Flow diagram analysis of electrical fatalities in construction industry

Chi, Chia-Fen; Lin, Yuanyuan; Ikhwan, Mohamad

doi:10.1016/j.ssci.2011.12.012

Cited by 39 publications

(11 citation statements)

References 14 publications

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“…For instance, electrocutions and burns to body system and upper extremities often happened historically in exposure to electricity accidents wherein parts and material are the source of injury and small , new , nonresidential buildings are the location of accident. Though they used different methods, some studies have similarly examined the associations linking accident factors [ 65 , 66 , 67 ]. For instance, Chi et al [ 66 ] investigated fatal fall accidents to demonstrate how different types of falls are linked to specific causes; the team then suggested several prevention measures based on strong links between a cause and its consequent accident.…”

Section: Discussionmentioning

confidence: 99%

Trends in Catastrophic Occupational Incidents among Electrical Contractors, 2007–2013

Gholizadeh

Onuchukwu

Esmaeili

2021

IJERPH

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This study used methodologies of descriptive and quantitative statistics to identify the contributing factors most affecting occupational accident outcomes among electrical contracting enterprises, given an accident occurred. Accident reports were collected from the Occupational Safety and Health Administration’s fatality and catastrophe database. To ensure the reliability of the data, the team manually codified more than 600 incidents through a comprehensive content analysis using injury-classification standards. Inclusive of both fatal and non-fatal injuries, the results showed that most accidents happened in nonresidential buildings, new construction, and small projects (i.e., $50,000 or less). The main source of injuries manifested in parts and materials (46%), followed by tools, instruments, and equipment (19%), and structure and surfaces (16%). The most frequent types of injuries were fractures (31%), electrocutions (27%), and electrical burns (14%); the main injured body parts were upper extremities (25%), head (23%), and body system (18%). Among non-fatal cases, falls (37%), exposure to electricity (36%), and contact with objects (19%) caused most injuries; among fatal cases, exposure to electricity was the leading cause of death (50%), followed by falls (28%) and contact with objects (19%). The analysis also investigated the impact of several accident factors on the degree of injuries and found significant effects from such factors such as project type, source of injury, cause of injury, injured part of body, nature of injury, and event type. In other words, the statistical probability of a fatal accident—given an accident occurrence—changes significantly based on the degree of these factors. The results of this study, as depicted in the proposed decision tree model, revealed that the most important factor for predicting the nature of injury (electrical or non-electrical) is: whether the source of injury is parts and materials; followed by whether the source of injury is tools, instruments, and equipment. In other words, in predicting (with a 94.31% accuracy) the nature of injury as electrical or non-electrical, whether the source of injury is parts and materials and whether the source of injury is tools, instruments, and equipment are very important. Seven decision rules were derived from the proposed decision tree model. Beyond these outcomes, the described methodology contributes to the accident-analysis body of knowledge by providing a framework for codifying data from accident reports to facilitate future analysis and modeling attempts to subsequently mitigate more injuries in other fields.

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Section: Discussionmentioning

confidence: 99%

Trends in Catastrophic Occupational Incidents among Electrical Contractors, 2007–2013

Gholizadeh

Onuchukwu

Esmaeili

2021

IJERPH

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“…For example, a series of yes/no questions was added to the audit to identify specific issues that may be present in lock out/tag out procedures (e.g., “Are all workers involved in a maintenance or repair activity required to put their lock and tag on equipment?”) given the findings reported in Table 3. The current study, as well as several recent analyses of occupational fatalities (Chi et al, 2009, 2012), stresses the importance of de-energizing equipment prior to maintenance and carefully following required lock out/tag out procedures.…”

Section: Discussionmentioning

confidence: 71%

Analysis of Fatalities During Maintenance and Repair Operations in the U.S. Mining Sector

Reardon

Heberger

Dempsey

2014

IIE Transactions on Occupational Ergonomics and Human Factors

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Background Maintenance and repair work in mining is particularly hazardous and yet has received little focus in ergonomics research. Purpose In this article, an attempt has been made to determine if patterns can be identified to categorize maintenance and repair fatalities in mining, to compare occurrence of fatalities between coal and metal/nonmetal sectors, and to use this information to identify safety deficiencies and associated proposed remedial measures. Methods A classification scheme was developed to identify patterns in fatalities, including proximal causes, tasks, and contributing factors. This scheme was tested to ensure adequacy of the categories, and fatalities were categorized using the scheme. All testing and categorization were done by two of the authors to ensure reliability of the coding scheme. Results Patterns were successfully identified to categorize the fatalities, and these patterns were different between coal and metal/nonmetal mines. Coal mines had a greater proportion of electrical-related fatalities, while more fatalities related to potential energy occurred at metal/nonmetal mines. Most of the fatalities were caused by the victim coming into contact with an object or machine or the victim falling from height, and they occurred most often while the victim was performing maintenance or repair on equipment, cleaning, or removing blockages. The most frequent factors contributing to these incidents were failure to properly de-energize or lock out/tag out equipment, violation of work procedures, missing or inadequate safety equipment, and failure to block equipment properly. Conclusions The classification approach used was successful in identifying hazard patterns during maintenance and repair fatalities in mining. These patterns identify areas to focus attention when developing interventions to prevent the occurrence of future fatalities.

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“…We assumed that if the data was collected more than the current study, it would be possible to show the better pattern. This flow diagram cannot be adopted from electrical injury in that each of the flow diagrams can be directly linked with feasible prevention strategies by cutting the flow [10].Since it is dynamic, it means that Fraudster can have the other scenario if one scenario is not successful, e.g. if the fraudsters' demand for wire is not successful, the fraudsters can only ask for the private identity.…”

Section: Discussionmentioning

confidence: 99%

“…A series of flow diagram was constructed based on the information media and money media to illustrate how the fraudsters exchanged information with the victims and how the fraudsters obtained unauthorized financial benefit similar to the prevention of electrical injury [10]. Each of the flow diagrams could be directly linked with feasible prevention strategies by cutting the flow of information or money.…”

Section: Introductionmentioning

confidence: 99%

Pattern analysis of fraud case in Taiwan, China and Indonesia

Kusumo

Chi

Dewi

2017

IOP Conf. Ser.: Mater. Sci. Eng.

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Abstract. The current study analyzed 125 successful fraud cases happened in Taiwan, China, and Indonesia from 2008 to 2012 published in the English online newspapers. Each of the case report was coded in terms of scam principle, information media (information exchange between fraudsters and victim), money media (media used by fraudsters to obtain unauthorized financial benefit) and other additional information which was judged to be relevant. The Chisquare Automatic Interaction Detector (CHAID) was applied to the coded data of information, scam principle and money media to find a subset of predictors that might derive meaningful classifications. A series of flow diagrams was constructed based on CHAID result to illustrate the flow of information (scam) travelling from information media to money media.

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Flow diagram analysis of electrical fatalities in construction industry

Cited by 39 publications

References 14 publications

Trends in Catastrophic Occupational Incidents among Electrical Contractors, 2007–2013

Trends in Catastrophic Occupational Incidents among Electrical Contractors, 2007–2013

Analysis of Fatalities During Maintenance and Repair Operations in the U.S. Mining Sector

Pattern analysis of fraud case in Taiwan, China and Indonesia

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