• 대한안전경영과학회지
• /
• 제12권3호
• /
• pp.177-182
• /
• 2010

Industrial business environments have rapidly changed and face severe competitive challenges. The effective inventory system enables to product and deliver the products quickly for meeting due date of customer's order in this environment. This study have developed a web-based inventory system using RFID for an injection molding industry. The system analysis inventory problem issues such as inventory planning, warehouse assignment and assist to develop production scheduling. In this study, web-based inventory system using Java language and RFID technology is proposed and implemented. As the result of implementation of the system, we expected that it manages to inventory planning continually and systematically.

• 반도체디스플레이기술학회지
• /
• 제10권1호
• /
• pp.101-105
• /
• 2011

In case of high-tech process industries such as semiconductor and TFT-LCD manufactures, fault of a virtually finished product that is value-added one, since it has gone throughout the most of processes, may give rise to quality cost nearly amount to its selling price and can be a main cause that decreases the efficiency of manufacturing process. This paper proposes a real-time dispatching algorithm for semiconductor manufacturing process with rework. In order to evaluate the proposed algorithm, this paper examines the performance of the proposed method by comparing it with that of the existing dispatching algorithms, based on various experimental data.

• 전기학회논문지
• /
• 제61권9호
• /
• pp.1330-1335
• /
• 2012

This paper proposes an automatic measurement sampling method for the semiconductor manufacturing process. The method recommends sampling rates using information of process capability indexes and production scheduling plan within the restricted metrology capacity. In addition, it automatically controls the measurement WIP (Work In Process) using measurement priority values to minimize the measurement risks and optimize the measurement capacity. The proposed sampling method minimizes measurement controls in the semiconductor manufacturing process and improves the fabrication productivity via reducing measurement TAT (Turn Around Time), while guaranteeing the level of process quality.

• 대한산업공학회지
• /
• 제22권4호
• /
• pp.619-631
• /
• 1996

This paper describes an approach for the incorporation of maintenance times into a hierarchical scheduling for a failure prone flexible manufacturing system. The maintenance should not be performed too often because of the resulting reduction of capacity. Most manufacturing systems are large and complex. It is natural to divide the control into a hierarchy consisting of a number of different levels. Each level is characterized by the length of the planning horizon and the kind of data required for the decision making process. The goal of the analysis reported here is to calculate the production requirements while the machines fail and are repaired at random times. The machine failure and preventive maintenance are considered simultaneously.

• 한국항해학회지
• /
• 제23권4호
• /
• pp.63-76
• /
• 1999

This paper aims at developing an integrated fleet management support system for industrial carriers who usually control the vessels of their own or on a time charter to minimize the cost of shipping their cargoes. The work is mainly concerned with the operational management problem of the fleet owned by a major oil company, a typical industrial carrier. The optimal fleet management problem for the major oil company can be divided into two phase problem. The front end corresponds to the production operation problem of the transportation of crude oil, the refinery operation, and the distribution of product oil to comply with the demand of the market. The back end is to tackle the fleet scheduling problem to meet the seaborne transportation demand derived from the front end. Relevant optimization models for each phase are proposed and described briefly. Then a user-friendly integrated fleet management support system is built based on the proposed optimization models for both ends under Windows environment. A case study reflecting the practices of fleet management problem for the major oil company is carried out by using the system.

• 산업공학
• /
• 제13권2호
• /
• pp.246-252
• /
• 2000

As moulds and dies are manufactured through complex processes under the make-to-order production environment, it is very difficult that the manufacturing activities as like observance of the due date, trace of the progress, etc are controlled with a real time. In this paper, a schedule-planning system using the commercial software Microsoft Project 98 is developed to control the procedures of mould and die manufacturing with real time. Once an initial schedule is planned from the BOM information in the intranet, it is rescheduled by data collected from machines on the shop floor. The system is suitable to medium- or small-sized manufacturing companies as well as large-sized ones, because it can be installed with a low cost.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 심포지엄 논문집 정보 및 제어부문
• /
• pp.98-101
• /
• 2004

Linear Programming(LP) is the term used for defining a wide range of optimization problems in which the objective function to be minimized or maximized is linear in the unknown variables and the constraints are a combination of linear equalities and inequalities. LP problems occur in many real-life economic situations where profits are to be maximized or costs minimized with constraint limits on resources. While the simplex method introduced in a later reference can be used for hand solution of LP problems, computer use becomes necessary even for a small number of variables. Problems involving diet decisions, transportation, production and manufacturing, product mix, engineering limit analysis in design, airline scheduling, and so on are solved using computers. This technique is called Sequential Linear Programming (SLP). This paper describes LP's problems and solves a LP's problems using the neural networks.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
• /
• pp.449-455
• /
• 2002

This paper considers that advanced planning and scheduling (APS) in manufacturing and the efficient purchasing where each customer order has its due date and multi-suppliers exit We present a Make-To­Order Supply Chan (MTOSC) model of efficient purchasing process from multi-suppliers and APS with outsourcing in a supply chain, which requires the absolute due date and minimized total cost. Our research has included two states. One is for efficient purchasing from suppliers: (a) selection of suppliers for required parts; (b) optimum part lead­time of selected suppliers. Supplier selection process has received considerable attention in the business­management literature. Determining suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decisions usually is complex and unstructured. These influence factors can be divided into quantitative and qualitative factors. In the first level, linguistic values are used to assess the ratings for the qualitative factors such as profitability, relationship closeness and quality. In the second level a MTOSC model determines the solutions (supplier selection and order quantity) by considering quantitative factors such as part unit price, supplier's lead-time, and storage cost, etc. The other is for APS: (a) selection of the best machine for each operation; (b) deciding sequence of operations; (c) picking out the operations to be outsourcing; and (d) minimizing makespan under the due date of each customer's order. To solve the model, a genetic algorithm (GA)-based heuristic approach is developed. From the numerical experiments, GA­based approach could efficiently solve the proposed model, and show the best process plan and schedule for all customers' orders.

• 산업경영시스템학회지
• /
• 제38권3호
• /
• pp.100-107
• /
• 2015

Recently as the manufacturers want competitiveness in dynamically changing environment, they are trying a lot of efforts to be efficient with their production systems, which may be achieved by diminishing unplanned operation stops. The operation stops and maintenance cost are known to be significantly decreased by adopting proper maintenance strategy. Therefore, the manufacturers were more getting interested in scheduling of exact maintenance scheduling to keep smooth operation and prevent unexpected stops. In this paper, we proposedan integrated maintenance approach in injection molding manufacturing line. It consists of predictive and preventive maintenance approach. The predictive maintenance uses the statistical process control technique with the real-time data and the preventive maintenance is based on the checking period of machine components or equipment. For the predictive maintenance approach, firstly, we identified components or equipment that are required maintenance, and then machine parameters that are related with the identified components or equipment. Second, we performed regression analysis to select the machine parameters that affect the quality of the manufactured products and are significant to the quality of the products. By this analysis, we can exclude the insignificant parameters from monitoring parameters and focus on the significant parameters. Third, we developed the statistical prediction models for the selected machine parameters. Current models include regression, exponential smoothing and so on. We used these models to decide abnormal patternand to schedule maintenance. Finally, for other components or equipment which is not covered by predictive approach, we adoptedpreventive maintenance approach. To show feasibility we developed an integrated maintenance support system in LabView Watchdog Agent and SQL Server environment and validated our proposed methodology with experimental data.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제31권2호
• /
• pp.164-172
• /
• 2004

일반적으로 국지적 탐색에서 최적해를 획득할 가능성은 가능한 많은 이웃해를 생성하면서 반복 수를 늘릴수록 높아지나 긴 탐색시간이 소요된다. 따라서 한정된 시간 내에 최적해를 효율적으로 찾기 위해서는. 적절한 수의 이웃해를 생성하되, 탐색의 질을 높일 수 있는 이웃해를 선별해서 생성하는 것이 요구된다. 본 논문에서는 국지적 탐색기법을 적용하여 부하평준화 문제를 해결할 때, 탐색의 효율을 향상시킬 수 있는 이웃해 선정 기법을 제안하고, 실세계 데이타를 대상으로 그 성능을 검증하였다. 본 논문에서 제안하는 이웃해 선정 기법은 확률적 선별에 기반 한 방법으로서, 탐색의 질을 개선시킬 가능성에 대한 추정치를 기준으로 부여된 확률에 따라 이웃해를 선별하여 생성하는 기법이다. 대상 문제에 국지적 탐색기법으로 tabu 탐색과 simulated annealing를 적용한 실험에서, 무작위 또는 그리디 선별에 기반 한 방법보다 우수한 성능을 보임을 확인하였다.