• Industrial Engineering and Management Systems
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• v.6 no.1
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• pp.83-93
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• 2007

This paper gives an attempt to build a decision support tool linked with a simulation software called ARENA for evaluating and comparing the performance of the push and pull material driven strategies operating in the flow shop environment with a bottleneck resource as the shop's constraint. To be fair for such evaluation, the comparison must be made fairly under the optimal setting of both systems' operating parameters. In this study, an optimal-seeking heuristic algorithm, Genetic Algorithm (GA), is employed to suggest a systems' best design based on the economic consideration, which is the profit generated from the system. Results from the study have revealed interesting outcomes, letting us know the strength and weakness of the push and pull mechanisms as well as the effect of each operating parameter to the overall system's financial performance.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2006.05a
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• pp.103-106
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• 2006

This study proposes a method of generating steel house shop drawing in an automated design method, reducing construction manpower and period. With one hour fire-resistant approval code, reflecting work ability and efficiency, steel-framed house market is expected to extend from one or two story house to multi-purpose facilities up to four story height. More models have been constructed in this system than the first appearance of fire-resistant approval in Korea in 1997. Also, cost estimation of components such as frame walls, roof trusses and floors is obtained with shop drawings. Also, the lack of suppliers of steel framed house shop drawing and unstandardized drawing method get constructors have difficulty in understanding its design. In steel framed house industry, shop drawings are essential part in building and constructing framework and they have major effects on construction deadlines and expenses. By exploring method of shop drawing automation, this study aims to optimize work flow with a standardized drawing method. The proposed system can be applied to manufacturing automation in domestic industry of factory-built panelizing method in the near future.

• Journal of the Korea Society for Simulation
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• v.22 no.3
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• pp.35-41
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• 2013

This paper applies an active period based bottleneck detection method to flow shop manufacturing system with limited buffer size. Manufacturing systems are constrained by one or more bottlenecks which degrades the system throughput. Conventional bottleneck detection methods include the waiting time or queue length of production stations and their utilization. Due to the random events such as production time of items, machine failure and repair times, the systems may change over time, and subsequently bottlenecks shift from one station to another station. Active period of working station may cause other stations to wait for productions. Information when and where active periods occur helps to find bottlenecks in production systems. Based on these informations, we predict bottlenecks in applying AweSim simulation language. We compare the simulation results of conventional methods with those obtained from duration of active period method, and duration ratio method of both sole and shift bottleneck periods. Even though simulation results are from simple flow shop model, they are quite promising for predicting bottlenecks of production stations. We hope this study aids in decision making regarding the improving system production yield and allocation of available resources of system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.138-141
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• 2006

This paper considers a two-machine flow-shop scheduling problem for minimizing mean flow time. Each job has three non-preemptive operations, where the first and third operations must be Processed on the first and second machines, respectively, but the second operation can be processed on either machine. A lower bound based on SPT rule is derived, which is then used to develop a branch-and-bound algorithm. Also, an efficient simple heuristic algorithm is developed to generate a near-optimal schedule. Numerical experiments are performed to evaluate the performances of the proposed branch-and-bound and the heuristic algorithm

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.306-316
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• 2013

The semiconductor industry has grown rapidly, and subsequently production planning problems have raised many important research issues. The reentrant flow-shop (RFS) scheduling problem with time windows constraint for harddisk devices (HDD) manufacturing is one such problem of the expanded semiconductor industry. The RFS scheduling problem with the objective of minimizing the makespan of jobs is considered. Meeting this objective is directly related to maximizing the system throughput which is the most important of HDD industry requirements. Moreover, most manufacturing systems have to handle the quality of semiconductor material. The time windows constraint in the manufacturing system must then be considered. In this paper, we propose a hybrid genetic algorithm (HGA) for improving chromosomes/offspring by checking and repairing time window constraint and improving offspring by left-shift routines as a local search algorithm to solve effectively the RFS scheduling problem with time windows constraint. Numerical experiments on several problems show that the proposed HGA approach has higher search capability to improve quality of solutions.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.4
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• pp.481-488
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• 2008

This paper deals with a scheduling problem for two-machine flow shop, in which the preceding machine is a batch processing machine that can process a number of jobs simultaneously. To minimize makespan of the system, we present a mixed integer linear programming formulation for the problem, and using this formulation, it is shown that an optimal solution for small problem can be obtained by a commercial optimization software. However, since the problem is NP-hard and the size of a real problem is very large, we propose a number of heuristic algorithms including genetic algorithm to solve practical big-sized problems in a reasonable computational time. To verify performances of the algorithms, we compare them with lower bound for the problem. From the results of these computational experiments, some of the heuristic algorithms show very good performances for the problem.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.235-245
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• 1998

This paper presents the fuzzy optimization model based scheduling methodology for the efficient production control of a FFS(FIexible Flow Shop) under the uncertain production environment. To develop the methodology, a fuzzy optimization technique is introduced in which the uncertain production capacity caused by the random events like the machine breakdowns or the absence of workers is modeled by fuzzy number. Since the problem is NP hard, the goal of this study is to obtain the near optimal but practical schedule in an efficient way. Thus, Lagrangian relaxation method is used to decompose the problem into a set of subproblems which are easier to solve than the original one. Also, to construct the feasible schedule, a heuristic algorithm was proposed. To evaluate the performance of the proposed method, computational experiments, based on the real factory data, are performed. Then, the results are compared with those of the other methods, the deterministic one and the existing one used in the factory, in the various performance indices. The comparison results demonstrate that the proposed method is more effective than the other methods.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.207-211
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• 2021

This paper addresses a two-stage flexible flow shop scheduling problem in which there is one machine in stage 1 and two identical machines in stage 2. The objective is the minimization of the total completion time. The problem is formulated by a mixed integer quadratic programming (MIQP) and a hybrid simulated annealing (HSA) is proposed to solve the MIQP. The HSA adopts the exploration capabilities of a genetic algorithm and incorporates a simulated annealing to reduce the premature convergence. Extensive computational tests on randomly generated problems are carried out to evaluate the performance of the HSA.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.719-739
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• 1996

A common control model used to implement computer integrated manufacturing(CIM) is based on the hierarchical decomposition of the shop floor activities, in which supervisory controllers are responsible for all the interactions among subordinates. Although the hierarchical control philosophy provides for easy understanding of complex systems, an emerging manufacturing paradigm, agile manufacturing, requires a new control structure necessary to accommodate the rapid development of a shop floor controller. This is what is called autonomous agent-based heterarchical control. As computing resources and communication network on the shop floor become increasingly intelligent and powerful, the new control architecture is about to come true in a modern CIM system. In this paper, heterarchical control is adopted and investigated, in which a controller for a unit of device performs three main functions - planning, scheduling and execution. Attention is paid to the planning function and all the detailed planning activities for heterarchical shop floor control are identified. Interactions with other functions are also addressed. In general, planning determines tasks to be scheduled in the future. In other words, planning analyzes process plans and transforms process plans into detailed plans adequate for shop floor control. Planning is also responsible for updating a process plan and identifying/resolving replanning activities whether they come from scheduling or execution.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.6
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• pp.118-126
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• 2003

Digital Manufacturing is a technology facilitating effective developments and agile productions of the product via digital computer models representing physical and logical schema and the behavior of the real manufacturing systems including manufacturing resources, environments and products. For the successful application of this technology, a digital factory as a well-designed and an integrated environment is essential. In this paper, we constructed the sophisticated digital factory of a Korean automotive company's body shop, and conducted precise simulations of unit cell, lines and the whole factory for the collision check, the production flow analysis and the off-line programming. We expect that this digital factory of the body shop helps us achieve great savings in time and cost for many manufacturing preparation activities of the new car development.