• IE interfaces
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• v.22 no.1
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• pp.85-94
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• 2009

Nowadays, most of the major manufacturing companies prepare their manufacturing schedule using package based solutions. Even though the accuracy of the detail scheduling result is high at implementation, however, it is low during maintenance period. The main cause of low accuracy during maintenance period is due to difficulties in maintaining the accurate level of master data. In this paper, we propose to easily maintain setup time, which is one of the most important factors required in master data to achieve good scheduling result, after changing job. This paper is mainly focused on how to deduce the factors that influence the setup time in a roll-based manufacturing field with print operations. For this purpose, we employed rule based algorithm and applied for deciding setup time for the existing product items. Likewise, it can be applied to new items without any complex setup procedures, and, finally, it displays the result of the real setup-time and calculated setup-time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.306-309
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• 1996

The job shop scheduling problem has been a major target for many researchers. And, most of the past studies did not consider setup time. In many cases of real manufacturing environment, however, there exists a setup time for each operations. The setup can be divide into two parts, one can be done after job arrival. The setup time based on the latter can be summed together with processing time, but that based on the former can not be. We propose an approximation method based on shifting bottleneck procedure for solving the job shop scheduling problem with sequence independent setup time. It schedules the machines one by one, taking a bottleneck machine among the machines not yet scheduled. Every time after a new machine is scheduled, all schedules previously established are updated. Both the bottlenck search and the schedule updating procedure are based on solving a single machine scheduling problem with ready time, setup time and delivery time iteratively.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.797-802
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• 2000

Flow shop scheduling problem involves processing several jobs on common facilities where a setup time Is incurred whenever there is a switch of jobs. Practical aspect of scheduling focuses on finding a near-optimum solution within a feasible time rather than striving for a global optimum. In this paper, a hybrid meta-heuristic method called tabu-genetic algorithm(TGA) is suggested, which combines the genetic algorithm(GA) with tabu list. The experiment shows that the proposed TGA can reach the optimum solution with higher probability than GA or SA(Simulated Annealing) in less time than TS(Tabu Search). It also shows that consideration of setup time becomes more important as the ratio of setup time to processing time increases.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.32
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• pp.121-126
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• 1994

Setup Time Reduction is an important aspect of the Just-in-Time(JIT) and Zero Inventory(Zl) Concepts since it supports reductions in manufacturing lead times and inventories. It also enables small lot sizes and kanban systems implementation for material flow - achieving major improvements in production floor management. One concept fundamental to the pursuit of JIT production in Japan and other countries is adoption of a setup time reduction. This paper looks at the necessities of setup time reduction and the relations to machine utilization. By using an EOQ model for evaluate the effect of setup time reduction, we get the results that over 75 % reduction in setup time is obtain the desired results in the lot size reduction.

• 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.

• Management Science and Financial Engineering
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• v.15 no.2
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• pp.1-21
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• 2009

We consider an $M^x/G/1$ queueing system with a random setup time under Bernoulli vacation schedule, where the service of the first unit at the completion of each busy period or a vacation period is preceded by a random setup time, on completion of which service starts. However, after each service completion, the server may take a vacation with probability p or remain in the system to provide next service, if any, with probability (1-p). This generalizes both the $M^x/G/1$ queueing system with a random setup time as well as the Bernoulli vacation model. We carryout an extensive analysis for the queue size distributions at various epochs. Further, attempts have been made to unify the results of related batch arrival vacation models.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.74-83
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• 2011

In this paper, we consider a new lot-sizing and scheduling problem (LSSP) that minimizes the sum of production cost, setup cost and inventory cost. Setup carry-over, setup overlapping, state dependent setup time as well as demand splitting are considered. For this LSSP, we develop a mixed integer programming (MIP) model, of which the size does not increase even if we divide a time period into a number of micro time periods. Also, we develop an efficient heuristic algorithm by combining a decomposition scheme with a local search procedure. Test results show that the developed heuristic algorithm finds a good quality (in practice, even better) feasible solution using far less computation time compared with the CPLEX, a competitive MIP solver.

• Korean Management Science Review
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• v.12 no.2
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• pp.77-87
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• 1995

In this paper we develop an efficient heuristic algorithm for the problem of scheduling n sequence-dependent jobs on a basic processor to minimize makespan. Efficient solution methods are already known for the sequence- independent case. But for the sequence-dependent case, this problem belongs to a set of strong NP-complete problems. We present a heuristic which is similar to shortest setup time heuristic but opportunity cost of setup time rather than shortest setup time is used for choosing next job. This heuristic algorithm has same computational complexity and worst case ratio as the shortest setup time heuristic. We used Wilcoxon signed rank test to show that our heuristic is superior to nearest setup time heuristic in term of average behavior.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.91-100
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• 1990

This paper is concerned with the development of optimal algorithms for multi-stage flowshop scheduling problems with sequence dependent setup times. In the previous researches the setup time of a job is considered to be able to begin at the earliest opportunity given a particular sequence at the start of operations. In this paper the setup time of a job is considered to be able to begin only at the completion of that job on the previous machine to reflect the effects of the setup time to the performance measure of sequence dependent setup time flowshop scheduling. The results of the study consist of two areas; first, a general integer programming(IP) model is formulated and a nixed integer linear programming(MILP) model is also formulated by introducing a new binary variable. Second a depth-first branch and bound algorithm is developed. To reduce the computational burdens we use the best heuristic schedule developed by Choi(1989) as the first trial. The experiments for developed algorithm are designed for a 4$\times$3$\times$3 factorial design with 360 observations. The experimental factors are PS(ratio of processing time to setup time), M(number of machines), N(number of jobs).

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.53-60
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• 2007

We consider the discrete-time $Geo^x/G/1$ queues under N-policy with multiple vacations (a single vacation) and setup time. In this queueing system, the server takes multiple vacations (a single vacation) whenever the system becomes empty, and he begins to serve the customers after setup time only if the queue length is at least a predetermined threshold value N. Using the heuristic approach, we derive the mean waiting time for both vacation models. We demonstrate that the heuristic approach is also useful for the discrete-time queues.