numerical experiments between varied emissions case and fixed emissions case are employed to analyze and validate the effectiveness of proposed method. The results indicate that considering the effect of quality uncertainty on carbon emissions can effectively increases profit and reduces total carbon emissions for corporations. Moreover, the model considering the effect of quality uncertainty on carbon emissions exhibits a better adaptability to the variations in the external conditions.