• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.1
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• pp.51-58
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• 1997

In this paper, we propose a stochastic LP model for determining an optimal input quantity in a single-product multi-stage production system with random yields. Due to the random yields in our model, each stage of the production system can result in defective items, which can be re-processed or scrapped at certain costs. We assume that the random yield at each stage follows an independent discrete empirical distribution. Compared to dynamic programming models that prevail in the literature, our model can easily handle problems of larger sizes.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.10a
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• pp.175-184
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• 1993

Modeling the production process is a necessary and essential aspect of the production planning. This paper introduces a theoretical model of the multi-stage production process. A multi-stage production process is regarded as a network of interrelated production activities which use system exogenous inputs of goods in production and the intermediate products transfers between activities to produce final products. Our model is characterized by (1) a few of the production-related assumptions and (2) two types of elements "goods and activities" that are represented in terms of the network terminology. This model is different from the another multi-stage production models, so-called production network models in relation to the production-theoretical concept. It is not based on the concept of the production correspondence and the activity production functions, but the technology model of Koopmans. Koopmans.

• 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 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.

• Management Science and Financial Engineering
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• v.6 no.1
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• pp.37-63
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• 2000

An important objective of pull-based production control is to achieve synchronized and smooth production flow in a multi-stage system that is subject to uncertainty. To our knowledge, previous research has not generated a performance measure that captures this objective of pull-based probased production control system. This performance material with respect to the instant when the operation is required. We examine the issue of asynchronous waste in a two-stage kanban control system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1579-1602
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• 2020

In the design of production system, buffer capacity allocation is a major step. Through polymorphism analysis of production capacity and production capability, this paper investigates a buffer allocation optimization problem aiming at the multi-stage production line including unreliable machines, which is concerned with maximizing the system theoretical production rate and minimizing the system state entropy for a certain amount of buffers simultaneously. Stochastic process analysis is employed to establish Markov models for repairable modular machines. Considering the complex structure, an improved vector UGF (Universal Generating Function) technique and composition operators are introduced to construct the system model. Then the measures to assess the system's multi-state reliability and structural complexity are given. Based on system theoretical production rate and system state entropy, mathematical model for buffer capacity optimization is built and optimized by a specific genetic algorithm. The feasibility and effectiveness of the proposed method is verified by an application of an engine head production line.

• 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.

• Korean Journal of Human Ecology
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• v.9 no.1
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• pp.107-116
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• 2000

The purpose of this study was to suggest the data of base for automated underwear manufacture by analyzing the technology of the automated underwear manufacturing facilities in the area of Jeonbuk with a focus on Jeonju and Iksan. The case study samples were 6 underwear firms. The results were as follows : 1. Automated underwear manufacturing systems in the area of JeonBuk introduced over the entire period between 1990 and 1997. Most of Their production type was multi-kind and small-quantity production. 2. They were using Gerber, Assyst, Lectra, Microdynamics and Investronica systems as the CAD/CAM system, of which the Gerber system was mostly used by them. 3. In the stage of production planning and in the stage of preparation for production, most of them realized automation, but in the stage of main production, every firm did not realize automation. In most cases, they used both the stage of mechanization and the stage of unit process automation.

• 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 the Society of Naval Architects of Korea
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• v.45 no.5
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• pp.547-553
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• 2008

Multi Progress Planning System problem in a multi-stage manufacturing system have a complexity and peculiarity different from other kinds of production system. World leading company has invested much cost and effort into a Real-Time Planning System and intelligent manufacturing field to obtain their own competitiveness. Especially Real-Time Planning System for ship production process as a part of intelligence for a shipyard. Real-Time Planning System, simulation based system, or virtual manufacturing system is an approach to achieve a such goal. It is expected that the Real-Time Planning System will contribute to the improvement of the productivity in working process at a shipyard. Also, This Real-Time Planning System will optimize the entire shipbuilding process in a multi progress planning environment for the delivery.