• Journal of Welding and Joining
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• 제34권3호
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• pp.1-5
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• 2016

At present, FSW(friction stir welding) process is being considered as an actual way for production of various industrial products. However FSW process involves high temperature and load on the tool during welding. These are make a difference between FSW machine and general machine tools. From this reason, development of FSW machine needs very careful consideration on stiffness of machine structure, spindle and moving axis including machine control system. In this study authors investigate on the trends of technology development of FSW machine in order to share the information for more extension of FSW technology with related researchers and engineers.

• 산업경영시스템학회지
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• 제20권43호
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• pp.277-285
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• 1997

In this paper, the definition to flexibility is examined through the literature and re-classified to set up an evaluation model. Flexibility is classified into three categories to find the flexibility types for evaluation. The flexibility type called as manufacturing flexibility is defined and a model is developed to make the performance evaluation possible, The manufacturing flexibility has a heavy relationship to the machine flexibility; and 5 flexibility types out of 8 have relationship to the machine flexibility. This indicates that it is possible to have a pretty good evaluation measure if the machine flexibility related types could be evaluated using a model. There are four different inter-arrival times in the model. A big time saving is observed if the processing time is set equal to 72 second. This indicates that a flexibility affects the system a lot if the inter-arrival time is close to the processing time. The model used in this paper includes multi-processes in a production line with machine failure. However, development of realistic models with buffer between processes and some of the flexibility types not included in this model are remained for further research.

• 산업경영시스템학회지
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• 제22권49호
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• pp.67-76
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• 1999

This research presents the relationship among machining time, cycle time and demand rate in a cellular manufacturing system. The manufacturing cell produces part families by automated machines. This paper discusses the cases of increasing demand rate in an existing cell and designing cell based on the demand rate. This research developed an algorithm for decision making such as cycle time, machines and workers in order to minimize the total machine capacity and the number of workers for any given demand rate. The proposed algorithm was successfully applied for the design and operation of cell manufacturing with a good result.

• 산업공학
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• 제12권1호
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• pp.10-18
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• 1999

Job shop manufacturing environments are using the concept of cellular manufacturing systems(CMS) which has several advantages in reducing production lead times, setup times, work-in-process, etc. Utilizing the similarities between cell-machine, part-machine, and the shape/size of parts, CMS can group machines and parts resulting in improved efficiency of this system. However, when grouping machines and parts in machine cells, there inevitably occurs exceptional elements(EEs), which can not operate in the same machine cell. Minimizing these EEs in CMS is a critical point that improving production efficiency. Constraints in machine duplication cost, machining process technology, machining capability, and factory space limitations are main problems that prevent achiving the goal of maintaining an ideal CMS environment. This paper presents an algorithm that minimizes EEs under the constraints of machine duplication cost and factory space limitation. Developing exceptional operation similarity(EOS) by cell-machine incidence matrix and part-machine incidence matrix, it brings the machine cells that operate the parts or not. A mathematical model to minimize machine duplication is developed by EOS, followed by a heuristic algorithm in order to reflect dynamic situation resulting from minimizing exceptional elements process and the mathematical model. A numerical example is provided to illustrate the algorithm.

• 산업공학
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• 제11권3호
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• pp.23-40
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• 1998

In this paper, a method to determine the optimal configuration of operating policies in an integrated-automated manufacturing system using the Taguchi method and computer simulation experiments is presented. An integrated-automated manufacturing system called direct-input-output manufacturing system(DIOMS) is described. We only consider the operational aspect of the DIOMS. Four operating policies including input sequencing control, dispatching rule for the storage/retrieval(S/R) machine, machine center-based part type selection rule, and storage assignment policy are treated as design factors. The number of machine centers, the number of part types, demand rate, processing time and the rate of each part type, vertical and horizontal speed of the S/R machine, and the size of a local buffer in the machine centers are considered as noise factors in generating various manufacturing system environment. For the performance characteristics, mean flow time and throughput are adopted. A robust design experiment with inner and outer orthogonal arrays are conducted by computer simulation, and an optimal configuration of operating policies is presented which consists of a combination of the level of each design factor. The validity of the optimal configurations is investigated by comparing their signal-to-noise ratios with those obtained with full factorial designs.

• 산업경영시스템학회지
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• 제38권3호
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• pp.100-107
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• 2015

Recently as the manufacturers want competitiveness in dynamically changing environment, they are trying a lot of efforts to be efficient with their production systems, which may be achieved by diminishing unplanned operation stops. The operation stops and maintenance cost are known to be significantly decreased by adopting proper maintenance strategy. Therefore, the manufacturers were more getting interested in scheduling of exact maintenance scheduling to keep smooth operation and prevent unexpected stops. In this paper, we proposedan integrated maintenance approach in injection molding manufacturing line. It consists of predictive and preventive maintenance approach. The predictive maintenance uses the statistical process control technique with the real-time data and the preventive maintenance is based on the checking period of machine components or equipment. For the predictive maintenance approach, firstly, we identified components or equipment that are required maintenance, and then machine parameters that are related with the identified components or equipment. Second, we performed regression analysis to select the machine parameters that affect the quality of the manufactured products and are significant to the quality of the products. By this analysis, we can exclude the insignificant parameters from monitoring parameters and focus on the significant parameters. Third, we developed the statistical prediction models for the selected machine parameters. Current models include regression, exponential smoothing and so on. We used these models to decide abnormal patternand to schedule maintenance. Finally, for other components or equipment which is not covered by predictive approach, we adoptedpreventive maintenance approach. To show feasibility we developed an integrated maintenance support system in LabView Watchdog Agent and SQL Server environment and validated our proposed methodology with experimental data.

• 산업공학
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• 제10권3호
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• pp.189-196
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• 1997

This paper presents a cell formation approach for a cellular manufacturing system to minimize the inter-cell moves considering operation sequences. Two new factors are introduced: (1)flow-similarity(FS) for integrating direct/indirect inter-machine flow and similarity (2)machine cell-part moves (CPM) for exactly computing inter-cell moves. FS is used for combining machines and CPM is used for assigning the parts to the preliminary machine cells. In addition, we develop an aggregated heuristic algorithm to form manufacturing machine cells and assign the parts to those cells based on these concepts. We use performance criterion called total inter-cell moves(TICM), which is the total material flow between internal cells and external cells. Results of computational tests on a number of randomly generated test problems show that the suggested heuristic is superior to existing methods.

• 에너지공학
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• 제26권3호
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• pp.11-29
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• 2017

인공지능 특히 심층신경망기계학습기법(딥러닝)의 제조업분야에서의 이용이 효율적이며 실용적일 수 있다는 인식이 넓게 수용되고 있다 이 보고서는 최근의 신경망기계학습 개발환경을 개관하고 제조업분야에서 활용되고 있는 딥 러닝기술을 개관한다.

• 한국기계가공학회지
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• 제19권5호
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• pp.111-117
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• 2020

Centrifugal casting is suitable for producing hollow-products using centrifugal force. Bush type metal bearings are the key parts that facilitate the rotational movement of various machinery. Metal bearings produced by conventional centrifugal casting machines show rotational imbalance. Therefore, after injecting a large amount of material, the product's precision is secured in the secondary processing. Rotational imbalance is caused by the force acting on the rotary disc plate. In order to minimize rotational imbalance, NASTRAN was used for the optimal design and structural analysis. It was concluded that the rotating plate of the conventional centrifugal casting machine should be prevented from tilting. For this purpose, the location & thickness of the stiffeners were obtained through the optimum design. In the conventional centrifugal casting machine, both ends of the product are lower in temperature than the center part, so internal stress occurs. This solves this problem by inserting a heating coil into the rotating plate.

• 대한산업공학회지
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• 제24권1호
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• pp.23-35
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• 1998

This article presents a network flow analysis to form flexible machine cells with minimum intercellular part moves and a neural network model to form part families. The operational sequences and production quantity of the part, and the number of cells and the cell size are taken into considerations for a 0-1 quadratic programming formulation and a network flow based solution procedure is developed. After designing the machine cells, a neural network approach for the integration of part families and the automatic assignment of new parts to the existing cells is proposed. A multi-layer backpropagation network with one hidden layer is used. Experimental results with varying number of neurons in hidden layer to evaluate the role of hidden neurons in the network learning performance are also presented. The comprehensive methodology developed in this article is appropriate for solving large-scale industrial applications without building the knowledge-based expert rule for the cellular manufacturing environment.