• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.2
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• pp.41-51
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• 2007

We categorize quality management practices as two factors ; 'infra factor' and 'process factor.' We confirm the factors' statistical significance with empirical investigation about 167 manufacturing companies in nationwide. Moreover, we find the two factors affect positively on the manufacturing capabilities of differentiation and reliability, and on the performances as improving products and process. We prove these results with empirical method of structural equation model and AMOS program.

• Proceedings of the Safety Management and Science Conference
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• 1999.11a
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• pp.247-257
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• 1999

There are several models for process quality assurance by quality system(ISO 9000), process capability analysis, acceptance control chart and so on. When a high level process capability has been achieved, it takes a long time to monitor the process shift, so it is sometimes necessary to develop a quicker monitoring system. To achieve a quicker quality assurance model for high-reliability process, this paper presents a model for process quality assurance when the fraction nonconforming is very small. We design an acceptance control chart based on variable quality characteristic and time-censored accelerated testing. The distribution of the characteristics is assumed to be normal of lognormal with a location parameter of the distribution that is a linear function of a stress. The design parameters are sample size, control limits and sample proportions allocated to low stress. These parameters are obtained under minimization of the relative variance of the MLE of location parameter subject to APL and RPL constraints.

• International Journal of Quality Innovation
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• v.6 no.1
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• pp.74-97
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• 2005

IDEF0 is the IEEE standard for functional enterprise modeling and has been used for business process modeling or process mapping in US and Europe. But it does not reflect the potential benefits of modeling and simulation of the dynamic aspects of an enterprise or a system. On the other hand, simulation tools concentrate mostly on the simulation of material flows and are difficult to include information flows and control flows. Additionally, the simulation models that include elements such as queues, event generators and process nodes is a visual interactive representation for the model builder, but is inconvenient for the domain expert. In an attempt to fill that void, we provide an integration of business process and simulation models in this paper. An enhancement of the IDEF0, called parameterized IDEF0, is proposed and its conversion mechanism to network simulation model is developed. Using this methodology, business process models for alternative systems can be evaluated and compared through simulation on time, cost, and quality metrics. As an application of the proposed methodology, economic evaluation of EDI (Electronic Data Interchange) for time-based BPR (Business Process Redesign) is demonstrated. In addition to BPR, the developed methodology may be further integrated with ABC (Activity Based Costing), TQM (Total Quality Management), and economic evaluation of information systems.

• Journal of Korean Society for Quality Management
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• v.52 no.2
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• pp.185-199
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• 2024

Purpose: The improvement of yield and quality in product manufacturing is crucial from the perspective of process management. Controlling key variables within the process is essential for enhancing the quality of the produced items. In this study, we aim to identify key variables influencing product defects and facilitate quality enhancement in CNC machining process using SHAP(SHapley Additive exPlanations) Methods: Firstly, we conduct model training using boosting algorithm-based models such as AdaBoost, GBM, XGBoost, LightGBM, and CatBoost. The CNC machining process data is divided into training data and test data at a ratio 9:1 for model training and test experiments. Subsequently, we select a model with excellent Accuracy and F1-score performance and apply SHAP to extract variables influencing defects in the CNC machining process. Results: By comparing the performances of different models, the selected CatBoost model demonstrated an Accuracy of 97% and an F1-score of 95%. Using Shapley Value, we extract key variables that positively of negatively impact the dependent variable(good/defective product). We identify variables with relatively low importance, suggesting variables that should be prioritized for management. Conclusion: The extraction of key variables using SHAP provides explanatory power distinct from traditional machine learning techniques. This study holds significance in identifying key variables that should be prioritized for management in CNC machining process. It is expected to contribute to enhancing the production quality of the CNC machining process.

• Journal of Korean Society for Quality Management
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• v.30 no.1
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• pp.61-73
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• 2002

The Quality Function Deployment(QFD) is a Quality Management technique to maximize customers' satisfaction by reflecting customer requirements into all business processes, including concept definition, product planning, parts planning, process planning, production planning, and sales planning. The basic concept of the QFD is to translate customers' requirements appropriately into engineering characteristics, into parts characteristics, into process characteristics, and into specific requirements and activities in production. In this study, we reviewed and analyzed the application process of the QFD to the development of A2 FATC (Full Automatic Temperature Controller), an automotive component developed and produced by company A. It has been reported that by applying the QFD to the development of A2 FATC, company A. achieved 34% improvement in control robustness quality characteristic, 27% improvement in deviation quality characteristic, and 30% improvement in overall quality characteristics.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.699-704
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• 2001

Developing a component-based software requires verified and standardized software components. This paper presents a component quality management (CQM) process. The process was developed and applied to the government-sponsored trial projects that developed software components. The process is composed of four phases：quality specification, quality planning, quality control, and quality evaluation. With this process, we can establish quality goals and focus our efforts on the activities to achieve the goals. A component quality model is also suggested to transform the implicit quality requirements into the measurable quality goals and to be used for the basis when we evaluate the quality of software components against the quality goals.

• Journal of Information Technology Services
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• v.18 no.2
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• pp.75-96
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• 2019

These days, many companies use information systems as a basis for organizational management activities and as an important component of sustainable management. Thus, securing and operating a high-quality information system that can improve the efficiency of business processes is a large part of corporate competitiveness. In order to get such a critical information system, it is only possible to successfully carry out the project. Various attempts and studies have been undertaken to increase the success rate of the project. However, the reality is that the success rate is still not getting much better. In this study, the concept of quality of service, which has long been actively studied in marketing area, was applied as a new factor to enhance the project's success. In this study, project performance activities were defined as the act of providing services. A survey of 164 valid collection data was analyzed. The analysis used SPSS 23. Four process quality factors (customer participation, customer response, knowledge and skills, reliability) and 21 metrics were derived. Through this research, I hope to be the starting point of applying process quality concept as a new breakthrough to increase success rate of project.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.2
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• pp.112-119
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• 2017

Korea's national R&D projects are increasing year by year. However, it is necessary to improve the quality of R&D result. In this paper, we introduce the developing and adjusting the R&D standard process based on process approach in ETRI. It is expected that the definition of R&D standard process will contribute to improve customer satisfaction and quality of R&D result through standardization and continuous improvement activities.

• Journal of Korean Society for Quality Management
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• v.44 no.1
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• pp.109-120
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• 2016

Purpose: This study developed a method of determining priorities for evaluating and revising defense standards. Methods: The proposed data integration and refinement methods are used to obtain component reliability information and to determine the frequency of component citation based on Pareto analysis. Based on the reliability information and the frequency of cited components, the target components for quality improvement can be determined and improved using various methods, such as engineering changes, special meetings, additional training, and revising the maintenance manual. Results: Based on the proposed process, we identified components that need to be improved in order to enhance the quality and reliability. Conclusion: Our process will improve the quality and reliability of weapon systems. The proposed process can be adopted for various weapon systems to enhance their quality and reliability, and to reduce military spending.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.433-438
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• 2002

A construction model of quality management system in manufacturing industry focuses on process approach and continual improvement amongst the quality management 8 principles which are elements of quality management system of ISO 9000:2000 family standards, and proposes the model that can construct quality management system throughout the process approach as more simple and effective way in developing and applying a quality management system for characteristics of the manufacturing industry.