Optimal Acquisition and Production Policies for Remanufacturing with Quality Grading

Author:

Sun Hong1ORCID,Li Yan1

Affiliation:

1. Business School, Shandong University, Weihai 264209, China

Abstract

Core acquisition is essential to the success of the remanufacturing business. The value of sorting and grading cores into nominal-quality classes has been certified in industry and academia. In this paper, we investigate how many unsorted cores of uncertain quality should be acquired and how many sorted cores should be remanufactured by a third-party remanufacturer (3PR) before the demand is realized. We first develop analytically tractable solutions to the acquisition and production model under deterministic demand, and then we extend it to the model under the stochastic demand by fully characterizing the structure of the optimal policy. Subsequently, we investigate the impact of core quality fraction uncertainty on the solutions. Finally, numerical analyses are conducted to further verify the proposed models. The results are as follows. First, the optimal quantity of acquisition/production and minimum expected profit increase with an increase in the selling price and decrease with an increase in the uncertainty of demand and acquisition cost. Second, the optimal production quantity does not decrease in acquisition quantity, and the rate of utilization of the recycled parts (the ratio of production quantity to acquisition quantity) increases with a decrease in the acquisition cost. Third, the growth stage is most profitable stage, so the remanufacturers should pay more attention to remanufacturing activities early in the life of products. The proposed models and solutions can not only solve the core acquisition and production problem in remanufacturing, but also solve the combinatorial optimization problem.

Funder

National Natural Science Foundation of China

Shandong Provincial Natural Science Foundation, China

Humanities and Social Sciences Foundation of the Ministry of Education of China

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

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