• Journal of the Korea Society for Simulation
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• v.19 no.3
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• pp.45-54
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• 2010

The inherent complexity of semiconductor fabrication processes makes it hard to solve well-known job scheduling problems in analytical ways, which leads us to rely practically on discrete event modeling simulations to learn the effects of changing the system's parameters. Meanwhile, unpredictable disturbances such as machine failures and maintenance diminish the productivity of semiconductor manufacturing processes with fixed scheduling policies; thus, it is necessary to adapt job scheduling policy in a timely manner in reaction to critical environmental changes (disturbances) in order for the fabrication process to perform optimally. This paper proposes an adaptive job control framework for a wafer fabrication process in a control system theoretical approach and implements it based on a DEVS modeling simulation environment. The proposed framework has the advantages in view of the whole systems understanding and flexibility of applying new rules compared to most ad-hoc software approaches in this field. Furthermore, it is flexible enough to incorporate new job scheduling rules into the existing rule set. Experimental results show that this control framework with adaptive rescheduling outperforms fixed job scheduling algorithms.

• ETRI Journal
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• v.27 no.5
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• pp.533-538
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• 2005

We developed a pipelined scheduling technique of functional hardware and software modules for platform-based system-on-a-chip (SoC) designs. It is based on a modified list scheduling algorithm. We used the pipelined scheduling technique for a performance analysis of an MPEG4 video encoder application. Then, we applied it for architecture exploration to achieve a better performance. In our experiments, the modified SoC platform with 6 pipelines for the 32-bit dual layer architecture shows a 118% improvement in performance compared to the given basic SoC platform with 4 pipelines for the 16-bit single-layer architecture.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.130-137
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• 2013

In this paper, we consider a two-agent scheduling with sequence-dependent exponential learning effects consideration, where two agents A and B have to share a single machine for processing their jobs. The objective function for agent A is to minimize the total completion time of jobs for agent A subject to a given upper bound on the objective function of agent B, representing the makespan of jobs for agent B. By assuming that the learning ratios for all jobs are the same, we suggest an enumeration-based backward allocation scheduling for finding an optimal solution and exemplify it by using a small numerical example. This problem has various applications in production systems as well as in operations management.

• Journal of the Society of Naval Architects of Korea
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• v.44 no.1 s.151
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• pp.48-54
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• 2007

Higher productivity and less cost during the manufacturing process of ships are required to maintain international competitiveness of modern shipbuilding industries. The integrated hull/ outfitting/ painting scheduling(IHOP) process is a final point, where logistics are finally being integrated and upcoming schedules are made. Therefore, more profits are expected from IHOP by effective management. In this thesis, IHOP is proposed in order to solve how to choose block erection date with IHOP scheduling logic. The result of IHOP scheduling is highly advised to utilize fabrication, outfitting shops. A standardized operation and load of resource will eventually be applied in long-term time span point of view for this will make it easy to enable capacity planning and workforce planning. It is also expected to eliminate inefficiency in overtime work and efficiently utilize manpower in short-term.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.1-9
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• 2010

In this paper, we consider a two-machine re-entrant permutation flowshop scheduling problem with the objective of minimizing total flowtime, and suggest branch and bound algorithms for the scheduling problem. In this scheduling problem, each job must be processed twice on each machine, that is, each job should be processed on the two machines in the order of machine 1, machine 2 and then machine 1 and machine 2. In this research, based on the results of existing researches for re-entrant permutation flowshop scheduling problems, various dominance properties, lower bound and heuristic algorithm are suggested for the problem, and those are used to develop branch and bound algorithms. In the computational experiments for evaluation of the performance of the algorithms, the suggested branch and bound algorithms are tested on randomly generated test problems and results are reported.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.4
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• pp.373-381
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• 2006

This paper considers a scheduling problem for a hybrid flowshop with dynamic order arrival. A hybrid flowshop is an extended form of a flowshop, which has serial stages like a flowshop but there can be more than one machine at each stage. In this paper, we propose a new method for the problem of scheduling with the objective of minimizing mean tardiness of orders which arrive at the shop dynamically. The proposed method is based on the list scheduling approach, however we use a more sophisticated method to prioritize lots unlike dispatching rule-based methods. To evaluate the performance of the proposed method, a simulation model of a hybrid flowshop-type production system is constructed. We implement well-known dispatching rules and the proposed methods in the simulation model. From a series of simulation tests, we show that the proposed methods perform better than other methods.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2060-2071
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• 2000

Scheduling parallel tasks, represented as a Directed Acyclic Graph (DAG) or task graph, on a multiprocessor system has been an important research area in the past decades. List scheduling algorithms assign priorities to a node or an edge in an input DAG, and then generate a schedule according to the assigned priorities. This appear proposes a list scheduling algorithms with effective method of priority assignments. The paper also analyzes the worst case performance and optimality condition for the proposed algorithm. The performance comparison study shows that the proposed algorithms outperforms existing scheduling algorithms especially for input DAGs with high communication overheads. The performance improvement over existing algorithms becomes larger as the input DAG becomes more dense and the level of parallelism in the DAG is increased.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.2
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• pp.130-145
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• 2004

This paper addresses the integrated problem of process planning and scheduling in FMS (Flexible Manufacturing System). The integration of process planning and scheduling is important for an efficient utilization of manufacturing resources. In this paper, a new method using an artificial intelligent search technique, called asymmetric multileveled symbiotic evolutionary algorithm, is presented to handle the two functions at the same time. Efficient genetic representations and operator schemes are considered. While designing the schemes, we take into account the features specific to each of process planning and scheduling problems. The performance of the proposed algorithm is compared with those of a traditional hierarchical approach and existing evolutionary algorithms. The experimental results show that the proposed algorithm outperforms the compared algorithms.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.2
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• pp.209-229
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• 1996

Scheduling problems which determine the sequence of jobs are one of the Important issues to many industries. This paper deals with a single-machine job sequencing problem which has complex constraints and an objective function. To solve the problem, an expressive constraint description language and an automatic code generator are developed for our scheduling system. The user just needs to describe the scheduling problem using the constraint description language that allows to express both quantitative and qualitative constraints as well as an objective function in real world semantics. Then, a complete scheduling program based on constraint satisfaction technique is automatically generated through the code generator. Advantage of this approach is that models of the scheduling problems are easily developed and maintained because models ore formulated by using the language which reflects real world semantics.

• Korean Management Science Review
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• v.29 no.2
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• pp.143-155
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• 2012

The purpose of this study is to formulate and solve the scheduling problem to heat-treatment process in forging process and apply it to industries. Heat-treatment is a common process in manufacturing heavy forged products in ship engines and wind power generators. Total complete time of the schedule depends on how to group parts and assign them into heat furnace. Efficient operation of heat-treatment process increases the productivity of whole production system while scheduling the parts into heat-treatment furnace is a combinatorial problem which is known as an NP-hard problem. So the scheduling, on manufacturing site, relies on engineers' experience. To improve heat-treatment process schedule, this study formulated it into an MIP mathematical model which minimizes total complete time. Three methods were applied to example problems and the results were compared to each other. In case of small problems, optimal solutions were easily found. In case of big problems, feasible solutions were found and that feasible solutions were very close to lower bound of the solutions. ILOG OPL Studio 5.5 was used in this study.