• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.184-191
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• 2010

In the environment of 450mm wafers production known as the next-generation semiconductor production process, one of the most significant features is the full automation over the whole manufacturing processes involved. The full automation system for 450mm wafer production will minimize the human workers' involvement in the manufacturing process as much as possible. In addition, since the importance of an individual wafer processing increases noticeably, it is necessary to develop more robust scheduling systems in the whole manufacturing process than so ever. The scheduling systems for the next-generation semiconductor production processes also should be capable of monitoring individual wafers and collecting useful data on them in real time. Based on the information gathered from these processes, the system should finally have a real-time scheduling functions controlling whole the semiconductor manufacturing processes. In this study, preliminary investigations on the requirements and needed functions for constructing the real time scheduling system and transforming manufacturing environments for 300mm wafers to those of 400mm are conducted and through which the next generation semiconductor processes for efficient scheduling in a clustered production system architecture of the scheduler is proposed. Our scheduling architecture is composed of the modules for real-time scheduling, the clustered production type supporting, the optimal scheduling and so on. The specifications of modules to define the major required functions, capabilities, and the relationship between them are presented.

• IE interfaces
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• v.19 no.3
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• pp.202-213
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• 2006

In this paper, we develop a planning system for the routing and scheduling of vehicles in pickup and delivery service such as door-to-door parcel service. Efficient routing and scheduling of vehicles is very important in pickup and delivery service. The routing and scheduling problem is a variation of vehicle routing problem which has various realistic constraints. We develop a heuristic algorithm based on tabu search to solve the routing and scheduling problem. We develop a routing and scheduling system installed the algorithm as a planning engine. The system manage the basic data and uses GIS data to make a realistic route plan.

• Journal of Industrial Technology
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• v.22 no.B
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• pp.61-70
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• 2002

The shipbuilding scheduling has many possible alternatives because of its long time horizon and a lot of jobs, so it is required that the scheduling system can generate and search feasible alternatives rapidly. The scheduling in the assembly shop is initiated by allocating, namely loading, the assembly blocks to each shop. In this step, the resource capacities (such as available man/hour, available crane) of each shop must be considered. The result of loading without above consideration can make the scheduling result based on that infeasible or worse one. In this paper, we developed the optimal scheduling system of shipbuilding, specifically for loading and scheduling of assembly block, using ILOG Solver/Scheduler. ILOG Solver/Scheduler is a general-purposed commercial software which supports to find a feasible or optimal solution using object oriented technique and constraints satisfaction programming, given constraints and objectives. Also, in order to enhance the system performance, we conducted various experiments of ILOG search strategies. The experimental results showed that the impact of search strategies is significant.

• Journal of Intelligence and Information Systems
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• v.1 no.2
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• pp.123-137
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• 1995

Most of solution methods in scheduling attempt to generate good solutions by either developing algorithms or heuristic rules. However, scheduling problems in the real world require considering more factors such as multiple objectives, different combinations of heuristic rules due to problem characteristics. In this respect, the traditional mathematical a, pp.oach showed limited performance so that new a, pp.oaches need to be developed. Expert system is one of them. When an expert system is developed for scheduling one of the most difficult processes faced could be knowledge acquisition on scheduling heuristics. In this paper we propose a method for the acquisition of knowledge on the selection of scheduling heuristics using Dempster-Shafer Theory(DST). We also show the examples in the multi-objectives environment.

• Journal of Industrial Convergence
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• v.1 no.2
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• pp.69-79
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• 2003

In order to solve scheduling, many techniques including optimization and heuristics methods have been proposed. However, these conventional approaches are usually inadequate to obtain a satisfactory solution because of a NP-Complete which requires extensive computation effort. The aim of this paper is to develop an expert system for job shop scheduling using an AI technique. Through this system, the user can choose one of several performances. If one performance is chosen, then the system solves a scheduling in order to satisfy that performance. Then, this system decides urgent job. This system can utilize production resources efficiently and minimize work-in-process inventories and tardy jobs.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.1
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• pp.14-23
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• 1996

Scheduling jobs effectively under consideration of actual loads on machines is one of the most complicated tasks in production control. The complexity of the finite capacity scheduling often makes the conventional methods of industrial engineering fail. As an alternative, Knowledge-based approaches to job-shop scheduling have been evolved recently. This paper presents a blackboard- based scheduling expert system which combines knowledge-based scheduling with interactive scheduling. It is shown to be possible to generate the feasible schedule within a reasonable time. Flexible reaction management is also possible while keeping the changes in the generated schedule to the minimal and adjusting the schedule to tardy operations or working environmental changes. The system is equipped with a rule base with heuristics for handling conflicted event. A case study applying the implemented system is described.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.91-100
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• 2005

Grid computing is widely applicable to various fields of industry including process control and manufacturing, military command and control, transportation management, and so on. In a viewpoint of application area, grid computing can be classified to three aspects that are computational grid, data grid and access grid. This paper focuses on computational grid which handles complex and large-scale computing problems. Computational grid is characterized by system dynamics which handles a variety of processors and jobs on continuous time. To solve problems of system complexity and reliability due to complex system dynamics, computational grid needs scheduling policies that allocate various jobs to proper processors and decide processing orders of allocated jobs. This paper proposes a service prediction-based job scheduling model and present its scheduling algorithm that is applicable for computational grid. The service prediction-based job scheduling model can minimize overall system execution time since the model predicts the next processing time of each processing component and distributes a job to a processing component with minimum processing time. This paper implements the job scheduling model on the DEVS modeling and simulation environment and evaluates its efficiency and reliability. Empirical results, which are compared to conventional scheduling policies, show the usefulness of service prediction-based job scheduling.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.354-357
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• 1996

Virtual Manufacturing System(VMS) is an integrated computer based model which has physical, logical schema and behavior of real manufacturing system. In this paper, an integrated scheduling system is developed to simulate and control a Virtual Factory. A workflow model is constructed to define and analyze the structure of a VMS. On-line dynamic dispatching system is developed using MultiPass algorithm and scheduling system considering dynamic CAPP is carried out. Integrated scheduling system developed in this paper reduces the discrepancies between virtual model and real manufacturing system, and control of real shop floor is possible.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.445-449
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• 1997

In order to provide a manufacturing system with efficiency and flexibility to cope with the changes in shop floor status, the integration of process planning and operations scheduling is required. In this paper,an integrated system of process planning and operations scheduling based on the concept of process net model is presented. The process net model includes the alternative process plans. The integrated system is applied for prismatic parts.