• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.15 no.3
• /
• pp.153-159
• /
• 2005

The purpose of this study was to assess the ergonomic risks of lifting tasks in a marine diesel engine manufacturing industry using the National Institute for Occupational Safety and Health(NIOSH) Revised Lifting Equation(NLE). Average Lifting Index(LI=Weight of Load/Recommended Weight Limit) of a total number of 45 lifting tasks was $1.6{\pm}0.7$. The LIs were above 1 at 34 tasks(75.6%), and above 2 at 11 tasks(24.4%). Parts management showed the highest average LI value (LI=2.3) in all departments, which resulted from high frequency and heave load of lifting. The common and significant ergonomic risk factors in the processes were the heavy weight of diesel engine parts and the long horizontal distance. In addition, some lifting tasks had such potential risk factors as the long vertical distance, the high frequency of lifts or the long work duration.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.5
• /
• pp.1089-1097
• /
• 2019

An era of smart manufacturing is coming through the rapid development of information and communication technology. As a result, many companies have begun to utilize a variety of hardware and software for the efficient business of the manufacturing process. At this time, the hardware and software used are supplied through manufacturing and distribution processes. These supply processes are exposed to a variety of security threats. As the recent cases of supply chain attacks have increased, foreign countries are establishing supply chain management systems and managing supply chain risks. In Korea, on the other hand, there was research on supply chain risk management in some fields. In this paper, we emphasizes the necessity of supply chain risk management through supply chain attack cases. In addition, we analyze trends of foreign supply chain management system and explains the necessity of domestic supply chain security strategy.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.64 no.4
• /
• pp.220-230
• /
• 2015

Rolling stock RAMS is a field of engineering which integrates reliability, availability, maintainability and safety (RAMS) characteristics into an inherent product design property through rolling stock system engineering process. It is implemented to achieve operational objectives successfully, and recently the RAMS has become a rapidly growing engineering discipline because it has a great potential to ensure safety and improve cost effectiveness. However, the Korean rolling stock industry has not yet implemented RAMS management in the rolling stock engineering process, despite the issue having been addressed since the introduction of the KTX. Thus, this paper discusses the processes, methods and techniques for RAMS assessment in three parts. Firstly, it outlines a process of the overall RAMS performance assessment for achieving technical RAMS design criteria. Secondly, it discusses a process for assessing the operational RAM and allocating the RAM. This paper also proposes a model for assessing safety-based risk management, which includes five analytic techniques for identifying the causes and consequences of a system failure. Finally, a case example is provided for the risk assessment of the pneumatic braking device.

• Journal of architectural history
• /
• v.21 no.2
• /
• pp.37-52
• /
• 2012

This research has set up the fire fighting general index for Fire fighting of Crowded Wooden Building Cultural Asset which is composed of traditional wooden building instinct or complex. The results of this study are as follows. First, Fire fighting general index for crowded wooden building cultural asset, it is necessary to set fire fighting priority by considering fire risk and cultural asset characteristic and establish the system to cope with fire disaster in the most effective way by arranging facilities with restricted resource. Second, Fire risk is the index to draw fire and spread risk of cultural asset by applying index calculation processes such as fire load, burning velocity and ignition material spread characteristic to various aspects such as individual building and complex and combining their results. Cultural asset importance index consists of individual building evaluation, publicity security degree, area importance evaluation and historical landscape degree evaluation. Third, for each index combination process, weight of each index is drawn on the basis of AHP analysis result that is performed to the specialists of related fields. The formula to apply and combine it is prepared to apply the model to include meaning of each index and comparative importance degree.

• The Korean Journal of Applied Statistics
• /
• v.26 no.1
• /
• pp.163-185
• /
• 2013

In this paper, we investigate the need to employ long-memory volatility models in terms of Value-at-Risk(VaR) estimation. We estimate the VaR of the KOSPI returns using long-memory volatility models such as FIGARCH and FIEGARCH; in addition, via back-testing we compare the performance of the obtained VaR with short memory processes such as GARCH and EGARCH. Back-testing says that there exists a long-memory property in the volatility process of KOSPI returns and that it is essential to employ long-memory volatility models for the right estimation of VaR.

• Journal of the Korean Society of Safety
• /
• v.36 no.1
• /
• pp.56-63
• /
• 2021

The narrative texts of industrial accident reports help to identify accident risk factors. They relate the accident triggers to the sequence of events and the outcomes of an accident. Particularly, a set of related keywords in the context of the narrative can represent how the accident proceeded. Previous studies on text analytics for structuring accident reports have been limited to extracting individual keywords without context. We proposed a context-based analysis using a Natural Language Processing (NLP) algorithm to remedy this shortcoming. This study aims to apply Word2Vec of the NLP algorithm to extract adjacent keywords, known as word embedding, conducted by the neural network algorithm based on supervised learning. During processing, Word2Vec is conducted by adjacent keywords in narrative texts as inputs to achieve its supervised learning; keyword weights emerge as the vectors representing the degree of neighboring among keywords. Similar keyword weights mean that the keywords are closely arranged within sentences in the narrative text. Consequently, a set of keywords that have similar weights presents similar accidents. We extracted ten accident processes containing related keywords and used them to understand the risk factors determining how an accident proceeds. This information helps identify how a checklist for an accident report should be structured.

• Journal of the Korean Society of Safety
• /
• v.36 no.3
• /
• pp.50-59
• /
• 2021

The main purpose of accident analysis is to identify the causal factors and the mechanisms of those factors leading to the accident. However, current accident analysis techniques focus only on finding the factors related to the accident without providing more insightful results, such as structures or mechanisms. For this reason, preventive actions for safety management are concentrated on the elimination of causal factors rather than blocking the connection or chain of accident processes. This greatly reduces the effectiveness of safety management in practice. In the present study, a technique to model the correlational structure of accident risk factors is proposed by using the co-occurrence keyword network analysis technique. To investigate the effectiveness of the proposed technique, a case study involving a portable ladder fall accident is conducted. The results indicate that the proposed technique can construct the correlational structure model of the risk factors of a portable ladder fall accident. This proves the effectiveness of the proposed technique in modeling the correlational structure of accident risk factors.

• Archives of Plastic Surgery
• /
• v.48 no.3
• /
• pp.295-304
• /
• 2021

Clinical photography is an essential component of patient care in plastic surgery. The use of unsecured smartphone cameras, digital cameras, social media, instant messaging, and commercially available cloud-based storage devices threatens patients' data safety. This paper Identifies potential risks of clinical photography and heightens awareness of safe clinical photography. Specifically, we evaluated existing risk-mitigation strategies globally, comparing them to industry standards in similar settings, and formulated a framework for developing a risk-mitigation plan for avoiding data breaches by identifying the safest methods of picture taking, transfer to storage, retrieval, and use, both within and outside the organization. Since threats evolve constantly, the framework must evolve too. Based on a literature search of both PubMed and the web (via Google) with key phrases and child terms (for PubMed), the risks and consequences of data breaches in individual processes in clinical photography are identified. Current clinical-photography practices are described. Lastly, we evaluate current risk mitigation strategies for clinical photography by examining guidelines from professional organizations, governmental agencies, and non-healthcare industries. Combining lessons learned from the steps above into a comprehensive framework that could contribute to national/international guidelines on safe clinical photography, we provide recommendations for best practice guidelines. It is imperative that best practice guidelines for the simple, safe, and secure capture, transfer, storage, and retrieval of clinical photographs be co-developed through cooperative efforts between providers, hospital administrators, clinical informaticians, IT governance structures, and national professional organizations. This would significantly safeguard patient data security and provide the privacy that patients deserve and expect.

• Journal of the Korean institute of surface engineering
• /
• v.56 no.4
• /
• pp.283-287
• /
• 2023

The structures for road safety are guard rails that protect the cars and passengers. If an accident occurs on the roads after a long period of installation, it may escalate into a major disaster. In order to repair many guard rails, the existing repair method of replacing them with new ones requires enormous financial resources. To solve this problem, the G-SAVE method was developed to repair the guard rail without replacing them. This method removes the rust on the surface of the guard rail and then performs ambient-dip galvanizing coating on it without replacing the new ones. No studies or reports have yet been made on the risk assessment of harmful substances, vehicles for these entire processes. Therefore, this paper focuses on risk assessment using the PHA (Preliminary Hazard Analysis) technique and conducts risk assessment for concept design stage of the coating vehicles.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.06a
• /
• pp.201-203
• /
• 2022

Increasing global market of used electric vehicle (EV) battery encourages international firms to establish its subsidiary companies or business units specializing in battery recycling. Such kind of companies predominantly use closed loop supply chain (CLSC) for their operations of battery manufacturing and used battery recycling/reusing in global scale. However, EV battery recycling, as a relatively new industry, makes its global CLSC be exposed to various types of risks, which leads to inefficiency of supply processes and makes supply chains more complicated and vulnerable. Identifying, evaluating, and analyzing possible risks in CLSC has a great importance for optimization and increasing effectiveness for the global supply chain of used EV battery. Itwill assist to elaborate the efficient CLSC management and possible risk mitigation strategies to keep the global EV battery supply chain resilient and sustainable. This study aims to develop a conceptual framework for risk assessment in this new sector. Therefore, it will populate the framework with possible failure modes identified from various literature on EV battery recycling and closed loop supply chains so that future research can validate and utilize the conceptual framework.