• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.28
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• pp.165-171
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• 1993

The algorithm of Giffler and Thompson is modified for solving job shop scheduling problems related to the overlapping production The start-lag and stop-lag are also applied New priority rules for the overlapping production are proposed and the efficiency of them is compared with that of the classical priority rules.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.17-24
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• 1997

This research suggests an approach to reduce the physical distribution cost of production by analyzing data from real situations. The proposed approach re-layouts facilities according to the SLP(Systematic Layout Planning) method. An application result showed that the production lead time was reduced by 24% and the payoff period for facility re-layout was about ten months.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1603-1608
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• 2011

This study reviewed how colleges can nurture creative media-major students by innovative curriculum of interdisciplinary project class for contents production, and also the consequent merits, faults and forcoming additional subject which should be studied more.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.25
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• pp.75-82
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• 1992

Standard acceptance sampling plans models the production pricess as a sequence of independent identically distributed Beruoulli random variables. However, the quality of items sampled sequentially from an ongoing production process of ten exhibits statistical dependency that is not accounted for in standard acceptance sampling plans. In this paper, a dependent production process is modelled as an ARMA process and as a two-state Markov chain. A simulation study of each is performed. A comparison of the probability of acceptance is done for the simulation method and for the approximation method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.35
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• pp.89-94
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• 1995

Previous MRP models were developed without considering learning effects on the determination of the production lot size environment. The only consideration was the setup and inventory holding costs. In this paper the proposed MRP model were developed incorporated the effects of learning. The result of this model show that learning significantly influence the production lot size and total variable cost. The numerical examples have been used to illustrated the impact of proposed model.

• 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.19 no.2
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• pp.65-74
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• 1993

In this paper, a two-echelon production-inventory model is developed which integrates the production scheduling problem of the multi-products produced on a single facility and the inventory problem of the related raw materials. The setup costs of the final products are assumed to be dependent on the production sequence. The aim is to determine simultaneously the production cycle time and the production sequence of the final products, and the procurement cycle times of the raw materials. For the model developed, a solution algorithm is suggested and illustrated with a numerical example. And the result is compared with those obtained by two separate subproblems.

• IE interfaces
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• v.24 no.3
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• pp.241-247
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• 2011

This paper develops a mathematical model which searches an optimum lot size of a press line, and applies this model to the scheduling of the press line. This mathematical model is not a widely studied cost model but a model which considers the utilization of the press line under a lean production system. In this paper, the optimum lot size is a minimum lot size which does not exceed the total work time of the press line. A production volume and the priority of the production in the press line are adjusted using this optimum lot size. A mathematical model developed in this paper will allow determining the optimum lot size easily in case of variable production environments such as an introduction of a new product and a fluctuation of production volume of each item. Therefore, our model will make a better scheduling of the press line and will enhance the utilization of it.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.20-32
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• 1995

This paper is concerned with the economic selection of both the lower limit and the process mean for a continuous production process. Consider a production process where items are produced continuously. All of the items are subject to acceptance inspection. The items for which the measured values of the quality characteristic are larger than the lower limit are accepted, and those smaller than the lower limit are rejected and excluded from shipment. The process mean may be set higher to reduce the costs incurred by imperfect quality. Using a higher process mean, however, results in a higher production cost when production cost is an increasing function of the quality characteristic. Assuming that the quality characteristic is normally distributed with known variability, cost models are constructed which involve production cost, cost incurred by imperfect quality, rejection cost, and inspection cost. Methods of finding optimal values of the lower limit and the process mean are presented and numerical examples are given.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.403-420
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• 1997

In this paper, we examine the effect of production uncertainty to production control policies. First, we examine two famous production control policies, namely, MRP and JIT from the view point of shop floor control perspective, and analyze the differences between them due to demand fluctuations and activity time variations. Second, we conduct simulation studies on MRP and JIT to draw out the effects of demand fluctuations and activity time variations. Demand fluctuations are further classified into demand lumpiness and demand irregularity. And, activity time variations are further classified into stationary time variations and non-stationary time variations. Experimental results show that, in terms of demand fluctuations, MRP is affected by demand lumpiness, but JIT by demand irregularity. And we also see that both MRP and JIT are influenced by stationary time variation with respect to activity time variations.