• Journal of Korean Institute of Industrial Engineers
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• v.24 no.3
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• pp.345-357
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• 1998

This paper focuses on production planning and scheduling problems in an assembly system operating on a make-to-order basis. Due dates are considered as constraints in the problems, that is, tardiness is not allowed. Since the planning problem is a higher-level decision making than the scheduling problem, the scheduling problem is solved using a production plan obtained by solving the planning problem. We suggest heuristic procedures in which aggregated information is used when the production planning problem is solved while more detailed information is used when the scheduling problem is solved. Since a feasible schedule may not be obtained from a production plan, an iterative approach is employed in the two procedures to obtain a solution that is feasible for both the production planning and scheduling problems. Computational tests on randomly generated test problems are done to show the performance of these algorithms, and results are reported.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.1
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• pp.15-39
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• 2009

Advanced planning and scheduling (APS) refers to a manufacturing management process by which raw materials and production capacity are optimally allocated to meet demand. APS is especially well-suited to environments where simpler planning methods cannot adequately address complex trade-offs between competing priorities. However, most scheduling problems of APS in the real world face both inevitable constraints such as due date, capability, transportation cost, set up cost and available resources. In this survey paper, we address three crucial issues in APS, including basic scheduling model, job-shop scheduling (JSP), assembly line balancing (ALB) model, and integrated scheduling models for manufacturing and logistics. Several evolutionary algorithms which adapt to the problems are surveyed and proposed; some test instances based on the practical problems demonstrate the effectiveness and efficiency of evolutionary approaches.

• Journal of the military operations research society of Korea
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• v.29 no.1
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• pp.112-119
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• 2003

The procedure and implementation of an simulation based production planning and scheduling system. Production planning and scheduling is important problem in manufacturing field. It is so important for delivery quality as well as productivity, too. In this paper, heuristic production planning and scheduling module for improving delivery quality and productivity will be discussed. Beginning with total demand and initial work in process, the algorithms for production scheduling and planning can efficiently generate a feasible production resources and capacity schedule results in high resource utilization, minimum number of the late orders and reduced labor variability. The algorithm is executed to achieve the best on time delivery performance. The developed heuristic algorithms in the module will be expected to provide the better delivery performance and productivity.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.1-8
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• 2021

This study proposes a systems engineering approach for the development of an advanced planning & scheduling (APS) system for a cosmetic case manufacturing factory. The APS system makes production plans and schedules based on the injection process, which consists of 27 plastic injection machines in parallel to control recommended inventory of products. The system uses machine operation/failure information and defective product/work-in-process tracking information to support intelligent scheduling. Furthermore, a genetic algorithm model is applied to handle the complexity of heuristic rules and machine/quality constraints in this process. As a result of the development, the recommended inventory compliance rate is improved by scheduling the 30-day production plan for 15 main products.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.78-86
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• 2015

Up-to-date business environment for manufacturers is very complex and rapidly changing. In other words, companies are facing a variety of changes, such as diversifying customer requirements, shortening product life cycles, and switching to small quantity batch production. In this situation, the companies are introducing the concept of JIT (just-in-time) to solve the problem of on-time production and on-time delivery for survival. Though many companies have introduced ERP (enterprise resource planning) systems and MRP (material requirement planning) systems, the performance of these systems seems to fall short of expectations. In this paper, the case study on introducing an APS (advanced planning and scheduling) system based on dispatching rules to a machining company and on finding a method to establish an efficient production schedule is presented. The case company has trouble creating an effective production plan and schedule, even though it is equipped with an MRP-based ERP system. The APS system is applied to CNC (computer numerical control) machines, which are key machines of the case company. The overall progress of this research is as follows. First, we collect and analyze the master data on individual products and processes of the case company in order to build a production scheduling model. Second, we perform a pre-allocation simulation based on dispatching rules in order to calculate the priority of each order. Third, we perform a set of production simulations applying the priority value in order to evaluate production lead time and tardiness of pre-defined dispatching rules. Finally, we select the optimal dispatching rule suitable for work situation of the case company. As a result, an improved production schedule leads to an increase in production and reduced production lead time.

• IE interfaces
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• v.20 no.3
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• pp.277-287
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• 2007

Semiconductor manufacturing is one of the most complex and capital-intensive processes composed of several hundreds of operations. In today’s competitive business environments, it is more important than ever before to manage manufacturing process effectively to achieve better performances in terms of customer satisfaction and productivity than those of competitors. So, many semiconductor manufacturing companies implement advanced planning and scheduling (APS) system as a management tool for the complex semiconductor manufacturing process. In this study, we explain roles of production planning and scheduling in semiconductor manufacturing and principal factors that make the production planning and scheduling more difficult. We describe the APS system implementation project at Korean semiconductor manufacturing company in terms of key issues with realistic samples.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.94-102
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• 2012

In this paper, an interactive planning and scheduling framework are proposed for optimising operations from pits to crushers in ore mining industry. Series of theoretical and practical operations research techniques are investigated to improve the overall efficiency of mining systems due to the facts that mining managers need to tackle optimisation problems within different horizons and with different levels of detail. Under this framework, mine design planning, mine production sequencing and mine transportation scheduling models are integrated and interacted within a whole optimisation system. The proposed integrated framework could be used by mining industry for reducing equipment costs, improving the production efficiency and maximising the net present value.

• Industrial Engineering and Management Systems
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• v.11 no.4
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• pp.310-330
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• 2012

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

• Korean Management Science Review
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• v.8 no.1
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• pp.51-70
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• 1991

This paper discusses planning and scheduling problems for efficient utilization of an FMS and presents an integrated decision support system for FMS production planning and scheduling problems. The decision support system, FMSDS(Flexible Manufacturing Systems Decision Support System), includes of data of handling module, part selection module, loading module, load adjusting module, scheduling module and simulation module etc. This paper includes the solution methodology of each subproblem. And an integrated interface scheme between the subproblems is presented. The interface scheme considers the relationships between the subproblems and generates solution using hierarchical and looping approaches. FMSDS is made up of six alternative models considering 3 loading objectives and 2 production order processing strategies. Performance comparisons among 6 alternatives and other decision support systems are shown using the non-terminating simulation techniques.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.36-45
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• 1993

This paper presents a model and a heuristic procedure to design production planning and transportation scheduling systems of critical items, components and products on the basis of material requirement planning concept and transportation planning model. These systems are stemmed from a multi-site multi-product production company in a international economic zone. An example is provided to validate the heuristic procedure developed.