• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.47
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• pp.35-45
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• 1998

Scheduling problem in Flexible Manufacturing Systems(FMS) is complex because of various situation of Manufacturing Systems. Especially, in case of short-term scheduling demanding high efficiency, low cost at short-period, efficient scheduling is a serious problem. To solve this problem, many dispatching rules are developed. But, it leave much to be desired, because real situation in shop floor is complex and real-time scheduling is needed in real manufacturing shop floor. In this paper, search algorithm that allocate different dispatching rules to each machine is presented to complement lack of dispatching rule and develop practical real-time scheduling system. The search algorithm is described in detail. First, algorithm detect machine breakdown, evaluate each dispatching rule. dispatching rules for each machine meeting performance criteria are ranked. The algorithm selects new dispatching nile for bottleneck machine. The effectivenes and efficiency of the mixed dispatching rule and search algorithm is demonstrated.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.2
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• pp.82-90
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• 2006

Reconfigurability of machine tools is one of the critical factors to realize the responsive manufacturing systems to satisfy the mass customization production. This paper presents the methods to model the reconfigurable machine tools (RMTs) on Internet in response to change in the machining requirements. Specifically, the structure and motion model of machine tools using module combination rules and connectivity graph are developed. And we developed Internet-based simulator for designing of RMTs (ISD-RMT). In response to the user requirements, various structures of RMTs can be derived using the module combination rules and connectivity graph relationships. In addition, the user can verify generating structures through the control and simulation procedures.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.05a
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• pp.145-153
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• 1999

We consider a Direct Input Output Manufacturing System(DIOMS) which has a munber of machine centers placed along a built-in Automated Storage/Retrieval System(AS/RS). The Storage/Retrieval (S/R) machine handles parts placed on pallets for the machine centers located at either one or both sides of the As/Rs. This report studies the operational aspect of DIOMS and determines the optimal operating policy by combining computer simulation and genetic algorithm. The operational problem includes: input sequencing control, dispatching rule of the S/R machine, machine center-based part type selection rule, and storage assignment policy. For each operating policy, several different policies are considered based on the known research results. In this report, using the computer simulation and genetic algorithm we suggest a method which gives the optimal configuration of operating policies within reasonable computation time.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.1
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• pp.141-154
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• 1996

This paper presents a similarity coefficient based approach to the problem of machine-part grouping for cellular manufacturing. The method uses relevant production data such as part type, production volume, routing sequence to make machine cells and part families for cell formation. A new similarity coefficient using weighted factors is introduced and an algorithm for formation of machine cells and part families is developed. A comparative study of two similarity coefficient methods, Gupta and Seifoddini's method and the proposed method, is conducted.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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• pp.21-27
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• 2022

The rotorcraft engine gearbox transmits the power generated by the turboshaft engine to the rotor by reducing the rotational speed and increasing the torque. The core of the rotorcraft engine gearbox is lightweight performance, which requires maximum weight reduction within the range that meets various requirements and constraints. Therefore, lightweight design through gear macro geometry optimization is necessary. In this study, gear macro geometry optimization was performed to reduce the weight of a rotorcraft engine gearbox. NSGA-III was used for the optimization, resulting in a combination of the gear ratio and macro geometry that minimizes the weight of the total gear. In addition, the safety factor of the gears satisfied the given conditions.

• Industrial Engineering and Management Systems
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• v.3 no.1
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• pp.52-58
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• 2004

This report examines the issue of designing an efficient production system by increasing several types of flexibility. Increasing manufacturing flexibility is a key strategy for efficiently improving market responsiveness in the face of uncertain market demand for final products. The manufacturing system comprises multiple plants, of which individual plants have multiple manufacturing lines that are designed to produce limited types of products in accordance with their size and materials. Imbalance in the workload occurs among plants as well as among manufacturing lines because of fluctuations in market demand for final products. Thereby, idleness of some manufacturing lines and longer lead times in some manufacturing lines occur as a result of the high workload. We clarify how these types of flexibility affect manufacturing performance by improving only one type of flexibility or by improving multiple types of flexibility simultaneously. The average lead time and the imbalance in workload are adopted as measures of manufacturing performance. Three types of manufacturing flexibility are interrelated: machine flexibility, routing flexibility, and process flexibility. Machine flexibility refers to the various types of operations that a machine can perform without requiring the prohibitive effort of switching from one order to another. Routing flexibility is the capability of processing a given set of part types using more than one line (alternative line) in the plant. Process flexibility results from being able to build different types of final products at the same plant.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.295-302
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• 2022

This paper contains the development of a smart power device designed to collect load power data from industrial manufacturing machines, predict future variations in load power data, and detect abnormal data in advance by applying a machine learning-based prediction algorithm. The proposed load power data prediction model is implemented using a Long Short-Term Memory (LSTM) algorithm with high accuracy and relatively low complexity. The Flask and REST API are used to provide prediction results to users in a graphical interface. In addition, we present the results of experiments conducted to evaluate the performance of the proposed approach, which show that our model exhibited the highest accuracy compared with Multilayer Perceptron (MLP), Random Forest (RF), and Support Vector Machine (SVM) models. Moreover, we expect our method's accuracy could be improved by further optimizing the hyperparameter values and training the model for a longer period of time using a larger amount of data.

• IE interfaces
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• v.14 no.1
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• pp.20-29
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• 2001

This paper presents a concurrent design approach that deals with manufacturing cell formation and cellular layout in Cellular Manufacturing System. Manufacturing cell formation is to group machines into machine cells dedicated to manufacture of part families, and cellular layout problem determines layout of the manufacturing cells within shop and layout of the machines within a cell. In this paper, a concurrent approach for design of machine cell and cellular layout is developed considering manufacturing parameters such as alternative process plans, alternative machines, production volume and processing time of part, and cost per unit time of operation. A mathematical model which minimizes total cost consisting of machine installation cost, machine operating cost, and intercell and intracell movements cost of part is proposed. A hybrid method based on genetic algorithm is proposed to solve the manufacturing cell formation and cellular layout design problem concurrently. The performance of the hybrid method is examined on several problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.137-146
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• 2000

One of the problems faced in implementing cellular manufacturing systems is machine-part group formation. This paper proposes machine-part grouping algorithms based on Self-Organizing Map(SOM) neural networks and K-Means algorithm in cellular manufacturing systems. Although the SOM spreads out input vectors to output vectors in the order of similarity, it does not always find the optimal solution. We rearrange the input vectors using SOM and determine the number of groups. In order to find the number of groups and grouping efficacy, we iterate K-Means algorithm changing k until we cannot obtain better solution. The results of using the proposed approach are compared to the best solutions reported in literature. The computational results show that the proposed approach provides a powerful means of solving the machine-part grouping problem. The proposed algorithm Is applied by simple calculation, so it can be for designer to change production constraints.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.59-72
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• 1998

This study is concerned in manufacturing cell formation with operation sequences. Operation sequences must be reflected for manufacturing cell formation anyway, because the primary aim of cellular manufacturing system is to minimize the inter-cell flows, and inter-cell flows are differed by operation sequences. In this study we propose flow-similarity(FS) of reflecting both inter-machine similarity and direct/indirect flow, and then apply the modified P-median model for grouping machines. We also use machine cell-part handling frequency(CPH) so as to be assigned parts to the machine cells having the most CPH. We confirm this approach through an application example. The performance of this approach(FS-model) is evaluated and compared with P-median model and F-model through computational experiments.