• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.2
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• pp.43-63
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• 2013

Remanufacturing is a process of recovering end-of-life products into serviceable parts for producing new products. Due to the limited supply of recovery cores to remanufacture, a remanufacturing firm also needs to produce or procure new parts for fulfilling the demand. This paper is targeted for solving the problem of determining the optimal amount of newly produced and remanufacturing parts, which is called production and remanufacturing planning (PRP) problem, under uncertain supply of recovery cores. The new production mitigates the risk of insufficient core supply while it takes more costs than the remanufacturing. The PRP model in this paper also considers disassemble-to-order (DTO) environment, in which multiple kinds of parts are remanufactured from multiple products on order of the parts. Whereas existing studies presents only heuristic solutions for DTO remanufacturing, this paper provides an exact solution for this problem and analytical sensitivity of the involved cost parameters, adopting multi-dimensional newsvendor modeling and stochastic linear programming techniques. The result shows that production and remanufacturing plans for multiple products are mutually dependent, and a change of cost parameters involved in only one part is propagated to all other parts.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.3
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• pp.71-84
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• 2009

This paper considers a remanufacturing and purchasing planning problem, in which either used products(or wastes) are remanufactured or remanufactured products(or final products) are purchased to satisfy dynamic demands of remanufactured products over a discrete and finite time horizon. Also, as remanufactured products are purchased more than or equal to a special quantity Q, a discount price policy is applied. The problem assumes that the related cost(remanufacturing and inventory holding costs of used products, and the purchasing and inventory holding costs of remanufactured products) functions are concave and backlogging is not allowed. The objective of this paper is to determine the optimal remanufacturing and purchasing policy that minimizes the total cost to satisfy dynamic demands of remanufactured products. This paper characterizes the properties of the optimal policy and then, based on these properties, presents a dynamic programming algorithm to find the optimal policy. Also, a network-based procedure is proposed for the case of a large quantity of low cost used products. A numerical example is then presented to demonstrate the procedure of the proposed algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.4
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• pp.111-122
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• 2000

This paper considers remanufacturing planning problems under deterministic environments. As increasing the environmental pressures in manufacturing, various methods for reducing wasted or postponing the time to be waste are considered. This paper considers remanufacturing planning problems on a single facility, where the wastes(or used products) are remanufactured to satisfy the given demand on the remanufactured products. The objective is to find the optimal remanufacturing and purchasing planning of the wastes which minimize total cost subject to satisfaction all the given demand on the remanufactured products. Two problems that the amount of wastes is a given constant or a decision variable are considered, respectively. For the problems, the extreme point solutions are characterized, and dynamic programming algorithms are developed with numerical examples.

• Industrial Engineering and Management Systems
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• v.13 no.2
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• pp.231-249
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• 2014

This paper discusses a green supply chain with a manufacturer and a collection trader, and it proposes an optimal production planning for remanufacturing of parts in used products with quality classification errors made by the collection trader. When a manufacturer accepts an order for parts from a retailer and procures used products from a collection trader, the collection trader might have some quality classification errors due to the lack of equipment or expert knowledge regarding quality classification. After procurement of used products, the manufacturer inspects if there are any classification errors. If errors are detected, the manufacturer reclassifies the misclassified (overestimated) used products at a cost. Accordingly, the manufacturer decides to remanufacture from the higher-quality used products based on a remanufacturing ratio or produce parts from new materials. This paper develops a mathematical model to find how quality classification errors affect the optimal decisions for a lower limit of procurement quality of used products and a remanufacturing ratio under the lower limit and the expected profit of the manufacturer. Numerical analysis investigates how quality of used products, the reclassification cost and the remanufacturing cost of used products affect the optimal production planning and the expected profit of a manufacturer.

• Industrial Engineering and Management Systems
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• v.14 no.2
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• pp.159-174
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• 2015

Remanufacturing used, end-of-life products is a complex problem involving multiple types of products that may share common parts. Recovery targets assigned by market demand and environmental legislation add more difficulty to the problem. Manufacturers now need to achieve specified take-back and recovery rates while fulfilling demands for remanufactured products. To assists in the demand- and legislation-driven remanufacturing of a family of products (i.e., multiple products that share common parts), this paper introduces a bi-objective mixed integer linear programming (MILP) model for optimizing remanufacturing. The model identifies optimal remanufacturing plans for a product family, whereby, the remanufacturer can achieve demand and recovery targets more profitably and in an environmentally-friendly manner. The model can also be used to quantify and justify the economic and environmental benefits of a product family from a remanufacturing perspective. A case study is presented for remanufacturing an alternatorfamily of products.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.3
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• pp.240-247
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• 2005

Today's hightech society requires thousands of different products which ultimately result in billions of tons of materials discarded, most of which end up in landfills. Therefore industrial circles could not help thinking about environmental problems by regulations of government or pressures of consumer. Generally, the related research subjects are classified into both of environmentally conscious manufacturing and product recovery, where product recovery aims to minimize the amount of waste sent to landfills by recovering materials and parts from old or outdated products by means of recycling and remanufacturing (including reuse of parts and products). In this research, we constructed a model for remanufacturing various goods using a single facility and developed a dynamic programing(DP) algorithm based upon the optimal solution characterization. We showed the efficiency of the developed DP algorithm with a numerical example.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.699-706
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• 2005

증가하는 소비의 추세, 한정된 자원, 폐기물 처분등의 문제로 인하여, remanufacturing 에 대한 관심이 더욱 높아져가고 있다. Remanufacturing 에 대한 생산계획 및 스케줄링은 높은 불확실성으로 인하여 기존의 방법들과 별개로 다루어져야 한다. 본 연구에서는 manufacturing/remanufacturing 생산 시스템에서의 생산계획을 위한 수정된 유전 알고리즘(GA)을 제안하였다. GA 의 chromosome 은 각 부품의 생산 수준을 의미하며, 알고리즘을 이용하여 중간조립품과 최종제품의 분해/조립 계획을 결정할 수 있다. 임의로 생성된 문제들에 대해 실험한 결과, 다양한 문제들에 대하여 적용 가능하다는 것을 알 수 있었다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.77-86
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• 2012

We consider the capacitated lot-sizing and scheduling problem for a paper remanufacturing system that produces several types of corrugated cardboards. The problem is to determine the lot sizes as well as the sequence of lots for the objective of minimizing the sum of setup and inventory holding costs while satisfying the demand and the machine capacity over a given planning horizon. In particular, the paper remanufacturing system has sequence-dependent setup costs that depend on the type of product just completed and on the product to be processed. Also, the setup state at one period can be carried over to the next period. An integer programming model is presented to describe the problem. Due to the complexity of the problem, we modify the existing two-stage heuristics in which an initial solution is obtained and then it is improved using a multi-pass interchange method. To show the performances of the heuristics, computational experiments were done using the real data, and a significant amount of improvement is reported.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.192-202
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• 2009

Disassembly of products at their end-of-life (EOL) is a prerequisite for recycling or remanufacturing, since most products should be disassembled before being recycled or remanufactured as secondary parts or materials. In disassembly sequence planning of EOL products, considered are the uncertainty issues, i.e., defective parts or joints in an incoming product, disassembly damage, and imprecise net profits and costs. The paper deals with the problem of determining the disassembly level and corresponding sequence, with the objective of maximizing the overall profit under uncertainties in disassembly cost and/or revenue. The solution is represented as the longest path on a directed acyclic graph where parameter (arc length) uncertainties are modeled in the form of intervals. And, a heuristic algorithm is developed to find a path with the minimum worst case regret, since the problem is NP-hard. Computational experiments are carried out to show the performance of the proposed algorithm compared with the mixed integer programming model and Conde's heuristic algorithm.

• Industrial Engineering and Management Systems
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• v.8 no.1
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• pp.14-21
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• 2009

We formulate a mathematical model of remanufacturing system as multi-stage reverse Logistics Network Problem (mrLNP) with minimizing the total costs for reverse logistics shipping cost and inventory holding cost at disassembly centers and processing centers over finite planning horizons. For solving this problem, in the 1st and the 2nd stages, we propose a Genetic Algorithm (GA) with priority-based encoding method combined with a new crossover operator called as Weight Mapping Crossover (WMX). A heuristic approach is applied in the 3rd stage where parts are transported from some processing centers to one manufacturer. Computer simulations show the effectiveness and efficiency of our approach. In numerical experiments, the results of the proposed method are better than pnGA (Prufer number-based GA).