• Journal of Korean Society for Quality Management
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• v.22 no.4
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• pp.79-101
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• 1994

In modern manufacturing, a product consists of many components created by different processes. Variations in the individual component dimensions and in the processes may result in unacceptable final assemblies. Thus, engineers have increased pressure to properly set tolerance specifications for individual components and to control manufacturing processes. When a proper variation stack-up analysis is not performed for all of the components in a functional system, all component parts can be within specifications, but the final assembly may not be functional. Thus, in order to improve the performance of the final assembly, a proper variation stack-up analysis is essential for specifying dimensional tolerances and process control. This research provides a detailed case example of the use of variation stack-up analysis using a Monte Carlo simulation method to improve the defect rate of a complex process, which is the commutator brush track undercut process of an armature assembly of a small motor. Variations in individual component dimensions and process mean shifts cause high defect rate, Since some dimensional characteristics have non-normal distributions and the stack-up function is non-linear, the Monte Carlo simulation method is used.

• Journal of Environmental Impact Assessment
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• v.26 no.6
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• pp.418-430
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• 2017

The quality of surface water is a very important issue to use various demands like as drinking water, industrial, agricultural and recreational usages. There has been an increasing demand for monitoring water quality of many rivers by regular measurements of various water quality variables. However precise and effective monitoring is not enough, if the acquired dataset is not analyzed thoroughly. Therefore, the aim of this study was to estimate differences of seasonal and regional water quality using multivariate data analysis for each investing tributaries in Han River. Statistical analysis was applied to the data concerning 11 mainly parameters (flow, water temperature, pH, EC, DO, BOD, COD, SS, TN, TP and TOC) for the time period 2012~2016 from 12 sampling sites. The seasonal water quality variations showed that each of BOD, TN, TP and TOC average concentration in spring and winter was higher than that of summer and fall, respectively. In summer each flow rate and average concentration of SS was higher than any other seasons, respectively. The correlation analysis were explained that EC had a strong relationship with BOD (r=0.857), COD (r=0.854), TN (r=0.899) and TOC (r=0.910). According to principal component analysis, five principal components (Eigenvalue > 1) are controlled 98.0% of variations in water quality. The first component included TP, DO, pH. The second component included EC, TN. The third component included SS. The fourth component included flow. The last component included Temp. Cluster analysis classified that spring is similar to fall and winter with water quality parameters. AnyA, WangsA, JungrA and TancA were identified as affected by organic pollution. Cluster analysis derived seasonal differences with investigating sites and better explained the principal component analysis results.

• The KIPS Transactions:PartD
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• v.10D no.5
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• pp.745-752
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• 2003

The component-based development methodology becomes famous as the reuse technology for independence and productivity of software development It is necessary component metrics for component-based systems, because It should be measurable to improve the quality of the software. Hence, in this paper, we propose component cohesion and coupling metrics which is reflected in characteristics of component. The operation use value is calculated by the information of classes interface commonly uses to offer the component's service. And, the operation similarity value is calculated by the operations use value. Component cohesion and coupling is calculated by the operation similarity and based of the information which is extracted in the analysis phase. And, we examine the necessity of component metrics in comparison with object-oriented metrics.

• The Journal of Society for e-Business Studies
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• v.7 no.3
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• pp.219-240
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• 2002

The various software engineering techniques have been appeared in order to cope with the software crisis since 1980's. Currently, the research against the techniques likes the Design pattern, Component which improve the software's re-use are spread out. Also S/W Development Process are interested intensively which attempts the quality and a increasing productivity of software development with the basic policy. The design pattern is the solution against the problem which occurs repeat in a specific area. Many design pattern are developed and researched, but the method which accommodates the developed design pattern efficiently in the phase of analysis and design software development process is not good enough, so it is the actual applying technique is difficult. In this paper we suggest and the “UML components+” which is a efficient component development process from customizing EJB based the J2EE using the “UML Components” which is a component development methodology. Applying J2EE pattern efficiently with UML components+, there is a possibility of efficiency in the component development based pattern.

• ETRI Journal
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• v.31 no.3
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• pp.304-314
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• 2009

Component-based software reuse has been generally regarded as a promising approach to improving software productivity and quality within software development. However, progress in component-based software reuse has been slower than expected. Much of the software reuse literature points to the lack of software components that can maximize users' benefits as the most important source of the slow progress. Considering that the underlying processes behind component-based software reuse are strikingly similar to commercial software marketing, this paper attempts to identify the aspects of software components that consumers value and to establish relationships between the identified aspects and consumer behavior in the software component market. More specifically, this paper focuses on the perceived subjective features of software components. This study was conducted in a web-based artificial market environment called "SofTrade."

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.143-148
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• 2022

Component-based software development (CBD) is a methodology that has been embraced by the software industry to accelerate development, save costs and timelines, minimize testing requirements, and boost quality and output. Compared to the conventional software development approach, this led to the system's development being completed more quickly. By choosing components, identifying systems, and evaluating those systems, CBSE contributes significantly to the software development process. The objective of CBSE is to codify and standardize all disciplines that support CBD-related operations. Analysis of the comparison between component-based and scripting technologies reveals that, in terms of qualitative performance, component-based technologies scale more effectively. Further study and application of CBSE are directly related to the CBD approach's success. This paper explores the introductory concepts and comparative analysis related to component-based software engineering which have been around for a while, but proper adaption of CBSE are still lacking issues are also focused.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.119-124
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• 2024

Component-based software development (CBD) is a methodology that has been embraced by the software industry to accelerate development, save costs and timelines, minimize testing requirements, and boost quality and output. Compared to the conventional software development approach, this led to the system's development being completed more quickly. By choosing components, identifying systems, and evaluating those systems, CBSE contributes significantly to the software development process. The objective of CBSE is to codify and standardize all disciplines that support CBD-related operations. Analysis of the comparison between component-based and scripting technologies reveals that, in terms of qualitative performance, component-based technologies scale more effectively. Further study and application of CBSE are directly related to the CBD approach's success. This paper explores the introductory concepts and comparative analysis related to component-based software engineering which have been around for a while, but proper adaption of CBSE are still lacking issues are also focused.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.414-416
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• 2003

As environmental conditions for memory products are increasingly high speed/high density, adopting diverse system configuration, it's more and more difficult for current component tester to adopt the actual condition of field application. If system test screening is realized in component level, test coverage failure can be made more secured in the initial stage, evaluation cost can be reduced and the effectiveness of investment for the facility can be maximized. Based on the above background, component automatic system tester was developed and showed off satisfactory results per each memory device family. In this paper, component quality stabilization strategy and cost saving for tester investment through future Quality monitoring and application to mass production will be presented.

• Ocean and Polar Research
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• v.33 no.3
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• pp.291-301
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• 2011

To investigate major factors controlling variations in water quality, principal component analysis and cluster analysis were used to analyze data sets of 12 parameters measured at 23 sampling stations of Jinhae Bay during winter and spring. Principal component analysis extracted three major factors controlling variations of water quality during winter and spring. In winter, major factors included freshwater input, polluted material input, and biological activity. Whereas in spring they were polluted material input, freshwater input, and suspended material input. The most distinct difference in the controlling factors between winter and spring was that the freshwater input was more important than the polluted material input in winter, but the polluted material input was more important than the freshwater input in spring. Cluster analysis grouped 23 sampling stations into four clusters in winter and five clusters in spring respectively. In winter, the four clusters were A (station 5), B (stations 1, 2), C (station 4), and D (the remaining stations). In spring, the five clusters included A (station 5), B (station 1), C (station 3), D (station 6), and E (the remaining stations). Intensive management of the water quality of Masan and Hangam bays could improve the water quality of Jinhae Bay since the polluted materials were mainly introduced into Jinhae Bay through Masan and Hangam bays.

• Journal of Environmental Health Sciences
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• v.35 no.6
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• pp.517-525
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• 2009

The water quality of Lake Shihwa had been rapidly deteriorating since 1994 due to wastewater input from the watersheds, limited water circulation and the lack of a wastewater treatment policy. In 2000, the government decided to open the tidal embankment and make a comprehensive management plan to improve the water quality, especially inflowing stream water around Shihwa and Banwol industrial complex. However, the water quality and microbial community have not as yet been fully evaluated. The purpose of this study is to investigate the influent water quality around the industrial area based on chemical and biological analysis, and collected surface water sample from the Siheung Stream, up-stream to down-stream through the industrial complex, Samples were collected in July 2009. The results show that the downstream site near the industrial complex had higher concentrations of heavy metals (Cu, Mn, Fe, Mg, and Zn) and organic matter than upstream sites. A combination of DGGE (Denaturing Gradient Gel Electrophoresis) gels, lists of K-WQI (Korean Water Quality Index), cluster analysis, MDS (Multi-Dimensional Scaling) and PCA (Principal Component Analysis) has demonstrated clear clustering between Siheung stream 3 and 4 and with a high similarity and detected metal reducing bacteria (Shewanella spp.) and biodegrading bacteria (Acinetobacter spp.). These results suggest that use of both chemical and microbiological marker would be useful to fully evaluate the water quality.