• 대한산업공학회지
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• 제16권1호
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• pp.115-122
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• 1990

Kanban, a pull system for inventory control is in direct contrast to conventional push systems. In the pull system, the kind and quantity of items needed by the succeeding stage are withdrawn from the preceding stage, only at the rate and at the time they are consumed. In this paper, lot size models are formulated in two special cases of practical interests and simple solution procedures are adapted to minimize the total cost of the kanban system. An numerical example is solved to illustrate the method.

• 대한산업공학회지
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• 제12권1호
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• pp.49-53
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• 1986

A dynamic lot size model is developed for the deteriorating items. The amount of deterioration during a period is assumed to be proportional to the inventory at the end of the period. It is further assumed that deterioration rates can differ among periods. This new model is shown to be equivalent to the general one by simple transformation of some variables. A numerical example is given to illustrate the derived results.

• 한국경영과학회지
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• 제1권1호
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• pp.151-170
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• 1976

There are many cases of production processes which intermittently produce several different kinds of products for stock through one set of physical facility. In this case, an important question is what size of production run should be prduced once we do set-up for a product in order to minimize the total cost, that is, the sum of the set-up, carrying, and stock-out costs. This problem is used to be called scheduling of multiple products through a single facility in the production management field. Despite the very common occurrence of this type of production process, no one has yet devised a method for determining the optimal production schedule. The purpose of this study is to develop quantitative analytical models which can be used practically and give us rational production schedules. The study is to show improved models with application to a can-manufacturing plant. In this thesis the economic production quantity (EPQ) model was used as a basic model to develop quantitative analytical models for this scheduling problem and two cases, one with stock-out cost, the other without stock-out cost, were taken into consideration. The first analytical model was developed for the scheduling of products through a single facility. In this model we calculate No, the optimal number of production runs per year, minimizing the total annual cost above all. Next we calculate No$_{i}$ is significantly different from No, some manipulation of the schedule can be made by trial and error in order to try to fit the product into the basic (No schedule either more or less frequently as dictated by) No$_{i}$, But this trial and error schedule is thought of inefficient. The second analytical model was developed by reinterpretation by reinterpretation of the calculating process of the economic production quantity model. In this model we obtained two relationships, one of which is the relationship between optimal number of set-ups for the ith item and optimal total number of set-ups, the other is the relationship between optimal average inventory investment for the ith item and optimal total average inventory investment. From these relationships we can determine how much average inventory investment per year would be required if a rational policy based on m No set-ups per year for m products were followed and, alternatively, how many set-ups per year would be required if a rational policy were followed which required an established total average inventory inventory investment. We also learned the relationship between the number of set-ups and the average inventory investment takes the form of a hyperbola. But, there is no reason to say that the first analytical model is superior to the second analytical model. It can be said that the first model is useful for a basic production schedule. On the other hand, the second model is efficient to get an improved production schedule, in a sense of reducing the total cost. Another merit of the second model is that, unlike the first model where we have to know all the inventory costs for each product, we can obtain an improved production schedule with unknown inventory costs. The application of these quantitative analytical models to PoHang can-manufacturing plants shows this point.int.

• Management Science and Financial Engineering
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• 제22권1호
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• pp.1-4
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• 2016

We consider a two-tier supply chain with multiplicative random yield. We focus on the supply chain performance with respect to the control scheme of determining the production lot size. The profit loss due to distributed control is analyzed to give an insight for devising efficient supply contracts.

• 문화기술의 융합
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• 제8권5호
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• pp.577-582
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• 2022

외상 거래는 고객의 수요를 증대시킬 목적으로 공급자가 경쟁 업체와의 가격 차별화 수단의 하나로 활용되어진다. 특히 공급자(Supplier), 중간유통자(Retailer) 그리고 고객(Customer)으로 구성되는 2 단계 공급사슬의 경우 공급자로부터 허용되는 상품 대금의 지불 유예는 중간유통자의 재고투자비용을 줄이는 수단이 되고, 중간유통자는 줄어든 재고 투자비용의 절감으로부터 최종 고객의 수요 증대를 기대하면서 판매 가격을 할인 할 수 있는 여지를 갖게 된다. 이와 같이 외상을 통한 지불 유예가 고객의 수요 증대를 목적으로 경쟁 기업과의 차별화 방안으로 제공되어 진다는 면에서 보면 외상 거래 기간은 거래량에 따라 차등적으로 허용되는 것이 좀 더 일반적일 수 있다. 퇴화성 제품의 경우 주문량에 따라 주어지는 외상 거래 기간은 중간유통자의 주문량에 긍정적인 요인이 되지만 제품의 퇴화는 주문량의 증가에 부정적인 요인이 될 수 있어 중간유통자의 재고정책 결정에는 두 요인의 절충이 필요하고, 특히 퇴화율은 중간유통자의 재고정책 결정에 중요한 역할을 하게 된다. 본 연구에서는 주문량에 따라 종속적으로 외상 거래기간이 허용되는 상황 하에서 퇴화율이 중간유통자의 재고정책에 미치는 영향을 분석하고자 한다.

• 문화기술의 융합
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• 제5권1호
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• pp.353-360
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• 2019

신용거래는 공급자가 고객의 수요를 증대 시킬 목적으로 경쟁 업체와의 가격 차별화 전략의 하나로 활용되어진다. 고객 입장에서 보면 공급자로부터 제품 대금에 대하여 일정 기간 동안 지불 유예가 허용되면, 재고 투자 비용이 절감되는 효과가 발생하고 결국 고객의 재고 정책에 긍정적인 영향을 미치게 된다. 전통적인 재고 모형의 경우 고객의 주문 비용은 주로 고정 비용으로 가정하였다. 그러나 많은 실제 문제의 경우, 고객은 고정 주문 비용과 함께 제품 운송을 위한 운송비용을 부담하고 있으며, 대부분의 운송비용은 구입량(주문량)에 따라 종속적으로 발생하게 된다. 본 연구에서는 공급자가 고객에게 제품 대금에 대하여 일정 기간 동안 신용거래를 허용하는 상황 하에서 고객의 주문 비용이 고정 주문 비용과 함께 주문량에 따라 종속적으로 발생하는 운송 비용을 포함한 재고 모형을 분석하였다. 문제 분석을 위하여 재고는 시간이 경과함에 따라 일정률로 퇴화한다는 가정 하에 고객의 연간 총 재고 비용에 대한 모형을 수립하였고, 총비용을 최소화하는 경제적 주문량 결정을 위한 해법을 개발하였다.

• 산업경영시스템학회지
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• 제43권2호
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• pp.120-125
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• 2020

Supply chain managers seek to achieve global optimization by solving problems in the supply chain's business process. However, companies in the supply chain hide the adverse information and inform only the beneficial information, so the information is distorted and cannot be the information that describes the entire supply chain. In this case, supply chain managers can directly collect and analyze supply chain activity data to find and manage the companies described by the data. Therefore, this study proposes a method to collect the order-inventory information from each company in the supply chain and detect the companies whose data characteristics are explained through deep learning. The supply chain consists of Manufacturer, Distributor, Wholesaler, Retailer, and training and testing data uses 600 weeks of time series inventory information. The purpose of the experiment is to improve the detection accuracy by adjusting the parameter values of the deep learning network, and the parameters for comparison are set by learning rate (lr = 0.001, 0.01, 0.1) and batch size (bs = 1, 5). Experimental results show that the detection accuracy is improved by adjusting the values of the parameters, but the values of the parameters depend on data and model characteristics.

• 한국농공학회논문집
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• 제53권3호
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• pp.59-64
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• 2011

The objective of the study is to develop life cycle inventory (LCI) database of dam, a major facility for irrigation water supply. The types of database developed are three out of nine dams according to the size of the wate r storage capacity: two kinds larger than 500,000 $m^3$ depending on gate for discharging (Type 1) and the other dam smaller than 500,000 $m^3$ (Type 2). According to the LCI analysis, type 1 larger than 500,000 $m^3$ storage capacity with gate has the lowest environment impact in the 6 impact categories. The impact of the type 1 accounts for 7~35 % of the type 2 for supplying irrigation water. Comparing with the environment impacts of water for other uses such as drinking and industrial water, the impacts of 1 $m^3$ irrigation water supply is 4~45 % of the one for industrial water supply and 1~16 % of the drinking water's. The three types of LCI DB on the irrigation water by dams will be useful in the application of Life Cycle Assessment in agricultural products and environmental labelling including carbon footprint since it is complied to the guidelines of LCI DB constr uction issued by Ministry of Environment and Ministry of Knowledge Economy.

• 산업기술연구
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• 제19권
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• pp.301-312
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• 1999

The purpose of this paper is to study the effects of container size with multi-stage and multi-item on average inventory and customer service level in Kanban systems. We use the different distributions of demand and interarrival time for each item to show that we had better to change the container size depending on different type of item for this simulation study. The small lot size can be used for container size of a single item if there is no setup time. The container size should be identical with average order size as setup time increases. The fill rate increases if the container size is large with multi-item. However, it is difficult to establish the effective container size because the effects of the container size on the order queue time are not clear. It is suitable to use the average order size as the container size for each item if the variance of demand and interarrival time of each item is relatively small. It is effective to sue the average container size if the variance of them is relatively large.

• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.57-64
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• 2021

The domestic semiconductor industry can produce various products that will satisfy customer needs by diversifying assembly parts and increasing compatibility between them. It is necessary to improve the production line as a method to reduce the work-in-process inventory (WIP) in the assembly line, the idle time of the worker, and the idle time of the process. The improvement of the production line is to balance the capabilities of each process as a whole, and to determine the timing of product input or the order of the work process so that the time required between each process is balanced. The purpose of this study is to find the optimal WIP and buffer size through SA (Simulated Annealing) that minimizes lead time while matching the number of two parts in a parallel assembly line with bottleneck process. The WIP level and buffer size obtained by the SA algorithm were applied to the CONWIP and DBR systems, which are the existing production systems, and the simulation was performed by applying them to the new hybrid production system. Here, the Hybrid method is a combination of CONWIP and DBR methods, and it is a production system created by setting new rules. As a result of the Simulation, the result values were derived based on three criteria: lead time, production volume, and work-in-process inventory. Finally, the effect of the hybrid production method was verified through comparative analysis of the result values.