• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.844-847
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• 1997

In this paper, scheduling problem is dealt for the minimization of due date penalty for the customer order. Multiproduct batch processes have been dealt with for their suitability for high value added low volume products. Their scheduling problems take minimization of process operation for objective function, which is not enough to meet the customer satisfaction and the process efficiency simultaneously because of increasing requirement of fast adaptation for rapid changing market condition. So new target function has been suggested by other researches to meet two goals. Penalty function minimization is one of them. To present more precisely production scheduling, we develop new scheduling model with penalty function of earliness and tardiness We can find many real cases that penalty parameters are divergent by the difference between the completion time of operation and due date. That is to say, the penalty parameter values for the product change by the customer demand condition. If the order charges different value for due date, we can solve it with the due date period. The period means the time scope where penalty parameter value is 0. If we make use of the due date period, the optimal sequence of our model is not always same with that of fixed due date point. And if every product have due date period, due date of them are overlapped which needs optimization for the maximum profit and minimum penalty. Due date period extension can be enlarged to makespan minimization if every product has the same abundant due date period and same penalty parameter. We solve this new scheduling model by simulated annealing method. We also develop the program, which can calculate the optimal sequence and display the Gantt chart showing the unit progress and time allocation only with processing data.

• Industrial Engineering and Management Systems
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• v.2 no.1
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• pp.9-27
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• 2003

In a wafer fabrication factory, the completion time of an order is affected by many factors related to the specifics of the order and the status of the system, so is difficult to predict precisely. The level of influence of each factor on the order completion time may also depend on the production system characteristics, such as the rules for releasing and dispatching. This paper presents a method to identify those factors that significantly impact upon the order completion time under various combinations of scheduling rules. Computer simulations and statistical analyses were used to develop effective due date assignment models for improving the due date related performances. The first step of this research was to select the releasing and dispatching rules from those that were cited so frequently in related wafer fabrication factory researches. Simulation and statistical analyses were combined to identify the critical factors for predicting order completion time under various combinations of scheduling rules. In each combination of scheduling rules, two efficient due date assignment models were established by using the regression method for accurately predicting the order due date. Two due date assignment models, called the significant factor prediction model (SFM) and the key factor prediction model (KFM), are proposed to empirically compare the due date assignment rules widely used in practice. The simulation results indicate that SFM and KFM are superior to the other due date assignment rules. The releasing rule, dispatching rule and due date assignment rule have significant impacts on the due date related performances, with larger improvements coming from due date assignment and dispatching rules than from releasing rules.

• Proceedings of the Safety Management and Science Conference
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• 2004.05a
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• pp.299-302
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• 2004

Today, several manufacture enterprises are endeavoring constantly to receive order winners of subsidiary company product. There are tendencies to occupy competitive advantage in high position in price competition and in quality etc. But, it is not easy to keep it even if price has been cheap recently. Also, it is hard to be competitive advantage element more, because production smoothing was made much even if there is in quality. To keep or improve present competitive power, the due date rate is becoming importance. Several techniques with MRP, MRP II appeared in the 1970s by method to improve the these due date rate. These techniques have some defects to due date. Therefore, in this paper, MRP wishes to receive the due date rate that is improved more by supplementing having these defect by DBR of TOC.

• Korean Management Science Review
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• v.13 no.2
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• pp.147-161
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• 1996

Due-date is an important factor in Flexible Manufacturing System scheduling. Even though most of researchers have focused part selection and loading problem using fixed due-date assignment rules, FMSs consist of multi-function machines which facilitate alternative processes. This research investigates interactions of three dispatching mechanisms, three NSS (Next Station Selection) rules and four due-date assignment rules using simulation. Both cost-based and time-based performance measures are considered in this research.

• IE interfaces
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• v.11 no.3
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• pp.1-13
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• 1998

This paper addresses a scheduling scheme for Flexible Flow Shop(FFS) in the case that a factory is a sub-plant of an electronic device manufacturing plant. Under this environment, job orders for the sub-plants in the production route are generated together with job processing time bucket when the customer places orders for final product. The processing time bucket for each job is a duration from possible release date to permissible due date. A sub-plant modeled FFS should schedule these jobs orders within time bucket. Viewing a Printed Circuit Board(PCB) assembly line as a FFS, the developed scheme schedules an incoming order along with the orders already placed on the scheduled. The scheme consists of the four steps, 1)assigning operation release date and due date to each work cells in the FFS, 2)job grouping, 3)dispatching and 4)machine allocation. Since the FFS scheduling problem is NP-complete, the logics used are heuristic. Using a real case, we tested the scheme and compared it with the John's algorithm and other dispatching rules.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.4
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• pp.415-424
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• 2002

Semiconductor manufacturing has been emerged as a highly competitive but profitable business. Accordingly it becomes very important for semiconductor manufacturing companies to meet customer demands at the right time, in order to keep the leading edge in the world market. However, due-date oriented production is very difficult task because of the complex job flows with highly resource conflicts in fabrication shop called FAB. Due to its cyclic manufacturing feature of products, to be completed, a semiconductor product is processed repeatedly as many times as the number of the product manufacturing cycles in FAB, and FAB processes of individual manufacturing cycles are composed with similar but not identical unit processes. In this paper, we propose a production scheduling and control scheme that is designed specifically for semiconductor scheduling environment (FAB). The proposed scheme consists of three modules: simulation module, cycle due-date estimation module, and dispatching module. The fundamental idea of the scheduler is to introduce the due-date for each cycle of job, with which the complex job flows in FAB can be controlled through a simple scheduling rule such as the minimum slack rule, such that the customer due-dates are maximally satisfied. Through detailed simulation, the performance of a cycle due-date based scheduler has been verified.

• Management Science and Financial Engineering
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• v.19 no.1
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• pp.29-36
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• 2013

This paper considers common due-date assignment and scheduling on parallel machines. The main decisions are: (a) deter-mining the common due-date; (b) allocating jobs to machines; and (c) sequencing the jobs assigned to each machine. The objective is to minimize the sum of the penalties associated with common due-date assignment, earliness and tardiness. As an extension of the existing studies on the problem, we consider sequence-dependent setup times that depend on the type of job just completed and on the job to be processed. The sequence-dependent setups, commonly found in various manufacturing systems, make the problem much more complicated. To represent the problem more clearly, a mixed integer programming model is suggested, and due to the complexity of the problem, two heuristics, one with individual sequence-dependent setup times and the other with aggregated sequence-dependent setup times, are suggested after analyzing the characteristics of the problem. Computational experiments were done on a number of test instances and the results are reported.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.435-439
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• 2001

In many make-to-order production systems customers ask due date confirmed and kept. Unexpected urgent orders from valuable customers often requires short lead times, which causes existing orders in the production schedule to be delayed so that their confirmed due dates cannot be met. This Imposes significant uncertainty on the production schedule in a supply chain. In this paper, we propose a new concept of capacity reservation as a viable tool for due date promising and suggest its operational alternatives. Simulation results show that the reserved capacity scheme appears to outperform simple FCFS scheduling policy in terms of the number of valuable urgent orders accepted and total profit attained.

• IE interfaces
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• v.14 no.4
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• pp.341-347
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• 2001

This paper describes a real-time manufacturing scheduling system on Internet using DBR(Drum-Buffer-Rope) scheduling method. We intend to change company-oriented manufacturing scheduling, which has been used at most manufacturing companies, to customer-oriented manufacturing scheduling. Customers can not only choose product kinds, quantities and order due dates, but also evaluate optimum order due date by themselves in real-time through internet and then the results will be converted into practical manufacturing scheduling. If the company cannot meet the customer order due date, it will offer reliable and accurate information to the customers by suggesting the earliest order due date. To evaluate the customer order due date in real time, companies should be able to estimate their accurate production capacity. This research uses Goldratt's DBR scheduling method to realize that function. The DBR scheduling does not recognize the production capacity of the whole company, but only of the constraint resources which have a great effect on the company throughput. Thus, it can improve the customer service level as well as the profit by performing more dynamic and reliable scheduling through Internet.

• Management Science and Financial Engineering
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• v.18 no.1
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• pp.1-12
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• 2012

In this paper, we report a case study on the common due-date assignment and scheduling problem in a paper remanufacturing system that produces corrugated cardboards using collected waste papers for a given set of orders under the make-to-order (MTO) environment. Since the system produces corrugated cardboards in an integrated process and has sequence-dependent setups, the problem considered here can be regarded as common due-date assignment and sequencing on a single machine with sequence-dependent setup times. The objective is to minimize the sum of the penalties associated with due-date assignment, earliness, and tardiness. In the study, the earliness and tardiness penalties were obtained from inventory holding and backorder costs, respectively. To solve the problem, we adopted two types of algorithms: (a) branch and bound algorithm that gives the optimal solutions; and (b) heuristic algorithms. Computational experiments were done on the data generated from the case and the results show that both types of algorithms work well for the case data. In particular, the branch and bound algorithm gave the optimal solutions quickly. However, it is recommended to use the heuristic algorithms for large-sized instances, especially when the solution time is very critical.