• Journal of Korean Society of Environmental Engineers
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• v.32 no.10
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• pp.957-964
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• 2010

The deactivated catalyzed diesel particulate filter-trap (DPF) was remanufactured by ultrasonic wave treatment with various prepared solutions, followed by active component re-impregnation, and the emission control performance and surface properties of remanufactured DPF were studied at various remanufacturing conditions. The proper ultrasonic wave cleaning time at various prepared solutions and optimal re-impregnation amounts of active component for the best emission control performance of DPF were investigated and its performance tests were also carried out with various temperatures for the conversions of CO, THC (total hydrocarbon) and PM (particulate matter) by catalytic reaction test unit using bypass gas from the diesel engine dynamo system. It was found that the emission control performance of DPF remanufactured with the high-temperature air washing, ultrasonic wave cleaning at acid/base solutions and active component re-impregnation method was recovered to 95% level of its activity compared to that of the fresh DPF, which was caused by removing the deactivating materials from the surface of the DPF, through the analyses of performance test and their surface characterization by Optical microscope, EDX, ICP, TGA, and porosimeter.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.4
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• pp.398-407
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• 2008

We consider a product recovery system that a single product is stocked in order to meet a demand from customers who may return products after usage. This paper addresses a problem of when to release a procurement process to replenish serviceable inventory and how many new products to procure. The structure of the optimal procurement policy is examined and numerically identified as a monotonic threshold curve. A numerical procedure is presented to jointly find the optimal procurement order size, optimal procurement policy, and optimal discounted profit. Sensitivity analysis also indicates that these optimal performance measurements have monotonic properties with respect to system parameters.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.05a
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• pp.40-44
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• 2005

For an increasing interest on environment and a reinforcement of regulation, reverse supply chain is getting more interest recently In this study, reverse supply chain model of the automobile industry is designed using system dynamics. Using this model, an enterprise can do various analysis to get better understanding in strategic and operational aspect. The impact on supply chain which is caused by the variation of remanufacturing rate and recycle rate as time changes can be analyzed. Also environment image of the enterprise can be analyzed in quantitative manner to make it easy to set up own strategic plan.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.162-170
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• 2009

This paper deals with a closed-loop remanufacturing system with one manufacturer and one remanufacturer. The manufacturer sells new products bearing the 'Extended Producer Responsibility (EPR).' It is assumed that the manufacturer's collection rate of used products depends only on the buy-back cost, while that of the remanufacturer depends on the minimum allowed quality level of used products in addition to the buy-back cost. Through the development of mathematical models with the objective function of maximizing profit, we study an efficient operation policy of each party. The decision variables are the unit selling price of new products and remanufactured products, the unit buy-back cost of the used products of the manufacturer and remanufacturer, and the minimum allowed quality level. The validity of the model is examined through numerical examples and sensitivity analysis.

• 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).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.57-70
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• 2011

To address global climate change, various governments are investing in electric vehicle research and, especially in Korea, the application of electric vehicles to public transportation. The lithium batteries used in electric vehicles typically have an expected life cycle of 2-5 years. If electric vehicles become commonly used, they will generate many discarded batteries that could be harmful to the environment. Additionally, lithium batteries are potentially explosive and should be handled appropriately. Thus, reverse logistics issues are involved in handling expired batteries efficiently and safely. Reverse logistics includes the collection, recycling, remanufacturing, and discarding of waste. This study developed a reverse logistics process for electric vehicle batteries after analyzing the as-is process for lead and lithium batteries. It also developed possible disposal regulations for electric vehicle batteries based on current laws regarding conventional batteries.

• 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.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Transactions of the Korean Society of Automotive Engineers
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• v.25 no.3
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• pp.389-396
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• 2017

Restorations of automotive parts have been done ever since the first vehicle was produced. Because the most expensive parts of a vehicle are in the engine system, there have been various restoration methods developed for engine parts. In the case of commercial diesel engines, the fuel injection device is a key and expensive component. It also has a significant effect on vehicle performance. In particular, reduced engine power and increased exhaust gas emissions may result from mechanical damage due to abrasion of the spill valve in the fuel injection system of a diesel engine. In this paper, restoration techniques for damaged parts are applied to restore the abrasion of a spill valve of fuel injection, also called as the "unit injector", of commercial diesel engines. In order to recover the damage, optimized polishing techniques using hard-metal and coating processes are applied. To evaluate restoration techniques for the spill valve, performance and durability tests are performed on a test bench.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.9
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• pp.854-862
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• 2012

The optimal design of batch-storage network by using periodic square wave model provides analytical lot sizing equations for a complex supply chain network characterized as multi-supplier, multi-product, multi-stage, non-serial, multi-customer, cyclic system including recycling and/or remanufacturing. The network structure includes multiple currency flows as well as material flows. The processes are represented by multiple feedstock/product materials with fixed composition which are very suitable for production processes. In this study, transportation processes that carry multiple materials with unknown composition are added and the time frame is changed from single period into multiple periods in order to represent nonperiodic parameter variations. The objective function of the optimization involves minimizing the opportunity costs of annualized capital investments and currency/material inventories minus the benefit to stockholders in the numeraire currency. The expressions for the Kuhn-Tucker conditions of the optimization problem are reduced to a multiperiod subproblem for average flow rates and analytical lot-sizing equations. The multiperiod lot sizing equations are different from single period ones. The effects of corporate income taxes, interest rates and exchange rates are incorporated.