• Journal of Korean Institute of Industrial Engineers
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• v.32 no.2
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• pp.98-103
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• 2006

In this research, the single machine capacitated lot-sizing and scheduling problem with sequence- dependent setup costs and setup times (CLSPSD) is considered. This problem is the extension of capacitated lot-sizing and scheduling problem (CLSP) with an additional assumption on sequence-dependent setup costs and setup times. The objective of the problem is minimizing the sum of production costs, inventory holding costs and setup costs satisfying customers' demands. It is known that the CLSPSD is NP-hard. In this paper, the MIP formulation is presented. To handle the problem more efficiently, a conceptual model is suggested, and one of the well-known meta-heuristics, the simulated annealing approach is applied. To illustrate the performance of this approach, various instances are tested and the results of this algorithm are compared with those of the CLPEX. Computational results show that this approach generates optimal or nearly optimal solutions.

• International Journal of Quality Innovation
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• v.6 no.3
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• pp.70-94
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• 2005

The IC packaging industry heavily relies on shop floor information, necessitating the development of a model to flexibly define shop floor information and timely handle manufacturing data. This study presents a novel data model of product manufacturing flow to define shop floor information to effectively respond to accelerated developments in IC package industry. The proposed data model consists of four modules: operation template setup, general process setup, enhanced bill of manufacture (EBOMfr) setup, and work-order process setup. The data model can flexibly define the required shop floor information and decision rules for shop floor product manufacturing flow, allowing one to easily adopt changes of the product and on the shop floor. However, to handle floor dynamics of the IC packaging industry, this work also proposes a WIP (i.e. work-in-process) system for monitoring and controlling the product manufacturing flow on the shop floor. The WIP system integrates the data model with a WIP execution module. Furthermore, an illustrative example, the MIRL WIP System, developed by Mechanical Industrial Research Laboratories of Industrial Technology Research Institute, demonstrates the effectiveness of the proposed model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.91-100
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• 1990

This paper is concerned with the development of optimal algorithms for multi-stage flowshop scheduling problems with sequence dependent setup times. In the previous researches the setup time of a job is considered to be able to begin at the earliest opportunity given a particular sequence at the start of operations. In this paper the setup time of a job is considered to be able to begin only at the completion of that job on the previous machine to reflect the effects of the setup time to the performance measure of sequence dependent setup time flowshop scheduling. The results of the study consist of two areas; first, a general integer programming(IP) model is formulated and a nixed integer linear programming(MILP) model is also formulated by introducing a new binary variable. Second a depth-first branch and bound algorithm is developed. To reduce the computational burdens we use the best heuristic schedule developed by Choi(1989) as the first trial. The experiments for developed algorithm are designed for a 4$\times$3$\times$3 factorial design with 360 observations. The experimental factors are PS(ratio of processing time to setup time), M(number of machines), N(number of jobs).

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.99-110
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• 2019

As the 4th industrial revolution progressing, manufacturers are trying to apply intelligent information technologies such as IoT(internet of things) and machine learning. In the semiconductor/LCD/tire manufacturing process, schedule plan that minimizes setup change and due date violation is very important in order to ensure efficient production. Therefore, in this paper, we suggest the deep learning based scheduling generation model minimizes setup change and due date violation in parallel machines. The proposed model learns patterns of minimizing setup change and due date violation depending on considered order using the amount of historical data. Therefore, the experiment results using three dataset depending on levels of the order list, the proposed model outperforms compared to priority rules.

• Journal of KIISE:Information Networking
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• v.29 no.4
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• pp.405-411
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• 2002

Open interfaces in the optica] Internet have been progressed by OIF's ISI, ITU-T ASTN's CCI and IETF's GSMP extensions with optical switching. These open interfaces enable the separation between the control plane and the optical transport plane. This separation allows flexibility in the network, but it suffers more setup delay than the traditional switch-by-switch connection setup. We propose the parallel interworking model, which will reduce the connection setup delay in the open interface of optical Internet. Based on the switch controller's caching capability about networks states, the parallel interworking procedures between signaling protocol and GSMP protocol are performed in the switch controller. We simulated and evaluated our proposed parallel interworking model and the existing sequential interworking model in terms of a connection setup delay and a completion ratio. We observed that the completion ratios of the two interworking models were quite close. However the connection setup delay of parallel interworking model is improved by about 30% compared with that of the sequential interworking model.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.19-33
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• 2019

Recently, manufacturers have been struggling to efficiently use production equipment as their production methods become more sophisticated and complex. Typical factors hindering the efficiency of the manufacturing process include setup cost due to job change. Especially, in the process of using expensive production equipment such as semiconductor / LCD process, efficient use of equipment is very important. Balancing the tradeoff between meeting the deadline and minimizing setup cost incurred by changes of work type is crucial planning task. In this study, we developed a scheduling model to achieve the goal of minimizing the duedate and setup costs by using reinforcement learning in parallel machines with duedate and work preparation costs. The proposed model is a Deep Q-Network (DQN) scheduling model and is a reinforcement learning-based model. To validate the effectiveness of our proposed model, we compared it against the heuristic model and DNN(deep neural network) based model. It was confirmed that our proposed DQN method causes less due date violation and setup costs than the benchmark methods.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.06a
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• pp.129-134
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• 2003

In this paper, we determine optimal reduction in the lead time and setup cost for some stochastic inventory models. And we propose more general model that allow the backorder rate as a control variable. We first assume that the lead time demand follows a normal distribution. And we assume that the backorder rate is dependent on the length of lead time through the amount of shortages. The stochastic models analyzed in this paper are the classical continuous and periodic review policy models with a mixture of backorders and lost sales. For each of these models, we provide a sufficient conditions for the uniqueness of the optimal operating policy. We also develop algorithms for solving these models and provide illustrative numerical examples.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.32
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• pp.121-126
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• 1994

Setup Time Reduction is an important aspect of the Just-in-Time(JIT) and Zero Inventory(Zl) Concepts since it supports reductions in manufacturing lead times and inventories. It also enables small lot sizes and kanban systems implementation for material flow - achieving major improvements in production floor management. One concept fundamental to the pursuit of JIT production in Japan and other countries is adoption of a setup time reduction. This paper looks at the necessities of setup time reduction and the relations to machine utilization. By using an EOQ model for evaluate the effect of setup time reduction, we get the results that over 75 % reduction in setup time is obtain the desired results in the lot size reduction.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.19
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• pp.79-88
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• 1989

This characteristics of process industries are high capital intensity, relatively long and sequence dependent setup times, and extremely limited capacity resources. The lot sizing, sequencing and limited capacity resources factors must he considered for production scheduling in these industries. This paper presents a mixed integer programming model for production scheduling. The economic trade offs between capacitated lot sizing flow shop scheduling and sequence dependent setup times also be compared with SMITH-DANIELS's model. As a results, it is shown that this paper has lower total cost, more efficient throughput than SMITH-DANIELS's model.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.1
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• pp.67-84
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• 1995

Five-axis NC machining is advanced machining technology by which highly geometrically complicated parts can be machined accurately with high machinability. In this paper, we investigate the problems of determining the machinability and part setup orientation for a given surface models. We first develop kinematic model of the five-axis machines based on the axis configuration, then develop algorithms for determining the feasibility of machining by one setup(machinability) and the part orientation for the C,A and A,B type configuration. The machinability is determined by computationally efficient procedure for finding the intersection between the feasible area on the sphere and the numerical map called binary spherical map(BSM), and the part setup is chosen such that the rotational range is minimized among the feasible configurations. The developed algorithms are tested by numerical simulations, convincing they can be readily implemented on the CAD/CAM system as an automated process planner giving the efficient machine type and setup for NC machining.