• Proceedings of the Korea Society for Simulation Conference
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• 1999.04a
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• pp.105-109
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• 1999

Tool shop of the D Heavy Industries Co.(DHI) fabricates engines for a bus, truck, small ship. In order to increase the production capacity of engines, DHI will be established the new tool shop that consists of a block line, head line, assembly line, test line and AS/RS in 1999. In order to assure the production capacity designed of the new tool shop for producing engines and improve the production process of it, it is needed to find a bottleneck process and an optimal way of allocating workloads among machines and workers to maximize the production. In a way to solve this, we model the engine fabrication process of the tool shop and analyze its performance by computer simulation. In this study, we at first identify the bottleneck processes of the engine fabrication process under the designed operation policy. Then, we derive some alternative operating policies applicable to the new tool shop of an engine, and analyze the optimal operation policy by comparing the performance of the tool shop following each alternative policy.

• Journal of the military operations research society of Korea
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• v.9 no.1
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• pp.69-74
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• 1983

This article presents a deterministic inventory model for situations in which, during the stockout period, a fraction ${\beta}$ of the demand is backordered and the remaining fraction $1-{\beta}$ is lost. By defining a time proportional backorder cost and a fixed penalty cost per unit lost, a convex objective function representing the average annual cost of operating the inventory system is obtained. The optimal operating policy variables are calculated directly. At the extremes ${\beta}\;=\;1$ and ${\beta}\;=\;0$ the model presented reduces to the usual backorders and lost sales case, respectively.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.18-28
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• 2006

We consider a Direct Input Output Manufacturing System(DIOMS) which has a munber of machine centers placed along a built-in Automated Storage/Retrieval System(AS/RS). The Storage/Retrieval (S/R) machine handles parts placed on pallets for the operational aspect of DIOMS and determines the optimal operating policy by combining computer simulation and genetic algorithm. The operational problem includes: input sequencing control, dispatching rule of the S/R machine, machine center-based part type selection rule, and storage assignment policy. For each operating policy, several different policies are considered based on the known research results. In this paper, using the computer simulation and genetic algorithm we suggest a method which gives the optimal configuration of operating policies within reasonable computation time.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.1
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• pp.43-55
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• 2009

We consider a Direct Input Output Manufacturing System(DIOMS) which has a number of machine centers placed along a built-in Automated Storage/Retrieval System(AS/RS). The Storage/Retrieval (S/R) machine handles parts placed on pallets for the operational aspect of DIOMS and determines the optimal operating policy by combining computer simulation and genetic algorithm. The operational problem includes: input sequencing control, dispatching rule of the SIR machine, machine center-based part type selection rule, and storage assignment policy. For each operating policy, several different policies are considered based on the known research results. In this paper, using the computer simulation and genetic algorithm we suggest a method which gives the optimal configuration of operating policies within reasonable computation time.

• Journal of Korean Society for Quality Management
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• v.29 no.3
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• pp.39-48
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• 2001

Preventive maintenance(PM) is an action taken on a repairable system while it is still operating, which needs to be carried out in order to keep the system at the desired level of successful operation. In this paper, we consider a Bayesian approach to determine an optimal periodic preventive maintenance policy. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established. Some numerical examples are presented for illustrative purpose.

• Journal of Korean Institute of Industrial Engineers
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• v.8 no.2
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• pp.33-36
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• 1982

This paper considers preventive maintenance policies for a system with two types of units which is subject to deterioration. Two generalized models are investigated ; a preventive maintenance policy based on the cumulative operating time and a policy based on the number of minimal repairs performed. Optimal preventive maintenance policies which minimize the expected average cost per unit time including the earning loss due to the deterioration are discussed and some numerical examples are given.

• Korean Management Science Review
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• v.29 no.1
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• pp.1-14
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• 2012

The goal of the multi-reservoir operation planning is to provide an optimal release plan that maximize the reservoir storage and hydropower generation while minimizing the spillages. However, the reservoir operation is difficult due to the uncertainty associated with inflows. In order to consider the uncertain inflows in the reservoir operating problem, we present a Stochastic Dynamic Programming (SDP) model based on the markov decision process (MDP). The objective of the model is to maximize the expected value of the system performance that is the weighted sum of all expected objective values. With the SDP model, multi-reservoir operating rule can be derived, and it also generates the steady state probabilities of reservoir storage and inflow as output. We applied the model to the Geum-river basin in Korea and could generate a multi-reservoir monthly operating plan that can consider the uncertainty of inflow.

• Journal of the military operations research society of Korea
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• v.23 no.1
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• pp.63-75
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• 1997

This study is concerned with a few models for optimal requirement level of CSP by improving and adjusting the existing models to determine CSP items and quantity as follows. First, by building a model with a objective function of the operating level and constrains of budget, quantity and items of CSP are simultaneously determined. Second, we removed some steps to improve initial solution by using a constraint of usable budget level. Third, we demonstrated a model to be applied with real operating situation by combining two models of Lee(1994) and above. Lastly, by assuming a failure probability distribution is a binomial distribution, the better solution can be obtained. Some facts with necessity of policy improvement were raised as follows: (1) necessity of improvement of the CSP acquisition system, (2) in case of the same kind, permission of diversion in order to execute budget effectively, (3) getting accurate failure rate.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.14 no.24
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• pp.7-13
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• 1991

Recently, in FMS composing of various automatic equipments, the machines with lower operating costs, and with higher operating costs and replacement costs resulting from deterioration have been appearing successively as a result of rapidly advances in technology. "Control Limit Policy" [1] by using Markov decision policy, a kind of optimal economic replacement decision, well reflects and represents this environment. In this paper, it is reviewed that the decision method of the forecasted replacement alternatives in planning horizon under technological advances is derived. The proposed method is applied to a numerical example and some characteristics are examined by sensitivity. It is clarified that the method is relatively insensitive to changes of parameters at the present decision. decision.

• Journal of Korean Society of Forest Science
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• v.82 no.4
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• pp.396-405
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• 1993

In this paper, a nonlinear programming model to determine the optimal operating policy to minimize production costs for particleboard plants is presented. The model provides optimal values for three decision variables : specific gravity of particleboard, mat moisture content and mat resin content. These decision variables are key factors influencing the cost and quality of particleboard manufacturing processes. In formulating the nonlinear programming model, the minimum quality standards for internal bond strength and modulus of rupture of particleboard are used as industry-wide quality constraints. These quality standards are expressed as nonlinear functions of the decision variables. In order to demonstrate the applicability of the proposed model, the model is applied to solve for optimal solutions of four theoretical problems. The problem scenarios are built to investigate effects of changes in hot-pressing speed and purchase price of chip and resin.