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Though accident data have been collected across industries, they may inherently contain uncertainty of randomness and fuzziness which in turn leads to misleading interpretation of the analysis. To handle the issue of uncertainty within accident data, the present work proposes a rough set theory (RST)-based approach to provide rule-based solution to the industry to minimize the number of accidents...
In the occupational accident analysis, identification of the interrelationships of the factors behind the accidents is very important. To explore the relationships or the impacts of the causal factors on the accidents and to predict the incident outcomes i.e., injury, near miss, and property damage cases, Bayesian Network (BN) model is used in this paper. The proposed model is validated using the...
Steel industry is considered to be an economic sector with higher number of accidents. Workers in this industry are exposed to a wide variety of hazards during working hours. Thus, the database maintained in industry varies in terms of the types of data indicating nature of accidents, causes of accidents, date and time-stamp etc. The objective of this study is to give predictive solution of accident...
This study proposes a new scheme for measurement of safety performance in work systems using segmented point process models that can capture the points of changes in the working conditions as well as changes in safety initiatives. Data, collected from an underground coal mine, were analyzed using homogeneous (HPP) as well as non-homogeneous (NHPP) point process models. Time between occurrences (TBO)...
Occupational accident is a serious issue for every industry. Steel industry is considered to be one of the economic sectors having a high number of accidents. Thus, the main aim of this study is to build a model which could predict the occupational incidents (i.e., injury, near-miss, and property damage) using support vector machine (SVM) by utilizing a database comprising almost 5000 occupational...
The focus of the present study is to build a predictive model which not only could predict the occupational incidents but also provide rules for explaining accident scenarios like near-miss, property damage, or injury cases. Classification and regression tree (CART) is used for prediction purpose. Furthermore, the parameters of CART have been tuned by grid based tuning and genetic algorithm (GA)....
Occupational accidents are a serious threat to any organization. Occupational accidents in steel industry sector remain a threat as workforce is exposed to different kinds of hazards due to the workplace characteristics. In this study, a unique method is proposed by developing a text mining based prediction model using fault tree analysis (FTA), and Bayesian Network (BN). Free unstructured accident...
In this study, the measurement of job stress of electric overhead traveling crane operators and quantification of the effects of operator and workplace characteristics on job stress were assessed.Job stress was measured on five subscales: employee empowerment, role overload, role ambiguity, rule violation, and job hazard. The characteristics of the operators that were studied were age, experience,...
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