• Ocean Systems Engineering
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• v.9 no.3
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• pp.329-347
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• 2019

The shipbuilding industry is characterized by order production, and various processes are performed simultaneously in the construction of ships. Therefore, effective management of the production process and productivity improvement form important key factors in the industry. For decades, researchers and process managers have attempted to improve processes by using business process analysis (BPA). However, conventional BPA is time-consuming, expensive, and mainly based on subjective results generated by employees, which may not always correspond to the actual conditions. This paper proposes a method to improve the production process of offshore plant modules by analysing the process mining data obtained from the shipbuilding industry. Process mining uses information accumulated from the system-provided event logs to generate a process model and determine the values hidden within the process. The discovered process is visualized as a process model. Subsequently, alternatives are proposed by brainstorming problems (such as bottlenecks or idle time) in the process. The results of this study can aid in productivity improvement (idle time or bottleneck reduction in the production process) in conjunction with a six-sigma technique or ERP system. In future, it is necessary to study the standardization of the module production processes and development of the process monitoring system.

• Journal of the Korea Safety Management & Science
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• v.9 no.6
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• pp.163-169
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• 2007

This study deals with the improvement of production process on a flow production system with the consideration of six sigma. We analyze the production process and survey the important factors of improvement of productivity. Using a six sigma, we find strategic point and suggest a reformation of production process. We applied a simulation technique to simulate the production line proposed by the result of the Six sigma. With the result of the simulation, this study analyzes the propriety of production line and proposes the alternatives of new production process.

• Proceedings of the Safety Management and Science Conference
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• 2007.11a
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• pp.9-19
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• 2007

This study deals with the improvement of production process on a flow production system with the consideration of six sigma. We analyze the production process and survey the important factors of improvement of productivity. Using a six sigma, we find strategic point and suggest a reformation of production process. We applied a simulation technique to simulate the production line proposed by the result of the Six sigma. With the result of the simulation, this study analyzes the propriety of production line and proposes the alternatives of new production process.

• Journal of the Korea Safety Management & Science
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• v.24 no.3
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• pp.93-103
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• 2022

This study investigated the method of continuous improvement of small-medium company production processes through POSCO's QSS(Quick Six Sigma) activities. QSS is a field operation technique that encompasses the advantages of Six Sigma, TPS(Toyota Production System), TQM (Total Quality Management), and IE(Industrial Engineering). Through this, POSCO not only encourages activities centered on related small and medium-sized partners, etc., but is also expected to contribute to the continuous improvement of the company's own production process through QSS activities. In this study, rather than unconditionally carrying out activities according to the needs of large companies, the research is to help the continuous improvement of the actual production process of small and medium-sized enterprises by effectively applying and spreading QSS activities in consideration of the characteristics and environment of the company. For this purpose, empirical research is conducted on the process improvement activities and QSS activities of company Y, which has less than 100 assembly and production quality and inspection processes among SMEs. The changes in the production process improvement of SMEs through the application of the final QSS were investigated through empirical studies.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.199-204
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• 2017

Good product quality is so essential to enabling firms to succeed that how to make the product quality better through technology development is one of the most important issues that many CEOs think over. With regard to the product quality improvement from firms' technology development, this study has made an attempt to empirically investigate the effect of the external information network diversity on the product quality improvement of the small and medium-sized enterprises (SMEs) in the information technology (IT) sector, mediated by their production process improvement. This research illuminates the following two points by empirically analyzing the 310 IT SMEs through the ordinary least squares regression analysis. First, IT SMEs' external information network diversity has a positive influence on their product quality improvement from technology development. Second, IT SMEs' production process improvement partially mediates the impact of their external information network diversity on the product quality improvement.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.11-28
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• 2009

Intelligent investment in setup cost reduction and process reliability improvement is crucial to an emerging integrated lean six sigma practice today. This study examines a cost-minimizing problem of jointly determining production lot size, setup cost reduction, and process reliability improvement decisions for a manufacturer with an imperfect production process. We develop models for previously untapped discrete shipping in a supply chain context as well as continuous shipping and solve them optimally using differential calculus and nonlinear programming. We also conduct analytic and numerical sensitivity analyses to provide various important managerial insights into practices.

• The Journal of Information Systems
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• v.27 no.3
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• pp.25-42
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• 2018

Purpose The purpose of this study focused on adopting production systems in cognitive psychology to improve the extraction process of persuasive design characteristics for healthcare-related mobile applications. Design/Methodology/Approach A research approach with four stages was developed. We developed and updated the evaluation guideline for persuasive design characteristics (PDC). We tried to summarize and analyze each of 28 PDC and prepared related production rules. Verification process for both guideline approach and production system approach were performed. Top one hundred apps from both medical category and health and Fitness category were selected and evaluated by two approaches. By comparing the results of the two approaches, we tried to explain the improvement and reliability of introducing the production system in the PDC extraction process. Findings Based on the updated guideline for healthcare-related mobile applications, a production system in cognitive psychology was developed. By comparing the PDC extraction results by two approaches, production system showed a better improvement for evaluation precision and efficiency for decision-making process. The findings of this study can be used for researchers and app developers to apply production system to analyze, evaluate, and develop better healthcare-related apps with persuasion.

• Proceedings of the Safety Management and Science Conference
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• 2007.04a
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• pp.73-80
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• 2007

Recently, the strategy of the age of limitless competition for existence of manufacturing company appears for the enhancement of productivity through the automatic system, the reduction for the cost for standardization and the decision making process for the information system. Especially the critical success factors in manufacturing company can be summarized for the establishment of production visibility through the production management, material & work-in-process management, the establish of the flexible manufacturing system for the changed order priority and the establish of the quality system for improvement of product and process quality. The existing production management systems supply only simple information about production results on real time, can delay quick decision making. And it can prevent acquiring the information about various customer needs and the communication problems with other systems. In this paper, it will show MES system, a solution for the problems of existing production management systems. And through a case study of D company, it will reveal improvement effect on shipment error using MES system and economic analysis for MES itself.

• The Journal of Information Systems
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• v.26 no.2
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• pp.143-164
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• 2017

Purpose The purpose of this study is to investigate to investigate the effects of cloud system on the efficiency improvement and cost-saving of production processes. It also tries to provide small- and medium-sized companies and IT practitioners with a practical guideline for a successful implementation of could systems. Design/methodology/approach This study was conducted by observing and analyzing a case of implementing a cloud system at a small-sized company having multiple job sites in terms of the improvement in data-sharing efficiency and cost-saving of production processes. Findings This study found that cloud system was an effective way of sharing data between and among production processes of geographically scattered job sites and thus, helped the company to remedy problems of work schedule and load-balance along sequential production processes. Cloud system also allowed the company to reduce the number of visits made by 3-inspectors to four job sites by 75% and the personnel cost related to inspectors' site visit.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.137-145
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• 2020

Various elements of Fabrication (FAB), mass production of existing products, new product development and process improvement evaluation might increase the complexity of production process when products are produced at the same time. As a result, complex production operation makes it difficult to predict production capacity of facilities. In this environment, production forecasting is the basic information used for production plan, preventive maintenance, yield management, and new product development. In this paper, we tried to develop a multiple linear regression analysis model in order to improve the existing production capacity forecasting method, which is to estimate production capacity by using a simple trend analysis during short time periods. Specifically, we defined overall equipment effectiveness of facility as a performance measure to represent production capacity. Then, we considered the production capacities of interrelated facilities in the FAB production process during past several weeks as independent regression variables in order to reflect the impact of facility maintenance cycles and production sequences. By applying variable selection methods and selecting only some significant variables, we developed a multiple linear regression forecasting model. Through a numerical experiment, we showed the superiority of the proposed method by obtaining the mean residual error of 3.98%, and improving the previous one by 7.9%.