• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.130-138
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• 2023

The selection of the correct examination variables for diagnosing heart disease provides many benefits, including faster diagnosis and lower cost of examination. The selection of inspection variables can be performed by referring to the data of previous examination results so that future investigations can be carried out by referring to these selected variables. This paper proposes a model for selecting examination variables using an Artificial Bee Swarm Optimization method by considering the variables of accuracy and cost of inspection. The proposed feature selection model was evaluated using the performance parameters of accuracy, area under curve (AUC), number of variables, and inspection cost. The test results show that the proposed model can produce 24 examination variables and provide 95.16% accuracy and 97.61% AUC. These results indicate a significant decrease in the number of inspection variables and inspection costs while maintaining performance in the excellent category.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.45-56
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• 1995

The method of lot by lot quality protection for sampling inspection by variables is widely used in quality control. In case of sampling inspection being done repeatedly, one can use the information from the previous sampling inspection to improve current estimates. This article shows that empirical Bayes estimator is superior to the usual sample mean in repeated sampling inspection by variables.

• Proceedings of the Safety Management and Science Conference
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• 2005.11a
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• pp.377-381
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• 2005

This paper discusses the features of the ANSI/ASQ Z1.9-2003, Sampling Procedures and Tables for Inspection by Variables. This system is based on the MIL-STD-414.

• Journal of Korean Society for Quality Management
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• v.23 no.1
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• pp.1-14
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• 1995

ISO 3951 (1989) Sampling Procedures and Charts for Inspection by Variables for Percent Nonconforming is an acceptable quality level (AQL) type sampling scheme. Sample size code letters and inspection levels in this International Standard correspond to those given in the ISO 2859 (1989), a standard for sampling plans by attributes. Two acceptance sampling procedures can be used ; tabular and graphical methods. The graphs could be used in less critical applications while the tabular method would be available for those familiar with MIL-STD-414 tables and to confirm the results of the graphs when needed. The sampling procedures of the ISO 3951 are matched to the ISO 2859 to enable us to move between them. Composite OC and ASN curves are given for AQL 2.5% and code letter F.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.531-538
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• 2017

In the case of hydraulic pressure type fuse, we accept or reject certain product lots by considering the number of defective products in the operating pressure test. Generally, this procedure, known as 'The inspection by attributes', has been most commonly used in the field of quality assurance of products. However, the method of inspection by attributes suffers because it tests more samples than inspection by variables. Even though the quality of the products has remained stable in the process condition, the same number of samples is required for every lot, which wastes time and money. This paper suggests that the lot acceptance procedure is changed from inspection by attributes to inspection by variables. We can calculate the statistical tolerance percent of defectives and compare this to the Acceptable Quality Level (AQL) in order to save money and time. It is also easier to monitor and control the quality of products by using the process capability index and x-bar charts. In conclusion, the procedure delivers mutual benefit to both the customer and the producer by securing high quality products and reference data.

• Journal of Korean Academy of Nursing
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• v.28 no.3
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• pp.550-562
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• 1998

The purpose of this study was to test the Theory of Planned Behavior in the prediction of contraceptive behavior among married women. This study used a descriptive correlational design to examine the relationships among the study variables. Eighty married women in Seoul and Kyungki-do participated in this study, Research instruments used were the tool for measuring TPB variables search as attitude toward contraception, subjective norm, perceived behavioral control, and intention ; and the tool for measuring contraceptive behavior. The former was modified by the researcher according to Ajzen & Fishbein(1980)'s guidelines for tool development and Jee (1993)'s tool. The latter was developed by the researcher Data was collected from July 20, 1996 to October 25, 1996. The results are as follows ; The three factors, attitude, subjective norm and perceived behavioral control of contraception can explain 30% of the variance in contraceptive intention. Inspection of path coefficient for each of the three predictor variables revealed that subjective norm and perceived behavioral control were the predictor variables on intention, while attitude was not. ; and intention and percevied behavioral control factors can explain 42% of the variance in contraceptive behavior. Inspection of path coefficient for each of the two predictor variables revealed that intention and perceived behavioral control were the predictor variables on behavior. In conclusion, this study identified that Theory of Planned Behavior was a useful model in the prediction of contraceptive behavior, and the contraceptive service program based on the TPB variables would be an effective nursing intervention for the change in contraceptive behavior.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.187-193
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• 1996

This paper presents a new approach to modify the traditional method for sampling inspectionby variables to suit undesired measurement conditions. On the basis of a systematic analysis of the effects of measurement errors on different types of acceptance schemes this paper gives two modified equations for revising the sampling size η and the acceptability constant $textsc{k}$ to form a new acceptance scheme (η'$textsc{k}$) under undesired measurement conditions. It has proved that the new method is suitable to different types of sampling inspection by variables including that for mean value and that for percent defective. The new acceptance scheme based on the proposed technique provides an engineering feasibility to replace the traditional scheme to suit undesired measurement conditions.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.1
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• pp.19-32
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• 2002

This paper examines the effect of the producer-supplier quality contract parameters and the magnitude of the quality related variables on the quality of the final products. Our analysis focuses on the parties' equilibrium behavior In a quality game environment where the supplier should choose among the two production technologies, one requiring high cost but producing high quality Parts and the other requiring low cost but producing low quality parts and where the producer should decide whether to do the inspection of the parts. The game framework is employed to depict the potential conflicts existing between the Producer and the supplier because the Producer can not observe the supplier's choice and each party wants the other to bear the cost of producing high quality products. In our model, we specifically consider the competitive situation where the producer competes with a firm producing the same product. We employ the market share attraction model to Incorporate the competitive situation and completely characterize the equilibrium by using the Nash equilibrium concept for the game solution. Our results show that the equilibrium depends on the contract terms and the magnitude of the quality related variables. Compared to the non-competitive situation, the probability of producer's Inspection and the probability of supplier's choosing the high quality technology increases in a competitive situation. This is true even when the competitor's quality is lower than the producer's lowest. As a result, the quality of the final product increases In a competitive situation. And as the failure cost borne by the supplier increases, the probability of choosing the high quality technology Increases and the probability of inspection decreases. The net effect of this results in the decrease of the final product quality.

• Journal of Korean Society for Quality Management
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• v.43 no.3
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• pp.453-466
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• 2015

Purpose: The purpose of this study is to design a systematic method to estimate optimal operation conditions of design variables for an electronic device alignment system. Method: The 2-level factorial design and the central composite design are used in order to plan experiments. Based on the experiment results, a regression model is established to find optimal conditions for the design variables. Results: 3 of 5 design variables are selected as major factors that affect the alignment system significantly. The optimized condition for each variable is estimated by using a sequential experiment plan and a quadratic regression model. Conclusion: The method designed in this study provides an efficient and systematic plan to select the optimized operation condition for the design variables. The method is expected to improve inspection accuracy of the system and reduce the development cost and period.

• Journal of the military operations research society of Korea
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• v.18 no.1
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• pp.110-127
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• 1992

In the preventive replacement policies of system that the failure can be detected through only periodic inspection, there is a penalty cost associated with the lapsed time between system failure and its detection. The system under study is replaced if the system fails before $n^{th}$ inspection, otherwise, preventive replacement is performed at the $n^{th}$ inspection. The decision variables are the inspection interval and the period of preventive replacement. This study presents the optimal preventive replacement policy that minimizes the long-run expected cost per unit time.