• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.97-110
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• 2018

With the advent of the 4-th industrial revolution, manufacturing companies have increasing interests in the realization of smart manufacturing by utilizing their accumulated facilities data. However, most previous research dealt with the structured data such as sensor signals, and only a little focused on the unstructured data such as text, which actually comprises a large portion of the accumulated data. Therefore, we propose an association rule mining based facility error pattern extraction framework, where text data written by operators are analyzed. Specifically, phrases were extracted and utilized as a unit for text data analysis since a word, which normally used as a unit for text data analysis, is unable to deliver the technical meanings of facility errors. Performances of the proposed framework were evaluated by addressing a real-world case, and it is expected that the productivity of manufacturing companies will be enhanced by adopting the proposed framework.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.2 no.1
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• pp.19-30
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• 2001

Machine tool (Mother machine) is the basis of industrial development and it largely has an effect on the quality improvement and Productivity improvement of machinery products because it demands high technical abilities such as design, machining. control and assembling which reflect the technical level of a country. But, in case of domestic companies. it is difficult to secure good engineers and enough fund for developing machine tool, which can not narrow the gap with advanced machine tool manufacturing companies. Therefore, this Project focused on the extraction of research and development project to improve the international competitiveness of machine tool industry through comprehending problems that domestic companies have and investigating the research trend in domestic and international countries.

• IE interfaces
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• v.13 no.3
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• pp.388-395
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• 2000

In this paper, we propose an approach for integrated process planning and scheduling through analysis of the alternative operations sequences and machine selection in supply chain with multiple plants. It takes into account such factors alternative machine, alternative operations sequences, setup time, transportation time between plants, along with other manufacturing factors. The objective of the model is to minimize makespan of machine schedules for all parts, determines operations sequence for each part, and selects a machine for each operation simultaneously. Examples are presented to demonstrate the effectiveness of the proposed approach.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.86-98
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• 2022

Recently, many studies have been conducted to improve quality by applying machine learning models to semiconductor manufacturing process data. However, in the semiconductor manufacturing process, the ratio of good products is much higher than that of defective products, so the problem of data imbalance is serious in terms of machine learning. In addition, since the number of features of data used in machine learning is very large, it is very important to perform machine learning by extracting only important features from among them to increase accuracy and utilization. This study proposes an anomaly detection methodology that can learn excellently despite data imbalance and high-dimensional characteristics of semiconductor process data. The anomaly detection methodology applies the LIME algorithm after applying the SMOTE method and the RFECV method. The proposed methodology analyzes the classification result of the anomaly classification model, detects the cause of the anomaly, and derives a semiconductor process requiring action. The proposed methodology confirmed applicability and feasibility through application of cases.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.91-97
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• 1995

This paper presents a possible application of artificial neural network in CM system design. CM systems can be designed based on product lines, part characteristics or part routines. GT(Group Technology) which uses part characteristics to design cells is widely applied, however, the identification of the part-machine families is the fundamental problem in the design process. A heuristic procedure using SOFM which requires only part-machine incidence matrix is proposed in this research. Comparison studies on ZODIAC and ROC with SOFM model are done and the results are discussed and summarized in this paper.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.329-332
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• 1998

This Paper proposes a mathematical model to solve the cell formation problem with exceptional elements, Exceptional elements are bottleneck machines and exceptional parts that span two or more manufacturing cells. The model suggests whether it is cost-effective to eliminate an EE (by machine duplication or part subcontracting), or whether the intercellular transfer caused by the EE should remain in the cell formation. It provides an optimal solution for resolving the interaction created by EE in the initial cell formation solution. In addition, the model recognizes potentially advantageous mixed strategies ignored by previous approaches.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.7-12
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• 2006

This study considers the problem of scheduling jobs on uniform parallel machines with a common due date. The objective is to minimize the total absolute deviation of job completion times about the common due date. This problem is motivated by the fact that a certain phase of printed circuit board manufacturing is bottleneck and the processing speeds of parallel machines in this phase are uniformly different for all jobs. Optimal properties are proved and a simple polynomial time optimal algorithm is developed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.14 no.24
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• pp.53-69
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• 1991

This paper is concerned with software developments for scheduling and sequencing of FMS. The scheduling algorithms are developed for 3 types of FMS:single machine type FMS, flowshop type FMS. assembly line type FMS. For the single machine type FMS. full enumeration algorithm is used. For the flowshop type FMS heuristic algorithms are developed. For the assembly type FMS the exsisting PERT/CPM algorithm is applied. Numerical examples are presented for illustration of each algorithm. Each soft ware program list are attached as appendices.

• Journal of Industrial Convergence
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• v.5 no.2
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• pp.21-32
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• 2007

This paper deals with the sequencing problem in the operation of the manufacturing systems with the constraint of buffer capacity. Some of studies for this theme have been progressed for several years. And then most of them considered only one objective, such as maximum lateness, machine utilization, makespan, mean flowtime and so on. This study deal with two objectives of the delivery for customers and the idle time of machines for producers. For the decision of sequence, the utility function is used. The developed heuristic algorithm presents a good solution. Through a numerical example, the procedures of the job sequencing is explained.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.6
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• pp.370-376
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• 2016

Manufacturing data analysis and its applications are getting a huge popularity in various industries. In spite of the fast advancement in the big data analysis technology, however, the manufacturing quality data monitored from the automated inspection system sometimes is not reliable enough due to the complex patterns of product quality. In this study, thus, we aim to define the level of trusty of an automated quality inspection system and improve the reliability of the quality inspection data. By correlation analysis and feature selection, this paper presents a method of improving the inspection accuracy and efficiency in an SVM-based automatic product quality inspection system using thermal image data in an auto part manufacturing case. The proposed method is implemented in the sealer dispensing process of the automobile manufacturing and verified by the analysis of the optimal feature selection from the quality analysis results.