• Journal of Service Research and Studies
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• v.4 no.1
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• pp.37-47
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• 2014

Researches in the services field have evolved tremendously in the last 20 years. However, researches in service innovation still follows the traditional approaches of product quality improvements. The current research reviews the relevant literature from the past, and analyzes limitations each research possess, thus suggest a service innovation framework. Also, we have developed a diagnostic tool that measures the level of service innovation driven from actual cases. The current research suggests a new road map to organizations that pursue service innovation as well as a new research direction to the researchers in the field of service innovation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.107-116
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• 2019

The defense industry has recently been developed for boosting exports of weapon systems. The survey and analysis of the quality level are required to form a relevant policy for expanding the defense industry. Evaluation indices and modeling of the quality level for manufacturers are used to examine the status of internal quality management and quality management system in order to enhance the overall quality level and establish a quality policy in the field of military supplies. There were some restrictions to apply all aspects of the quality level in the previous model. This paper deals with the research and analysis of other types of model for evaluating the quality level, including the model used in the defense field. By enhancing the close link between procedure indices and performance indices, the research and analysis could be conducted objectively and intuitively. The developed and improved model and indices will be used in the next survey of the quality level for manufacturers of military supplies. The survey results will be used to establish effective government quality management policy.

• Journal of Korean Society for Quality Management
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• v.45 no.1
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• pp.25-38
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• 2017

Purpose: Hot strip rolling mill consists of a lot of mechanical and electrical units. In condition monitoring and diagnosis phase, various units could be failed with unknown reasons. In this study, we propose an effective method to detect early the units with abnormal status to minimize system downtime. Methods: The early warning problem with various units is defined. K-means and PAM algorithm with Euclidean and Manhattan distances were performed to detect the abnormal status. In addition, an performance of the proposed algorithm is investigated by field data analysis. Results: PAM with Manhattan distance(PAM_ManD) showed better results than K-means algorithm with Euclidean distance(K-means_ED). In addition, we could know from multivariate field data analysis that the system reliability of hot strip rolling mill can be increased by detecting early abnormal status. Conclusion: In this paper, clustering-based monitoring and fault detection algorithm using Manhattan distance is proposed. Experiments are performed to study the benefit of the PAM with Manhattan distance against the K-means with Euclidean distance.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.783-793
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• 2019

Purpose: The purpose of this study is to apply the machine and deep learning methodology on error terms which are continuously auto-generated on the sensors with specific time period and prove the improvement effects of power generator prediction diagnosis system by comparing detection ability. Methods: The SVM(Support Vector Machine) and MLP(Multi Layer Perception) learning procedures were applied for predicting the target values and sequentially producing the error terms for confirming the detection improvement effects of suggested application. For checking the effectiveness of suggested procedures, several detection methodologies such as Cusum and EWMA were used for the comparison. Results: The statistical analysis result shows that without noticing the sequential trivial changes on current diagnosis system, suggested approach based on the error term diagnosis is sensing the changes in the very early stages. Conclusion: Using pattern of error terms as a diagnosis tool for the safety control process with SVM and MLP learning procedure, unusual symptoms could be detected earlier than current prediction system. By combining the suggested error term management methodology with current process seems to be meaningful for sustainable safety condition by early detecting the symptoms.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.75-86
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• 2019

Purpose: It is essential for the steel industry to produce steel products without unexpected downtime to reduce costs and produce high quality products. A hot strip rolling mill consists of many mechanical and electrical units. In condition monitoring and diagnosis, various units could fail for unknown reasons. Methods: In this study, we propose an effective method to detect units with abnormal status early to minimize system downtime. The early warning problem with various units was first defined. An autoencoder was modeled to detect abnormal states. An application of the proposed method was also implemented in a simulated field-data analysis. Results: We can compare images of original data and reconstructed images, as well as visually identify differences between original and reconstruction images. We confirmed that normal and abnormal states can be distinguished by reconstruction error of autoencoder. Experimental results show the possibility of prediction due to the increase of reconstruction error from just before equipment failure. Conclusion: In this paper, hot strip roughing mill monitoring method using autoencoder is proposed and experiments are performed to study the benefit of the autoencoder.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.25-38
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• 2019

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

• Journal of Service Research and Studies
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• v.11 no.4
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• pp.43-55
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• 2021

This study analyzed the efficiency of medical services in OECD member countries by dividing it into operational efficiency and quality efficiency. For this purpose, data from 2017-2019 OECD Health Statistics were used. As the analysis method, super efficiency was measured by applying an output-oriented Variable Returns to Scale (VRS) model. As a result of the analysis, Switzerland, Korea, and Italy were included in the high group of operational efficiency, Canada, Greece, Denmark, etc. in the medium group, and Belgium, Germany, and Spain in the low group. Based on quality efficiency, Norway, Switzerland, and Spain are in the high group, and Greece, Denmark, Mexico, etc. are in the medium group, and the Netherlands, Germany, Belgium, etc. were included in the low group. As a result of comparative analysis of efficiency by OECD member countries as of 2018, it was found that Korea's operational efficiency was the most efficient and quality efficiency was inefficient. Korea (0.998) should improve life expectancy by 0.2 (0.2%) and subjective health perception by 44.2 (138.1%) by benchmarking Greece (0.422), Switzerland (0.207), and Spain (0.371) to improve quality efficiency. Unlike most previous studies that focused on operational efficiency, this study measured quality efficiency together and analyzed the efficiency of the medical service industry in each OECD member country. Through this, this study has implications in that it confirmed the international competitiveness of the domestic medical service industry and suggested ways to improve efficiency.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.17 no.2
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• pp.223-238
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• 2006

For a public library. which is a regional information service agency. to acquire high competitiveness, preparation for uncertainties of future through understanding its own internal strengths and weaknesses. and external opportunities and threats based on assessments regarding knowledge information environment and characteristics of regional community. current status of the library, etc. Therefore. in this study, through SWOT analysis. one of competitive strategy analysis methods, the status of competitive strategy of C library was analyzed. In order to carry out the study interview and survey were performed with professional librarians, then through final consultations from management consulting experts, a plan to strengthen competitiveness for C library was devised. Conclusions from this study were as below. In order to strengthen competitiveness of C library offering distinguished high quality services through active cooperations with external institutions, efforts to improve library's position and stand following being selected as a library to visit for 2006 World Library and Information Congress, and revitalization of library usage through providing user oriented differentiated services are needed.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.217-242
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• 2022

With the launch of Artificial Intelligence(AI)-based intelligent products on the market, innovative changes are taking place not only in business but also in consumers' daily lives. Intelligent products have the potential to realize technology differentiation and increase market competitiveness through advanced functions of artificial intelligence. However, there is no new product development methodology that can sufficiently reflect the characteristics of artificial intelligence for the purpose of developing intelligent products with high market acceptance. This study proposes a KANO-QFD integrated model as a methodology for intelligent product development. As a specific example of the empirical analysis, the types of consumer requirements for hair loss prediction and treatment device were classified, and the relative importance and priority of engineering characteristics were derived to suggest the direction of intelligent medical product development. As a result of a survey of 130 consumers, accurate prediction of future hair loss progress, future hair loss and improved future after treatment realized and viewed on a smartphone, sophisticated design, and treatment using laser and LED combined light energy were realized as attractive quality factors among the KANO categories. As a result of the analysis based on House of Quality of QFD, learning data for hair loss diagnosis and prediction, micro camera resolution for scalp scan, hair loss type classification model, customized personal account management, and hair loss progress diagnosis model were derived. This study is significant in that it presented directions for the development of artificial intelligence-based intelligent medical product that were not previously preceded.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.2
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• pp.87-102
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• 2016

The customer requirements are constantly changing in the hyper-competition and competition is becoming increasingly intensified. In order to ensure the competitive advantage in the industry should focus on the management activities to enhance customer satisfaction. High quality means pleasing customers, not just protecting them from annoyances. It is due to continuous and requires the establishment of a quality management system that meets the characteristics and systematization need to manage a stable quality and productivity, which should be done in a company-wide quality management activities. The purpose of this study is to identify a suitable organizational diagnostic model for considering to adopt ISO 9001 quality management systems. We used the three-round delphi techniques on a panel of 30 experts. A total of 26 assessment indicators were developed through this panel. First, it is important to evaluate the strategy about quality. Second, it is important to evaluate the systems about periodically communicating quality agenda. Third, it is important to evaluate the responsibility of overall business process. In conclusion, this study empirically shows how firms can develop an organizational diagnostic model to increase their quality management systems.