• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.82-87
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• 1998

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 and genetic algorithm is suggested. The process net model includes the alternative process plans. The integrated system is applied for prismatic parts.

• 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 the Korean Operations Research and Management Science Society
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• v.30 no.3
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• pp.55-65
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• 2005

In recent manufacturing systems, most jobs may have several process plans, such as alternative sequence of operations, alternative machine etc. A few researches have addressed the necessity for the integration of process planning and scheduling function for efficient use of manufacturing resources. But the integration problem is very difficult and complex. Many prior researches considered them separately or sequentially. It introduces overlapping or partial duplications in solution efforts. In this paper, Integration problem of jobs with multiple process plans in a job shop environment Is addressed. In order to achieve an efficient integration between process planning and scheduling by taking advantage of the flexibility that alternative process plans offer, we designed GA(Genetic Algorithm)-based scheduling method. The performance of proposed GA is evaluated through comparing integrated scheduling with separated scheduling in real world company with alternative machines and sequences of operations. Also, a couple of benchmark problems are used to evaluate performance. The integrated scheduling method in this research can be effectively epplied to the real case.

• Korean Journal of Computational Design and Engineering
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• v.18 no.2
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• pp.129-137
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• 2013

This paper proposed the scheduling method for tire mixing processes using the genetic algorithm. The characteristics of tire mixing process have the manufacturing routing, operation machine and operation time by compound types. Therefore, the production scheduling has to consider characteristics of the tire mixing process. For the reflection of the characteristics, we reviewed tire mixing processes. Also, this paper introduces the genetic algorithm using the crossover and elitist preserving selection strategy. Fitness is measured by the makespan. The proposed genetic algorithm has been implemented and tested with two examples. Experimental results showed that the proposed algorithm is superior to conventional heuristic algorithm.

• IE interfaces
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• v.17 no.spc
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• pp.20-27
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• 2004

A flexible assembly system (FAS) is a production system that assembles various parts with many constraints and manufacturing flexibilities. This paper presents a new method for efficiently solving the integrated process planning and scheduling in FAS. The two problems of FAS process planning and scheduling are tightly related with each other. However, in almost all the existing researches on FAS, the two problems have been considered separately. In this research, an endosymbiotic evolutionary algorithm is adopted as methodology in order to solve the two problems simultaneously. This paper shows how to apply an endosymbiotic evolutionary algorithm to solving the integrated problem. Some evolutionary schemes are used in the algorithm to promote population diversity and search efficiency. The experimental results are reported.

• IE interfaces
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• v.19 no.2
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• pp.153-159
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• 2006

The research of scheduling algorithms for operating the facility of exhibition and convention can be hardly found in published papers. This study is to find problems in the process of operating the facility of exhibition and convention and to develop the scheduling algorithm satisfying those problems. The scheduling algorithm of this paper is developed through constructing the mathematical model and analyzing the mathematical structure of variables and constraints in that model. The scheduling algorithm developed in this paper consists of the first stage of scheduling, the second stage of feasibility routine and the third stage of improving scheduling results. Some experimental results are given to verify the effectiveness of the scheduling algorithm developed in this paper.

• 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.

• IE interfaces
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• v.16 no.2
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• pp.185-194
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• 2003

This paper deals with a realistic production scheduling under a make-to-order production environment. The practical case is studied on the transformer winding process in the 'H' company. The transformer winding is a process that rolls a coil that is coated with an electric insulation material in order to generate the required voltage using the voltage fluctuation. This process occupies an important position among the production processes in the transformer manufacturing company. And this process is composed of parallel machines with different performances according to the voltage capacity and winding type. In this paper, we propose a practical heuristic algorithm for production scheduling to satisfy the customer’s due date under a make-to-order production environment. Also, we implement the production scheduling system based on the proposed heuristic algorithm. Consequently, the proposed heuristic algorithm and the implemented production scheduling system are currently working in the transformer production factory of the ‘H’ company.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.1-9
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• 2015

In shipbuling processes, a quay wall is a major resource for additional operations after an erection operation at dock. A quay wall is becoming a new bottleneck instead of docks, while ship types with long operation time at quay wall are increasing recently. We developed a quay wall scheduling algorithm for the quayside operations of ships in this paper. The objective function is to minimize the sum of not assigned days of ships which have to be assigned to any quay wall under limited numbers of quay walls. The scheduling algorithm is based on an assignment method to assign each ship to a quay wall among its alternative quay walls at the time of launching or moving to another quay wall. The scheduling algorithm is also using Tabu Search algorithm to optimize assignment sequence of ships. The experiment shows that the algorithms in this paper are effective to make schedule of the quayside operations of ships.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.111-120
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• 2017

This paper proposes an improved standard genetic algorithm (GA) of making a near optimal schedule for integrated process planning and scheduling problem (IPPS) considering tool flexibility and tool related constraints. Process planning involves the selection of operations and the allocation of resources. Scheduling, meanwhile, determines the sequence order in which operations are executed on each machine. Due to the high degree of complexity, traditionally, a sequential approach has been preferred, which determines process planning firstly and then performs scheduling independently based on the results. The two sub-problems, however, are complicatedly interrelated to each other, so the IPPS tend to solve the two problems simultaneously. Although many studies for IPPS have been conducted in the past, tool flexibility and capacity constraints are rarely considered. Various meta-heuristics, especially GA, have been applied for IPPS, but the performance is yet satisfactory. To improve solution quality against computation time in GA, we adopted three methods. First, we used a random circular queue during generation of an initial population. It can provide sufficient diversity of individuals at the beginning of GA. Second, we adopted an inferior selection to choose the parents for the crossover and mutation operations. It helps to maintain exploitation capability throughout the evolution process. Third, we employed a modification of the hybrid scheduling algorithm to decode the chromosome of the individual into a schedule, which can generate an active and non-delay schedule. The experimental results show that our proposed algorithm is superior to the current best evolutionary algorithms at most benchmark problems.