• Journal of the Korean Society of Safety
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• v.29 no.6
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• pp.1-8
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• 2014

Safety certification and inspection of dangerous machines and equipments used in industries are to save lives of workers and properties involved. Cause analysis of industrial accidents is essential to prove the effectiveness of such certification and inspection. This study focuses on suggesting systematic method for cause analysis of industrial accidents associated with dangerous machines and devices. Incorporating transition from the current user-oriented indirect regulations to more manufacturer and user balanced direct regulations, suggested method coupled with safety certification, safety inspection, safety management and safety education will guarantee more effective prevention of industrial accidents.

• Journal of the Korean Society of Safety
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• v.35 no.4
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• pp.1-8
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• 2020

Intensity of accidents associated with dangerous machines and devices are (hereafter items), in general, high compared to other industrial accidents. This study focuses on cause analysis of accidents associated with items that are subject to safety certification. The method is based on automated analysis of abstracts of accidents written in descriptive format. The analysis results indicate that more than 50% of accidents associated with items are caused by technical reasons and nearly 50% of accidents were preventable. More effective prevention of industrial accidents would then be realized by safety certification at the stage of danger generation. Transition from the direct regulation on users to manufacturers is also needed to improve the effectiveness and efficiency of industrial safety system in Korea.

• Journal of the Korean Society of Safety
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• v.37 no.3
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• pp.9-15
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• 2022

The analysis of the causes of accidents in workplaces where machines and tools are used is essential to improve the effectiveness and efficiency of safety prevention policies in places of employment in Korea. The causes of workplace accidents are not fully understood mainly due to difficulties in analyzing available descriptive information. This study focuses on the automated accident cause analysis in workplaces based on the accident abstracts found in industrial accident reports written in an unstructured descriptive format. The method proposed in this paper is based on text data mining and uses the keyword search function of Excel software to automate the analysis. The analysis results indicate that the primary reason for the frequency of accidents is related to technical aspects at a stage in which dangerous situations occur in the workplace. Accidents due to managerial causes are typically observed when danger exists in the workplace; however, managerial actions play a more important role in reducing accident severity. A small company tends to use unsafe machines and devices, leading to further accidents due to technical causes, whereas managerial causes are more conspicuous as the company grows. To preclude the occurrence of accidents due to inadequate knowledge, the implementation of safety management and the provision of safety education to elderly workers at the early stage of their employment are particularly important for small companies with less than 100 workers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.901-908
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• 2012

In an intelligent automated manufacturing environment, an administrator may use M2M (Machine-to-Machine) communication to recognize machine movement and the environment, as well as to respond to any potential dangers. However, commonly used wireless protocols for this purpose such WLAN (Wireless Local Area Network), ZigBee, and Bluetooth use the same ISM (Industrial Science Medical) band, and this may cause frequency interference among different devices. Moreover, an administrator is frequently exposed to dangerous conditions as a result of being surrounded by densely distributed moving machines. To address this issue, we propose in this paper to employ a location-based frequency interference management using fingerprinting scheme in industrial environments and its advanced localization schemes based on k-NN (Nearest Neighbor) algorithms. Simulation results indicate that the proposed schemes reduce distance error, frequency interference, and any potential danger may be responded immediately by continuous tracing of the locations.

• Fire Science and Engineering
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• v.18 no.1
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• pp.18-23
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• 2004

This paper describes the minimum ignition limits for propane-air 5.25 Vol.% mixture gases in low voltage inductive circiuts. The improved effects on the ignition limit are studied by parallel safety components(resistors) for propane-air 5.25 Vol.% mixture gas in low voltage inductive circuits. The experimental devices used in this test are the IEC type spark ignition test apparatus. The minimum ignition limits are controlled by the values of current in inductive circuit. Energy supplied from electric source is first accumulated at the inductance, it's extra energy is working as ignition source of the explosive gas. The improved effects on the ignition limit are respectively obtained as the maximum rising rate of 330% by composing parallel circuits between inductance and resistor as compared with disconnecting inductance with the safety components. The more values of inductance increase the higher improved effects of ignition limit rise. The less values of resistor the higher improved effects of ignition limit rise. It is considered that the result can be used for not only data for researches and development of intrinsically safe explosion-proof machines which are applied equipment and detectors used in dangerous areas but also for datum for its equipment tests.