• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.1
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• pp.47-50
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• 2004

This paper deals with the problem of batching and scheduling of jobs whose processing times are different respectively But, they are given as not the exact value but the range from the lower limits to the upper, which makes it possible to group jobs into batches. The grouping of jobs is desirable because of the capability of the batch processor to accommodate several jobs at once. The time required to process the jobs in any batch depends on their lower limit processing times. Once processing is initiated on a batch processor, the batch cannot be interrupted, nor can other jobs be started. And all jobs are assumed to be simultaneously available. This paper develops the model to describe these situation and a heuristic method to minimize its total tardiness.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.1
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• pp.87-96
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• 2001

This paper considers the transfer batch scheduling problem for a two-machine flow shop with setup times consisting of attached setup time and separate setup time. The attached setup is attached to the processing and can be scheduled in anticipation of arriving work. Two cases of the separate setup are addressed. One is the case that the separate setup can be done only when a machine is idle. The other is the case that the separate setup can be done even though the machine is idle. the other is the case that the separate setup can be done even though the machine is operating. A scheduling rule similar to Johnson\`s rule is suggested to minimize makespan. the scheduling rule developed can be applied to most of the two-machine flow shop scheduling problems if some parameters are adjusted. A numerical example is presented to illustrate the scheduling rule.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.4
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• pp.105-114
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• 2003

This paper considers a single facility scheduling problem for the fabrication of components supporting the subsequent assembly into products. Each product consists of two types of components, one is common to all products and the other is unique to itself. The unique components are processed individually and the common components are processed in batches, and a distinct setup is incurred for the production of a batch of common components. Under the so-called “batch availability” environment, we propose an efficient dynamic programming(DP) procedure for the optimal sequencing and batching schedule with minimum total completion times of products in the situation that each product is said to be complete if both common and unique components of the product are finished. Computational results show that the proposed DB procedure is more efficient than the previous work which has considered the same problem as this paper.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.369-372
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• 1996

The factory under this study consists of mixed-model assembly lines and workcenters which provide parts to the main lines. Parts produced by the workcenter have different specifications for different product models. The workcenters fabricate parts in batches, and they are divided into two types. A type 1 center supplies parts only to the main line that is designated to the center while type 2 center provides parts to all the main lines. The purpose of this study is to develop a scheduling scheme for the workcenter, and the main objective of the schedules is to provide parts for the main lines without delay. The facts that make the scheduling challengeable are that 1) the different models existing together on a main line request different parts, 2) the spaces for part inventories are limited and 3) set up times are sequence dependent and long in some cases. This study presents developed scheduling schemes for the type 1 center and explains the scheduling and control structure used.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.1
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• pp.155-164
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• 1996

Biomass to methane via anaerobic digestion conversion is a good supply method of substitutable energy resources. The economic viability of this technology is contingent upon managing the production facilities in a cost effective manner. The problem is to determine the batch production sequence as well as the batch residence times in the digester so as to maximize total gas production over a given planning horizon. The problem is difficult to solve since the batch sequencing decisions and the batch residence time decisions cannot be isolated. This paper developes a heuristic algorithm which is based on a dynamic programming procedure for the multiple feedstock sequencing and scheduling biogas production systems and demonstrates to yield good results.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.2
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• pp.33-46
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• 2000

The problem of scheduling n independent jobs on serial stages with identical parallel machines at each stage is considered. Each job lot is allocated evenly to all machines at each stage for processing and moved in transfer batches between states., This scheduling strategy is called an identical production pattern. The objective is to find a permutation schedule that minimizes makespan. A branch and bound algorithm is suggested to find an optimal permutation schedule for a transformed problem A number examples is presented to illustrate the branch and bound algorithm, Computational results for 640 problems generated randomly show that within a resonable time the suggested algorithm can be used for transfer batch scheduling in a flexible flowshop.

• Management Science and Financial Engineering
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• v.11 no.2
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• pp.19-43
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• 2005

This paper considers a variation of the customer order scheduling problem, and the variation is the case where the machine-job assignment is fixed. We examine the parallel machine environment, and the objective is to minimize the sum of the completion times of the batches. While a machine can process only one job at a time, different machines can simultaneously process different jobs in a batch. The recognition version of this problem is known to be NP-complete in the strong sense even if there exist only two parallel machines. When there are an arbitrary number of parallel machines, we establish three lower bounds and develop a dynamic programming (DP) algorithm which runs in exponential time on the number of batches. We present two simple but intuitive heuristics, SB and GR, and find some special cases where SB and GR generate an optimal schedule. We also find worst case upper bounds on the relative error. For the case of the two parallel machines, we show that GR generates an optimal schedule when processing times of all batches are equal. Finally, the heuristics and the lower bounds are empirically evaluated.

• 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).

• Management Science and Financial Engineering
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• v.13 no.2
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• pp.47-77
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• 2007

This paper considers a scheduling problem where a customer orders multiple products(jobs) from a production facility. The objective is to minimize the sum of the order(batch) completion times. While a machine can process only one job at a time, multiple machines can simultaneously process jobs in a batch. Although each job has a unique processing time, we consider the case where batch processing times are identical. This simplification allows us to develop heuristics with improved performance bounds. This problem was motivated by a real world problem encountered by foreign electronics manufacturers. We first establish the complexity of the problem. For the two parallel machine case, we introduce two simple but intuitive heuristics, and find their worst case relative error bounds. One bound is tight and the other bound goes to 1 as the number of orders goes to infinity. However, neither heuristic is superior for all instances. We extend one of the heuristics to an arbitrary number of parallel machines. For a fixed number of parallel machines, we find a worst case bound which goes to 1 as the number of orders goes to infinity. Then, a tighter bound is found for the three parallel machine case. Finally, the heuristics are empirically evaluated.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.506-512
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• 2006

In this paper, we propose a lot-sizing and scheduling problem that seeks to minimize the sum of production cost and inventory cost over a given planning horizon while considering idle state of a machine in a batch production system. For this problem, we develop an integer programming model. And, we develop an efficient 2-phase heuristic algorithm to find a high quality feasible solution within reasonable time bounds. In the first phase, we seek to minimize the production cost by assigning batches to machines. Then, in the second phase, we find a production sequence of batches that reduces the inventory cost, while considering adding or deleting idle states between batches. Computational results show that the developed heuristic algorithm finds excellent feasible solutions within reasonable time bounds. Also, we could significantly reduce the total cost consisting of production cost and inventory cost by using the developed heuristic algorithm at a real manufacturing system that produces zinc alloys.