• Journal of Environmental Health Sciences
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• v.3 no.1
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• pp.27-44
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• 1976

This study was carried out to evaluate the harmful factors in working environments and to investigate the labor productivity after improvement of environments, surveying 93 industrial establishments of 10 industries located in Youngdeungpo industrial area in Seoul. The results obtained were as follows: 1) The highest noise level of 125dB(A) was indicated at the rolling process of transport equipment manufacturing industry. 2) The best illumination level was shown in precise machinery industry and the worst was indicated in rubber products, metallic products and transport equipment manufacturing industries. 3) Thermal conditions were above threshold limit value (TLV) at more than two processes of all industries except printing industry. 4) The highest dust concentration was determined in textile and wearing manufacturing industry. 5) Organic solvents were detected at 52 processes in 93 industrial establishments and 33 processes of them showed higher than TLV. The results about harmful chemicals were as follows: a) sulfur dioxide ($SO_2$)was determined higher than TLV on welding process of metallic product manufacturing industry and heat treatment process of transport equipment manufacturing industry. b) Carbon monoxide (CO) concentration was 700ppm at heat treatment process of transport equipment manufacturing industry, indicating 14 times of TLV. c) vinylchloride concentration in the air of PVC raw material mixing process and PVC preparation process of chemical product manufacturing industry was determined higher than TLV. d) Hydrochloride (HCl) concentration in the air of wire expanding process of transport equipment manufacturing industry was determined higher than TLV. 7) Higher values of lead concentration than TLV were determined at lead welding metallic product manufacturing industry and type planting process of process of printing industry, $1.8mg/m^3$ and $0.3mg/m^3$ respectively. 9) 22, 968 of 52, 855 workers (i.e. 43.5%) in 93 industries were exposed to various harmful agents. 10) It was found that the improvement of illumination in electric apparatus manufacturing industry (from 20~40 lux to 420 lux) resulted in an increase in productivity of 6.5% per capita and a decrease in faulty products of 19%. 11) Improvement of environments using local exhaust ventilation system resulted in a decrease of harmful substances lower than TLV and an increase in productivity of 11.4%. 12) Improvement of shovelling tools based on ergonomics resulted in a reduction in energy expenditure of 25.3% and an increase in productivity of 32.2% per capita.

• International Journal of Contents
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• v.13 no.2
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• pp.57-65
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• 2017

Recently, due to the significance of Industry 4.0, the manufacturing industry is developing globally. Conventionally, the manufacturing industry generates a large volume of data that is often related to process, line and products. In this paper, we analyzed causes of defective products in the manufacturing process using the decision tree technique, that is a well-known technique used in data mining. We used data collected from the domestic manufacturing industry that includes Manufacturing Execution System (MES), Point of Production (POP), equipment data accumulated directly in equipment, in-process/external air-conditioning sensors and static electricity. We propose to implement a model using C4.5 decision tree algorithm. Specifically, the proposed decision tree model is modeled based on components of a specific part. We propose to identify the state of products, where the defect occurred and compare it with the generated decision tree model to determine the cause of the defect.

• Journal of the Korean Society for Precision Engineering
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• v.34 no.1
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• pp.19-22
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• 2017

This paper describes the efficient equipment maintenance that can offer the exact time for repair and change of component in root industry. A conventional method offered the fixed time for repair and change of component because the method is based on early guarantee specification of the component. However the operating condition of manufacturing field is often under worse condition than early guarantee condition for high productivity. So, most components can't use until early guarantee time due to the operation of various different condition. Therefore we suggest the useful method for efficient equipment-maintenance by manufacturing-field analysis and feedback database. For this, the classification of root industry and related equipment is performed and then the detail classification of the process and component for equipment maintenance. And the monitoring module is also designed to gather data for feedback process and the environment is basically implemented for aging and reliability test.

• International Commerce and Information Review
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• v.16 no.4
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• pp.55-75
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• 2014

Non-parametric method such as technology efficiency, DEA/Window model and Malmquist Productivity Index (MPI) are used to measure efficiency and productivity of ICT (Information and Communication Technology) manufacturing industry and service industry over the period 2007-2011. The results of this paper indicate following: (1) Technology efficiency of the ICT manufacturing industry were found as the range of 0.34 and 0.39 over the sample period. Technology efficiency of the ICT service industry were found as the range of 0.16 and 0.20 over the sample period. (2) The geometric average of the Malmquist TFP indexes on ICT manufacturing industry indicated the productivity improvement an average of 8.3 percent. The geometric average of the Malmquist TFP indexes on ICT service industry indicated the productivity improvement an average of 1.6 percent. (3) TIER analysis result on ICT manufacturing industry showed that optimal bench marking made by storage devices${\rightarrow}$wireless communication equipment${\rightarrow}$broadcasting equipment${\rightarrow}$radio, recording and playback devices${\rightarrow}$computers, printers, video and audio-visual equipment path. TIER analysis result on ICT service industry indicated that optimal bench marking made by computers and packaged software${\rightarrow}$wired communication${\rightarrow}$communication, information, detection equipment${\rightarrow}$consulting and construction for computer systems integration${\rightarrow}$industrial machinery and equipment rental${\rightarrow}$telecommunications reseller${\rightarrow}$system software development and delivery${\rightarrow}$hosting path.

• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.187-201
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• 2009

Semiconductor industry is based on equipment industry and timing industry. In particular, semiconductor process is very complex and as semiconductor-chip width tails and is becoming equipment gradually more as a high technology. Equipment operation is primarily engaged in semiconductor manufacturing (engineers and operator) of being conducted by, equipment errors have also been raised. Equipment operational data related to the error of korea occupational safety and health agency were based on data and production engineers involved in the operator's questionnaire was drawn through the error factor. Equipment operating in the error factor of 9 big item and 36 detail item detailed argument based on the errors down, and 9 big item the equipment during operation of the correlation error factor was conducted. Each of the significance level was correlated with the tabulation and analysis. Using the maximum correlation coefficient, the correlation between the error factors to derive the relationship between factors were analyzed. Facility operating with the analysis of error factors (big and detail item) derive a relationship between the model saw. The end of the operation of the facility in operation on the part of the two factors appeared as prevention. Safety aspects and ergonomics aspects of the approach should be guided to the conclusion.

• Journal of the Korean Society of Safety
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• v.38 no.1
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• pp.34-41
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• 2023

In this study, S food manufacturing business located in Chungbuk was selected as the subject, and the transition in insulation resistance in major electrical equipment used in this food manufacturing business was analyzed for 4 years (2018-2021). It was confirmed that the insulation resistance decreased over time for all 18 electrical facilities. Insulation resistance changed due to environmental influences such as load characteristics and ambient temperature. Particularly in the case of the food manufacturing industry, it was confirmed that the decrease started after 2 years, although it varied depending on equipment and environmental influences. Furthermore, it was confirmed that management through predicting the management cycle of electrical equipment is possible by deriving a regression equation through regression analysis of insulation resistance measurement values.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.5
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• pp.1369-1379
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• 2015

This study attempted an AHP analysis through interview with experts in the industries and questionnaire survey on recognition of organization members and future strategic development direction in order to upgrade shipbuilding equipment industries to marine plant equipment industries. Key research results are as follows. First, according to analysis on relative priority between three aspects on acceleration of shipbuilding equipment industries, importance was shown in the order of acceleration of internal competence, acceleration of manufacturing technology, and acceleration of supply chain, which means that the aspect on acceleration of internal competence had relatively higher importance. Second, as for relative importance of detailed item evaluation per respective aspect, it was found that development of core competencies was high from the aspect on acceleration of internal competence, higher value-addition was high from the aspect on acceleration of manufacturing technology, and IT infrastructure construction was high from the aspect on acceleration of supply chain.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.5
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• pp.486-492
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• 2013

Energy cost has been increasing rapidly to comply with environmental regulations worldwide and the manufacturing industry who consumes more than half of the total energy needs to improve their cost competitiveness considering environmental costs. Machine tools are essential elements in manufacturing industry and efforts have been made recently to increase their energy efficiency mainly by German and Japanese machine tool builders. In this paper, trends in energy saving technology are described on the hardware and software sides of peripheral equipment of machine tools. In addition, the power consumption of a machining center is measured and analyzed to develop a software-based standby strategy for energy saving with peripheral equipment of machine tools.

• Journal of Distribution Science
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• v.14 no.10
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• pp.21-27
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• 2016

Purpose - This study analyzes economic relations and mutual influence in the global equipment manufacturing industry (EMI) and China's influence. Research design, data, and methodology - Data were collected from the World Input-Output Database (WIOT), looking at 16 countries. The sample time period was 2002-2011. Influence and motivation coefficients were calculated. Results - 1) China's EMI showed a very strong influence coefficient, even surpassing world industrial powers like Japan, the USA, Germany, and Korea. 2) As for influence on added-value, China's EMI motivation coefficient was ranked third in 2011, which meant it had a negligible effect on added-value. 3) From 2002 to 2011, both the influence and motivation coefficients of China's EMI rose. Conclusions - China's EMI has strong influence and motivation coefficients. It has a significant impact on the world EMI, especially on the total output of the global EMI. Additionally, during 2002 to 2011, the ranking of China's EMI motivation coefficient improved year over year, and its economic efficiency obviously improved. By 2011, China's EMI's international influence was second only to the US and Japan.

• Journal of Industrial Convergence
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• v.12 no.2
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• pp.16-23
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• 2014

The aim of this study is to find the strategic industries that fulfills the on-site demands of the Gyeonggi province region related to the advancement and development of the local industries. As the results of the analysis, the 4 major strategic industries in the Gyeonggi province region were determined to be (1) electronic component, computer, visual, acoustic and telecommunication equipment manufacturing, (2) pulp, paper and paper product manufacturing, (3) medical substances and pharmaceutical product manufacturing, and (4) rubber and plastic product manufacturing. The industry of concordance between the 4 major strategic industry of the Gyeonggi province determined in this Study and the 13 future growth engine industry of Korea was the area of intelligent semiconductor. Accordingly, it was analyzed that there is a need to strategically cultivate the electrical and electronic telecommunication device industry, which is ranked the $1^{st}$among the strategic industries of Gyeonggi province by generating synergic effects with the policy of the government for nurturing of intelligent semiconductor industry.