• Management Science and Financial Engineering
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• v.9 no.2
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• pp.47-68
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• 2003

We consider the customer order scheduling problem with job capacity restriction where the number of jobs in the shop at the same time is fixed. In the customer order scheduling problem, each job is part of some batch (customer order) and the composition of the jobs (product) in the batch is pre-specified. The objective function is associated with the completion time of the batches instead of the completion time of the jobs. We first summarize the known results for the general customer order scheduling problems. Then, we establish some new properties for the problems with job capacity restriction. For the case of unit processing time with the objective of minimizing makespan, we develop a polynomial-time optimal procedure for the two machine case. For the same problem with a variation of no batch alternation, we also develop a polynomial-time optimal procedure. Then, we show that the problems with the objectives of minimizing makespan and minimizing average batch completion time become NP-hard when there exist arbitrary number of machines. Finally, We propose optimal solution procedures for some special cases.

• International Journal of Reliability and Applications
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• v.4 no.1
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• pp.13-26
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• 2003

This paper presents a comparative study of a few commonly used maintenance scheduling methods for small utilities that consists solely of thermal generating plants. Two deterministic methods and a stochastic method are examined. The deterministic methods employ the leveling of reserve capacity criterion, of which one uses a heuristic rule to level the deterministic equivalent load obtained by using the product of the unit capacity and its corresponding forced outage rate. The stochastic method simulates the leveling of risk criterion by using the peak load carry capacity of available units. The results indicate that for the size and type of the maintenance scheduling problem described In this study, the stochastic method does not produce a schedule which is significantly better than the deterministic methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.110-117
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• 2009

This paper introduces a case study for efficient generation of production schedules in a tube manufacturing system. The considered scheduling problem consists of two sub problems : lot sizing for a job and Job sequencing. Since these problems require simulation optimization in which the performance measures are obtained by simulation execution, the trade-off between solution quality and computation time is an important issue. In this study, the optimal lot size for every product type is determined from simulation experiments. Then, target production quantity for each product type is transformed to several jobs such that a Job consists of determined lot size. To obtain the good solution for a Job sequence in a reasonable time, a number of alternatives are generated from heuristic rules developed by intuition and analysis of the considered system, and a job sequence is selected from simulation experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.163.3-163
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• 2001

This paper presents the two-step strategy method of performing optimal scheduling of paper mill processes using MINLP (Mixed-Integer Non-Linear Programming) considering the trim loss problem in sheet cutting processes. The mathematical model for a sheet cutting process in the form of MINLP is developed in this study, and minimizing total cost is performed considering the cost of raw paper roll, :hanging cutting patterns, storage of over-product and recycling/burning trim. The paper has been used to deliver and conserve information for a long time, and it is needed to have various sizes and weights ...

• Proceedings of the Safety Management and Science Conference
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• 2003.05a
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• pp.285-290
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• 2003

There is only one server available and arriving work require services from this server. Job are processed by the machine one at a time. The most common objective is to sequence jobs on the severs so as to minimize the penalty for being late, commonly called tardiness penalty Based on other objectives, many criteria may serve as s basis for developing job schedules. Therefore, this study tries to proposed that Scheduling by customer needs group for minimizing the problem and reducing inventory, product development time, cycle time, and order lead time.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1826-1829
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• 2003

Fine chemical production must assure high-standard product quality as well as characterized as multi-product production in small volumes. Installing high-precision batch distillation is one of the common elements in the successful manufacturing of fine chemicals, and the importance of the process operation strategy with quality assurance cannot be overemphasized. In this study, we investigate the optimal operation strategy and production planning of a sequential multi-purpose plants consisting of batch processes and batch distillation with unlimited intermediate storage. We formulated this problem as an MILP model. A mixed-integer linear programming model is developed based on the time slot, which is used to determine the production sequence and the production path of each batch. Illustrative examples show the effectiveness of the approach.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.369-374
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• 2003

Disassembly scheduling is the problem or determining the ordering and disassembly schedules or used or end-of-life products while satisfying the demand or their parts or components over a certain planning horizon. To represent and optimally solve the basic case. i e ., single product type without parts commonality, an Integer programming model is suggested for the objective or minimizing the sum or purchase, setup, inventory holding, and disassembly operation costs. Then, the basic model is offended to consider the cases or single and multiple product types with parts commonality. Computational experiments done on the examples obtained from the literature show that the integer programming approach suggested in this paper works well.

• IE interfaces
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• v.14 no.4
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• pp.348-355
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• 2001

This paper suggests a detailed design of APS(Advanced Planning & Scheduling) system using the DBR (Drum-Buffer-Rope) which is a finite capacity scheduling logic of TOC(Theory of Constraints). Our design is composed of four modules; Network, Buffer, Drum and Subordination. The Network module defines the Product Network which is built from BOM and routings. The Buffer module inserts the Buffers into the Product Network. The Drum module describes detail procedures to create Drum Schedule on the CCR(Capacity Constraint Resource). The Subordination module synchronizes all non-constraints to the constraints by determining the length of Rope. This design documented by ARIS.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.125-137
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• 2010

This study focuses on the problem of scheduling wafer lots of several product families in the deposition workstation in a semiconductor wafer fabrication facility. There are multiple identical parallel machines in the deposition workstation, and two types of setups, record-dependent setup and family setup, may be required at the deposition machines. A record-dependent setup is needed to find optimal operational conditions for a wafer lot on a machine, and a family setup is needed between processings of different families. We suggest two-phase heuristic algorithms in which a priority-rule-based scheduling algorithm is used to generate an initial schedule in the first phase and the schedule is improved in the second phase. Results of computational tests on randomly generated test problems show that the suggested algorithms outperform a scheduling method used in a real manufacturing system in terms of the sum of weighted flowtimes of the wafer lots.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.692-699
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• 2008

Semiconductor research and development(R&D) fabs are very different than production fabs in many ways such as the scales of production, job priority, production methods, and performance measures. Efficient operations of R&D fabs are very important to the development of new product, process stability, high yield, and ultimately company competitiveness. This paper proposes the fab-wide scheduling method for operational optimization of the R&D fabs. Most scheduling systems of semiconductor fabs have only focused on maximizing throughput of each separated areas without considering WIP(works in process) flows of entire fab. In this paper, we proposes the a fab-wide scheduling system which schedules all lots to entire fab equipment at once. We develop the MIP(mixed integer programing) model which allocates the lots to production equipment considering many constraints of all processes and the CP(constraint programming) model which determines the sequences of the lots in the production equipment. The proposed FAB-wide scheduling model is applied to the newly constructed R&D fab. As a result, we have accomplished the system based automated job reservation, decrease of the hot lot delay, increase of the queue time satisfaction, the high throughput by maximizing the batch sizes, decrease of the WIP TAT(Turn Around Time).