• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.106-116
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• 2016

MTO (Make to Order) is a manufacturing process in which manufacturing starts only after a customer's order is received. Manufacturing after receiving customer's orders means to start a pull-type supply chain operation because manufacturing is performed when demand is confirmed, i.e. being pulled by demand (The opposite business model is to manufacture products for stock MTS (Make to Stock), which is push-type production). There are also BTO (Build to Order) and ATO (Assemble To Order) in which assembly starts according to demand. Lean manufacturing by MTO is very efficient system. Nevertheless, the process industry, generally, which has a high fixed cost burden due to large-scale investment is suitable for mass production of small pieces or 'mass customization' defined recently. The process industry produces large quantities at one time because of the lack of manufacturing flexibility due to long time for model change or job change, and high loss during line-down (shutdown). As a result, it has a lot of inventory and costs are increased. In order to reduce the cost due to the characteristics of the process industry, which has a high fixed cost per hour, it operates a stock production system in which it is made and sold regardless of the order of the customer. Therefore, in a business environment where the external environment changes greatly, the inventory is not sold and it becomes obsolete. As a result, the company's costs increase, profits fall, and it make more difficult to survive in the competition. Based on the customer's order, we have built a new method for order system to meet the characteristics of the process industry by producing it as a high-profitable model. The design elements are designed by deriving the functions to satisfy the Y by collecting the internal and external VOC (voice of customer), and the design elements are verified through the conversion function. And the Y is satisfied through the pilot test verified and supplemented. By operating this make to order system, we have reduced bad inventories, lowered costs, and improved lead time in terms of delivery competitiveness. Make to order system in the process industry is effective for the display glass industry, for example, B and C groups which are non-flagship models, have confirmed that the line is down when there is no order, and A group which is flagship model, have confirmed stock production when there is no order.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.343-348
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• 2002

We are concerned with a long-term replenishment contract for the ARIMA demand process in a supply chain. The chain is composed of one supplier, one buyer and consumers for a product. The replenishment contract is based upon the well-known (s, Q) policy but allows us to contract future replenishments at a time with a price discount. Due to the larger forecast error of future demand, the buyer should keep a higher level of safety stock to provide the same level of service as the usual (s, Q) policy. However, the buyer can reduce his purchase cost by ordering a larger quantity at a discounted price. Hence, there exists a trade-off between the price discount and the inventory holding cost. For the ARIMA demand process, we present a model for the contract and an algorithm to find the number of the future replenishments. Numerical experiments show that the proposed algorithm is efficient and accurate.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.4
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• pp.345-351
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• 2001

We are concerned with a multiple replenishment contract with a purchase price discount in a supply chain. The chain is composed of one supplier, one buyer and consumers for a product. The replenishment contract is based upon the well-known (s, Q) policy but allows contracting several firmed orders at a time with a price discount. Due to a larger forecast error of the future demand, the buyer should keep a higher level of safety stock to provide the same level of service of the usual (s, Q) policy but can reduce his purchase cost by placing larger quantity. Thus there exists a trade-off between the price discount and inventory holding cost. We present a model for the contract and an algorithm to find the optimum number of the firmed orders. Computer experiments show that the algorithm finds the global optimum solution very fast.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.4
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• pp.125-138
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• 2006

This paper considers a periodic review, two-echelon inventory system with one central warehouse and several re-tailers facing normally distributed demand. The goal is to attain target fill rates, while the systemwide total holding costs are minimized. An important aspect of this problem is material rationing in the case of shortages. If a central warehouse has insufficient inventory to deliver all replenishment orders to retailers, all order quantities are should be adjusted according to some rationing rule. A simple but efficient rationing rule is proposed and compared with the Balanced Stock (BS) rationing as introduced by Heijden which is known to be the best rationing policy in the literature. Numerical results show that the proposed rationing rule is more cost effective than BS rationing, especially for the differences in holding costs between retailers are large.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.153-158
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• 2018

At the Bank of Korea, capital stock statistics were created by the PIM (perpetual inventory method) with fixed capital formation data. Asset classifications also included 2 categories in residential buildings, 4 non-residential buildings, 14 constructions, 9 transportation equipment, 28 machinery, and 2 intangible fixed assets. It is the Korean government accounting system which is developed much with the field of the national accounts including the valuation, but until 2008 it was consistent with single-entry bookkeeping. Many countries, including Korea, were single-entry bookkeeping, not double-entry bookkeeping which can be aggregated by government accounting standard account. There was no distinction in journaling between revenue and capital expenditure when it was consistent with single-entry bookkeeping. For example, we would like to appropriately divide the past budget accounts and the settlement accounts data that have been spent on dredging into capital expenditure and revenue expenditure. It, then, tries to add the capital expenditure calculated to FCF (fixed capital formation), because revenue expenditure is cost for maintenance etc. This could be a new direction, especially, in the estimation of capital stock by the perpetual inventory method for infrastructure (SOC, social overhead capital). It should also be noted that there are differences not only between capital and income expenditure but also by other factors. How long will this difference be covered by the difference between the 'new series' and 'old series' methodologies? In addition, there is no large difference between two series by the major asset classification level. If this is treated as a round-off error, this is a problem.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.1
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• pp.91-103
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• 2006

Given a bill of materials (BOM) tree T labeled by the breadth first search (BFS) order from node 0 to node n and a general network ${\Im}=(V,A)$, where V={1,2,...,m} is the set of production facilities and A is the set of arcs representing transportation links between any of two facilities, we assume that each node of T stands for not only a component. but also a production stage which is a possible stocking point and operates under a periodic review base-stock policy, We also assume that the random demand which can be achieved by a suitable service level only occurs at the root node 0 of T and has a normal distribution $N({\mu},{\sigma}^2)$. Then our integrated model of facility location problems and safety stock optimization problem (FLP&SSOP) is to identify both the facility locations at which partitioned subtrees of T are produced and the optimal assignment of safety stocks so that the sum of production cost, inventory holding cost, and transportation cost is minimized while meeting the pre-specified service level for the final product. In this paper, we first formulate (FLP&SSOP) as a nonlinear integer programming model and show that it can be reformulated as a 0-1 linear integer programming model with an exponential number of decision variables. We then show that the linear programming relaxation of the reformulated model has an integrality property which guarantees that it can be optimally solved by a column generation method.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.311-314
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• 2005

Supply chain optimization is one of the most important components in the optimization of a company's value chain. This paper considers the problem of designing the supply chain for a product that is represented as an assembly bill of material (BOM). In this problem we are required to identify the locations at which different components of the product arc are produced/assembled. The objective is to minimize the overall cost, which comprises production, inventory holding and transportation costs. We assume that production locations are known and that the inventory policy is a base stock policy. We first formulate the problem as a 0-1 nonlinear integer programming model and show that it can be reformulated as a 0-1 linear integer programming model with an exponential number of decision variables.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.19-32
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• 2018

This study focuses on an M/M/1 queue with an attached continuous-type inventory. The customers arrive into the system according to the Poisson process, and are served in their arrival order; i.e., first-come-first-served. The service times are assumed to be independent and identically distributed exponential random variable. At a service completion epoch, the customer consumes a random amount of inventory. The inventory is controlled by the traditional (s, S)-inventory policy with a generally distributed lead time. A customer that arrives during a stock-out period assumed to be lost. For the number of customers and the inventory size, we derive a product-form stationary joint probability distribution and provide some numerical examples. Besides, an operational strategy for the inventory that minimizes the long-term cost will also be discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.79-89
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• 2023

The inventory of many materials requires a large storage space, and the longer the storage period, the higher the potential maintenance cost. When materials are stored on a construction site, there are also concerns about safety due to the reduction of room for movement and working. On the other hand, construction sites that do not store materials have insufficient inventory, making it difficult to respond to demands such as sudden design changes. Ordering materials is then subject to delays and extra costs. Although securing an appropriate amount of inventory is important, in many cases, material management on a construction site depends on the experience of the site manager, so a reasonable material inventory management plan that reflects the construction conditions of a site is required. This study proposes an economical material management method by reflecting variables such as the status of the preceding and following activities, site size, material delivery cost, timing of an order, and quantity of orders. To this end, we set the appropriate inventory amount while adjusting related activities in the activity network, using float time for each activity, the size of the yard, and the order quantity as the main variables, and applied a genetic algorithm to this process to suggest the optimal order timing and order quantity. The material delivery cost derived from the results is set as a fitness index and the efficiency of inventory management was verified through a case application.

• 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.