• Journal of Korean Institute of Industrial Engineers
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• v.34 no.1
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• pp.1-12
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• 2008

The Kanban system in Just-In-Time (JIT) production is very effective in reducing the inventories when consumption rate of the final product is relatively stable. When large fluctuations exist in the consumption rate, a new production ordering policy in which the production order quantity is determined by smoothing the demands exponentially is more suitable. This new ordering policy has not been investigated sufficiently. In this research, a multi-stage production and inventory system with stock points for materials and finished items located at each stage is considered. Approximations of average inventories at each stage in the system are derived theoretically. Numerical simulations are carried out to assess the accuracy of approximations and to evaluate the effectiveness of the new ordering policy as compared with the Kanban system. As a result, it is shown that the new ordering policy can achieve significantly lower inventory costs than the original Kanban system. The new ordering policy thus emerges as a key concept for an effective supply chain management.

• Journal of Korean Institute of Industrial Engineers
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• v.3 no.1
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• pp.39-47
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• 1977

Most of the current literature on inventory theory has been devoted to the study of single stage models. A class of inventory problems which is of great interest is the multistage inventory system which involves a series and hierarchical sequence of stations. This study analyzes some aspect of the series type and multi-stage inventory system, using the fixed cycle ordering which bas a modificatory control function in the system equations. The objective of this study is to clarify the dynamic behavior of the system. The author has derived the theoretical formulas of variation of ordering quantity and stock fluctuation of each stage due to power spectral density function. Influence of parameters such as, (1) intensity of autocorrelation of demand sequence ($\lambda$), (2) forecasting exponential smoothing factors of each stage (${\alpha}_1,\;{\alpha}_2,\;{\alpha}_3$) and (3) production control factor of the 3rd stage ($\gamma$), as operators of the system on the variation of ordering quantity and stock fluctuation of the system. is also clarified. As a result of this study, the relations between the variation of ordering quantity, stock fluctuation and the parameters of the system, have been found. The principles and the theorical analysis presented here will be applicable to more complex type of discrete control systems in constructing the specific condition of the system to minimize inventory variances.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.2
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• pp.251-256
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• 2006

In this paper we consider multi-stage, multi-product production, inventory systems which have assembly-tree-structure. We propose a new mathematical model for pull type ordering systems based on JIT manufacturing systems. To apply the model to an actual automobile parts manufacturer, the objective of proposed model is to minimize the sum of inventory and setup costs. Finally, a numerical example and computational results are given to illustrate the proposed model.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.151-157
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• 1993

In this paper, we investigate the effects of yield randomness for lot-sizing in a multi-stage production system. The practical importance of incorporating yield randomness into production models has been emphasized by many researchers. Yield randomness, especially in semiconductor manufacturing, poses a mojor challenge for production planning and control. The task becomes even more difficult if the demand for final product is uncertain. An attempt to meet the demand with a higher level of confidence forces one to release more input in the fabrication line. This leads to excessive work-in-process (WIP) inventories which cause jobs to spend unpredictably longer time waiting for the machines. The result is that it is more difficult to meet demand with exceptionally long cycle time and puts further pressure to increase the safety stocks. Due to this spiral effect, it is common to find that the capital tied in inventory is the msot significant factor undermining profitability. We propose a policy to determine the quantity to be processed at each stage of a multi-stage production system in which the yield at each stage may be random and may need rework.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.1
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• pp.29-41
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• 2006

As the quality and environmental problems become one of the most concerned issues of company, the rework policy needs to be efficiently designed and implemented to sustain the company's competitiveness. This paper examines three basic rework policies in multi-stage production systems and analyzes them in terms of costs of setup, production, inspection, and inventory. For analyzing the performance of the rework policies, we propose mathematical models which can compute total production cost and determine the optimal production batch size to minimize the total production cost. The rework policies are classified by the number and location of inspection stages. Using the mathematical models, we could analyze the performances of rework policies and suggest the optimal rework policy according to each manufacturing environment. The analyses show that the proposed model can be used to analytically evaluate and choose the rework policies.

• 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).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.186-194
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• 1990

Just-In-Time production is to keep the kanban system. When production managers implement and operate successfully the system in the multi-Line, multi-stage production setting, it is very important to determine the number of kanbans in deterministic kanban system under consideration with relevant factors as well as with cost. In concrete, we discuss about following factors in kanban system and provide a model formulating the multi-objective goal programming : Demand, stock on hand in process, Inventory cost and Labor cost, Vendor's suppling capacity, Work Load. Finally we analyze several numerical examples in order to test the model and attempt to expand the model in general case.

• The Journal of Society for e-Business Studies
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• v.7 no.2
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• pp.143-156
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• 2002

The objective of supply chain planning is to satisfy the requirements for minimizing inventory costs, transportation costs, and lead times throughout the supply, production and distribution stage dispersed geographically. Therefore, the supply chain planning system should have functionalities to resolve complex optimization problems that have characteristics of multi-stage and multi-product. Ant the system should also support collaborative decision making among distributed business partners. In this study, we proposed a distributed architecture for the supply chain planning system. To do this, we analyzed functional requirements by using IDEF-0(ICAM Definition-0) methodology, defined required components, and designed each component by using object-oriented methodology. We implemented a prototype system based on CORBA (Common Object Request Broker Architecture) to show that the proposed distributed architecture based on component technology is feasible and can solve supply chain planning problem collaboratively.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.41-65
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• 2002

We study a multi-component production/inventory system in which individual components are made to meet various demand types. We assume that the demands arrive according to a Poisson process, but there is a fixed probability that a demand requests a particular kit of different components. Each component is produced by a flow line with several stations in which the processing times of each station follow a two-stage Coxian distribution. The production of each component is operated by an independent base-stock policy with blocking. We assume that the time needed to assemble final products follows a general distribution and the capacity of an assembling facility is sufficiently large. The objective of this study is to obtain key performance measures such as the distribution of the number of each orders for each final product and the mean time of fulfilling a customer order. The basic principle of the proposed approximation method is to decompose the original system into a set of subsystems, each subsystem being associated with a flow line. Each subsystem is analyzed in isolation using a Marie's method. An iterative procedure is then used to determine the unknown parameters of each subsystem. Numerical results show that the accuracy of the approximation method is acceptable.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.113-119
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• 1987

A Multistage production-inventory model is developed for deteriorating items. The model is developed deterministic but time-varing demand pattern and instantaneous delivery. Deterioration rates are assumed to vary from period to period. Discrete version of Pontryagin's maximum principle is used to present the efficient alogrithm to solve this model easily. A numerical example is given to illustrate the derived results.