• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.1
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• pp.83-95
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• 2010

This paper considers a firm that operates make-to-stock and make-to-order facilities in successive stages. The make-to-stock facility produces components which are consumed by the external market demand as well as the internal make-to-order operation. The make-to-order facility processes customer orders with the option of acceptance or rejection. In this paper, we address the problem of coordinating how to allocate the capacity of the make-to-stock facility to internal and external demands and how to control incoming customer orders at the make-to-order facility so as to maximize the firm's profit subject to the system costs. To deal with this issue, we formulate the problem as a Markov decision process and characterize the structure of the optimal inventory allocation and customer order control. In a numerical experiment, we compare the performance of the optimal policy to the heuristic with static inventory allocation and admission control under different operating conditions of the system.

• IE interfaces
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• v.14 no.1
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• pp.9-19
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• 2001

Production planning and control system plays an important role in manufacturing companies because it determines all production capacity planning, material procurement planning, and production scheduling which are needed in the process of producing products. Many researches on production planning and control system have been conducted for many manufacturing companies for recent decade. But, a considerable research achievement has mainly been obtained on the forecast-driven production for a make-to-stock and an assemble-to-order. The reason is that there are some hardships such as difficulties of standardizing product information, the frequent changes of design and material, and the unexpected dynamic events that influence the production of customer's order in a make-to-order or an engineering-to-order environments. By these characteristics and their complexities, some studies for production planning and control system in a make-to-order environment are presented recently. In this paper, we present the framework of the hietachical production planning and control for a make-to-order environment with dynamic events. In order to illustrate the usefulness of the proposed framework for a hietachical production planning and control, the information system for a make-to-order production was implemented with the object of the company of producing electricity transformer.

• Journal of the Korea Safety Management & Science
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• v.23 no.4
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• pp.73-81
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• 2021

Today's manufacturers must respond quickly to customer needs. In particular, make-to-order companies are constantly striving to satisfy customer demand for products in order to secure more favorable conditions in the future through bidding. In this bidding process, quotations play a very important role in providing favorable conditions. And the most important content that companies strive to satisfy their customers is the product's performance. Therefore, a company can attract customers and secure economic profits through good quotations, but it can be said that the first priority is to match the performance of the products requested by the customers. That is, when a company creates a quotation, it is important to structure the quotation according to the performance of the product. Thus, this paper intends to present a quotation management framework and a quotation BOM information model for constructing quotations efficiently in make-to-order manufacturing. And, in order to prove the usefulness of the proposed quotation management framework, we presents an case of the construction of an quotation management system based on the JAVA platform. As a result, the integrated quotation management system based on the proposed quotation management framework and quotation BOM has been successfully operated in a make-to-order company that manufactures marine engines.

• IE interfaces
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• v.18 no.2
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• pp.148-157
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• 2005

The manufacturing industry with Make-to-Order production system is difficult to decide the standard information for the product and the demand is variable to estimate. In this paper, we concerned with the process planning method using data mining in the manufacturing industry with Make-to-Order environment. The subject of our study is the industry transformer plant which is received an diverse order of customer and then produced the product. Currently, process planning method is classified the standard information by hand based on the acquired knowledge through the experience. The standard information stored the various information, such as work sequence, time and so on. This process planning method needs an experts which possesses the field experience for several years. For the product specification which is varied in each order, current process planning method is not efficient due to need many times To solve this problem, we extract the information using data mining process for each processing time, and then construct the knowledge base. We propose a method which is the process planning of the industry transformer product in Make-to-Order environment using the knowledge base.

• IE interfaces
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• v.11 no.2
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• pp.177-190
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• 1998

The work-order performs an important role in make-to-order production. The development of work-order system in this production is more complex than work-order system in planing production. To construct work-order system, load of directors for work-order must be decreased, and production management between scheduling of master plan and current workshop conditions must be considered. In this study, we grasped troubles in present work-order system and flows of information for work order. Using these results are made database schemas and data flow diagrams for effective development of work-order system. And then, for successful establishment of work-order system and actual use of directors, we considered systematic and easy user-interface. For a case study, development procedures of work-order system are presented for plant factory.

• IE interfaces
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• v.20 no.1
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• pp.11-20
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• 2007

This case study aims to embody the requirement of the make-to-order type manufacturer who wants to manage risks effectively when decisions are required to be taken under a risk. First, we present a method for choosing the risk factors that should be controlled for the make-to-order type manufacturer. Subsequently, those factors have been verified using statistical methods such as the ANOVA test. The process flows to be operated with the selected risk factors and the rules for an early warning system have been proposed. For a couple of factors, a prototype system has been developed to illustrate actual applications. Applications of the technique developed here for other types of manufacturers might be an interesting research problem.

• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.196-203
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• 2010

Make-to-forecast production is a way to realize high customization and fast responsiveness. This study firstly investigates the effect of introducing a common component in a make-to-forecast production environment. The common component can eliminate a modification step, which is a major cost component in make-to-forecast production. It is illustrated, however, that introducing a versatile component that merely covers several variants is unattractive, and thus adding values to the common component is inevitable in this environment. Secondly, an order-matching rule under the condition that two partially overlapped delivery lead time intervals exist is proposed. The rule considers the effect of matching orders to units that can cover both intervals. An alternative re-matching rule is also developed and examined. Numerical experiments clarify that the proposed rule generally realizes higher contribution ratio and lower percentages of orphans and rejected orders. The proposed re-matching rule increases the average contribution ratio at the expense of increased orphans and order rejections.

• IE interfaces
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• v.23 no.4
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• pp.327-336
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• 2010

We consider a supply chain consisting of a make-to-order manufacturer and N component suppliers and study the impacts of the number of suppliers on component inventory management. The manufacturer has full information and continuously observes the state of both component inventory level and customer backorders. Based on this information, the manufacturer determines whether or not to place a component purchasing order to a supplier among N suppliers even though some orders are in process by other suppliers. The goal of this paper is to numerically identify the manufacturer's purchasing policy which minimizes the total supply chain cost and the best choice of N. Our model contributes to the current literature in that the problem of simultaneously considering multiple outstanding orders and incorporating order setup cost into the model has not been covered yet. From numerical experiment, we investigate how much the policy with N suppliers can contribute to reducing the supply cost compared to the policy with a single supplier.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.2
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• pp.117-129
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• 2005

This paper considers a make-to-order inventory-production system in which customer orders are admitted only when the number of outstanding customer orders is below a value committed by the system. We deal with general distributions for the customer order Inter-arrival, production, and replenishment lead time processes. Monotonicities of the optimal average cost with respect to these distribution parameters are established using sample path coupling arguments. When distributions are given as an exponential one, we implement a sensitivity analysis on the optimal inventory policy and show that it has monotonicities with respect to system costs using dynamic programming.

• IE interfaces
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• v.16 no.2
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• pp.185-194
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• 2003

This paper deals with a realistic production scheduling under a make-to-order production environment. The practical case is studied on the transformer winding process in the 'H' company. The transformer winding is a process that rolls a coil that is coated with an electric insulation material in order to generate the required voltage using the voltage fluctuation. This process occupies an important position among the production processes in the transformer manufacturing company. And this process is composed of parallel machines with different performances according to the voltage capacity and winding type. In this paper, we propose a practical heuristic algorithm for production scheduling to satisfy the customer’s due date under a make-to-order production environment. Also, we implement the production scheduling system based on the proposed heuristic algorithm. Consequently, the proposed heuristic algorithm and the implemented production scheduling system are currently working in the transformer production factory of the ‘H’ company.