• KIPS Transactions on Software and Data Engineering
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• v.9 no.12
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• pp.419-430
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• 2020

This paper investigated methods to improve the forecasting accuracy of the electricity consumption prediction model. Currently, the demand for electricity has continuously been rising more than ever. Since the industrial sector uses more electricity than any other sectors, the importance of a more precise forecasting model for manufacturing sites has been highlighted to lower the excess energy production. We propose a double encoder-decoder model, which uses two separate encoders and one decoder, in order to adapt both long-term and short-term data for better forecasts. We evaluated our proposed model on our electricity power consumption dataset, which was collected in a manufacturing site of Sehong from January 1st, 2019 to June 30th, 2019 with 1 minute time interval. From the experiment, the double encoder-decoder model marked about 10% reduction in mean absolute error percentage compared to a conventional encoder-decoder model. This result indicates that the proposed model forecasts electricity consumption more accurately on manufacturing sites compared to an encoder-decoder model.

• Safety and Health at Work
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• v.13 no.3
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• pp.343-349
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• 2022

Background: In the United States, the dairy product manufacturing industry has consistently had higher rates of work-related nonfatal injuries and illnesses compared to the national average for industries in all sectors. The selection and implementation of appropriate safety performance indicators are important aspect of reducing risk within safety management systems. This study examined the leading safety indicators implemented in the dairy product-manufacturing sector (NAICS 3115) and their perceived effectiveness in reducing work-related injuries. Methods: Perceptions were collected from individuals with safety responsibilities in the dairy product manufacturing facilities. OSHA Incident Rate (OIR) and Days away, restricted and transferred (DART) rates from 2013 to 2018 were analyzed. Results: The perceived most effective leading were safety observations, stop work authority, near miss reporting, safety audits, preventative maintenance, safety inspections, safety training attendance, and job hazard analysis/safety analysis, respectively. The 6-year trend analysis showed that those implementing all eight top indicators had a slightly lower rates than those that did not implement all eight. Production focused mentality, poor training, and lack of management commitment were perceived as the leading causes of injuries in this industry. Conclusion: Collecting leading indicators with the unique interest to meet the regulatory requirements and to document the management system without the actual goal of using them as input to improve the system most probably will not lead to an effective reduction of negative safety outcomes. For leading indicators to be effective, they should be properly selected, executed, periodically evaluated and actions are taken when necessary.

• Journal of the Ergonomics Society of Korea
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• v.24 no.3
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• pp.35-41
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• 2005

The KOSHA codes H-31 and H-30 provide general guidelines to establish a prevention program for work-related musculoskeletal disorders(WMSD). Understanding of the components and practitioner needs for a WMSD prevention program is necessary for effective revision and implementation of the KOSHA codes. The present study established a comprehensive structure for a WMSD prevention program and surveyed practitioner needs for the KOSHA codes. The comprehensive prevention program structure, consisting of 7 parts(organization, education, risk management, medical management, program evaluation, and record keeping) and 90 items, was constructed by analyzing WMSD prevention guidelines published by various government agencies such as KOSHA, OSHA and NIOSH. Next, 20 practitioners, from four industry sectors(auto manufacturing, auto part manufacturing, shipbuilding, and machinery), working in a safety and health department or labor union, were interviewed to collect opinions for the KOSHA codes in terms of relevance, government support, and additional information needed. Guidelines of the KOSHA codes requiring modifications and government supports were identified, which can be used to revise the KOSHA codes and to establish a government policy to promote the implementation of the KOSHA codes. Lastly, the survey revealed that integrated, customized, quantitative, and case information for WMSD prevention is additionally needed, which can be used as design guidelines for a WMSD prevention program manual for practitioners.

• Journal of Technology Innovation
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• v.15 no.1
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• pp.203-233
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• 2007

This study investigates how characteristics in the value-chain industrial cluster affect the R&D investment and the output of firms in each industries. For this, we try to extract the inter-industrial networking structure from the input-output table in which 17 manufacturing sectors are included. In particular, we will give shape to the "unit structure" which shows the intermediary flows of goods and services between industries in order to get an unit of final demand in a certain industry. Using this "unit structure", we can try the inter-industrial networking analysis and get some indices of centrality and centralization related to the characteristics of each industries in the value-chain industrial cluster. The results show that the centrality in the value-chain industrial cluster does not have any consequence for the R&D investment and the output in each industries. However, there is a correlation between the centralization in the value-chain industrial cluster and the R&D investment and the output of firms in each industries. These results may be very suggestive in bringing up a new frame of industrial cluster policy in a macro level.

• Industrial Engineering and Management Systems
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• v.4 no.2
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• pp.129-135
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• 2005

Continuous quality improvement through process refinement is a must for survival of all industries in the contemporary market place. This is true for both manufacturing and service sectors. While manufacturing has spearheaded quality efforts, the service sector has lagged behind primarily because of inherent difficulties. Customer satisfaction is perhaps the most important performance measure for service quality. There are a number of quality dimensions in service quality, such as reliability, responsiveness, assurance, empathy, and tangibles. An issue of concern is ‘how can one have a unified measure of service quality across all the dimensions?' The intent of this paper is to determine if the Analytical Hierarchy Process (AHP) method could be used to derive a single quality index. AHP is a quantitative technique that structures a multi-attribute, multi-person and multi-period problem hierarchically so that solutions are facilitated. This paper presents the development of an AHP model and the derivation of a Quality Index through it. The model is used in a hypothetical case and a quality index was developed. The advantages of using such a technique are discussed.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.16 no.1
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• pp.117-124
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• 2020

3D printing is a technology that has significantly grown in recent years, particularly in the aerospace, defense, and medical sectors where it offers significant potential cost savings and reduction of the supply chain by allowing parts to be manufactured on-site rather than at a distance supplier. In nuclear industry, 3D printing technology should be applied according to the manufacturing trend change. For the application of 3D printing technology to the nuclear power plant, several problems, including the absence of code & standards of materials, processes and testing & inspection methods etc, should be solved. Preemptively, the improvement of reliability of 3D printing technology, including mechanical properties, structural performance, service performance and aging degradation of 3D printed parts should be supported. These results can be achieved by collaboration of many organizations such as institute, 3D printer manufacturer, metal powder supplier, nuclear part manufacturer, standard developing organization, and nuclear utility.

• Journal of Mechanical Science and Technology
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• v.14 no.4
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• pp.380-392
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• 2000

A typical production-distribution system consist of three main echelons representing the retailer, distributors, and a factory each with an on-site warehouse. The system is sufficiently general and realistic to represent many industrial situations. However, decision functions and parameters have been selected to apply particularly to the production and distribution of consumer durables. The flows included in the model are materials, orders, and those information flows needed to support the material and order-rate decisions. In this work, a realistic production-distribution system has been used as a basic model, which consists of three sectors: retailer, distributor, and factory. That system is a nonlinear 25th-order continuous system interconnected between the echelons. Using a modern control algorithm, a typical multi-echelon production-distribution system using a dynamic controller is numerically simulated in the nominal plant and in the perturbed plant when the piecewise constant manufacturing decision is limited by a factory manufacturing upper-limit due to capital equipment, manpower, and factory lotsize.

• Korea Trade Review
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• v.45 no.1
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• pp.101-118
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• 2020

This study aims to quantify the effects of non-tariff measures (NTMs) on exports in the Korean manufacturing industry. To do this, we employ product-level export data that includes information about whether or not a product is affected by NTMs. One of the main results is that NTMs (SPS/TBT) on average led to reduction in Korean exports. However, the effects of NTMs differed depending on the income level of the NTM-imposing country. The NTMs imposed by high-income countries, such as U.S.A. and Japan, were found to impede Korean exports, whereas the export effect of NTMs imposed by low-income countries such as China was found to not be statistically significant. In addition, the results analyzed based across industries, income level, and types of NTMs are as follows. First, NTMs imposed on textile-related products generally hindered exports regardless of the type of NTMs, but its negative impact on exports was noticeable in the case of NTMs originating from high-income countries. On the other hand, chemical product-related NTMs were found to lead to an increase in Korean exports, and it had a positive effect in the case of SPS imposed by low-income countries. In other industries except for textile- and chemical-related products, the effects of NTMs on exports were either statistically insignificant or showed inconsistent patterns.

• Journal of the Korean institute of surface engineering
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• v.57 no.3
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• pp.208-213
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• 2024

With the development of industry, miniaturization and densification of semiconductor components are rapidly progressing. Particularly, as demand surges across various sectors, efficiency in productivity has emerged as a crucial issue in semiconductor component manufacturing. Maximizing semiconductor productivity requires real-time monitoring of semiconductor processes and continuous reflection of the results to stabilize processes. However, various unexpected variables and errors in judgment that occur during the process can cause significant losses in semiconductor productivity. Therefore, while the development of a reliable manufacturing system is important, the importance of developing sensor technology that can complement this and accurately monitor the process is also growing. In this study, conducted a basic research on the concept of diagnostic sensors for thickness based on the physical changes of thin films due to etching. It observed changes in resistance corresponding to variations in thin film thickness as etching processes progressed, and conducted research on the correlation between these physical changes and thickness variations. Furthermore, to assess the reliability of thin film thickness measurement sensors, it conducted multiple measurements and comparative analyses of physical changes in thin films according to various thicknesses.

• Journal of Korea Technology Innovation Society
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• v.19 no.3
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• pp.545-571
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• 2016

The development of ICT brings a big change in manufacturing industries, and new information technology such as IoT, AR, and big data was applied on manufacturing process. As a result, the concept of smart factory has been introduced as a new manufacturing paradigm. In fact advanced countries like USA, Germany, and Japan have actively introduced smart factory in their manufacturing industries such as electronic, automobile, machinery, to improve production efficiency and quality. The manufacturing environment has been changed into flexible system, so that smart factory will be leading future manufacturing industries. Thes changes have more severe influence on Korean manufacturing industries. Mny industrial companies, have a strong interest in smart factory and they, particularly big enterprises, have been adopting smart factory to increase their manufacturing efficiencies. However, Korean small and medium-sized enterprises (SMEs) have many financial and technological difficulties so that the diffusion of smart factory in Korean SMEs has not been satisfiable up to present. However, smart factory is very important for enhancing their competitiveness in global market. Therefore, this study aims at identifying the standardization strategy of smart factory in so-called Korean 'roots industry' by presuming that the standardization will activate the diffusion of smart factory among Korean SMEs. For this purpose, first, this study examines the competitiveness of SMEs, especially in 'roots industry' and identifies the necessity of diffusion of smart factory among those SMEs. Second, based on the active review on the existing literature, this study identifies four factor groups that would influence the adoption or diffusion of standardized smart factory. They are technological, organizational, industrial and policy factors. Third, using those four factors, this study made two comprehensive case analyses on the adoption and diffusion of smart factory. These two companies belong to molding sector which is one of the important six sectors in 'root industry'. Finally, based on the theoretical and empirical analyse, this study suggests four strategies for activating the standardization of smart factory; international standardization, government-leading standardization, firm-leading standardization, and non-standardization.