A neuro-fuzzy algorithm for assessment of health, safety, environment and ergonomics in a large petrochemical plant

Azadeh, A.; Saberi, Morteza; Rouzbahman, Mahsa; Valianpour, F.

doi:10.1016/j.jlp.2015.01.008

Cited by 29 publications

(14 citation statements)

References 33 publications

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“…Several of the other models identi ed in the review also included elements that corresponded closely with the themes identi ed in our interview study. Based on the ndings from our review, the safety concern from managers and supervisors is identi ed the most key factor affecting the workers' risk perception and their understanding of safety issues [19,42,[49][50][51]. In addition, supervisors' safe behaviours such as regular safety inspection, motivating and supporting the subordinates, and providing resources for appropriate training of the workforce can motivate safety performance, encourage workers' participation as well as reporting potential incidents and unsafe behaviours [41,[52][53][54][55][56].…”

Section: Discussionmentioning

confidence: 99%

“…These studies examined work safety climate and aspects of working conditions and their association with occupational safety and work-related injuries among various workplace settings [11,42,[56][57][58]. They focus mainly on improving working conditions and its organizational and psychological aspects such as perceived work pressure, emergency response, physical and psychosocial hazards at work, job demands, physical factors of workplace, mental workload and stress, and defect of technology and design [42,50,51,[58][59][60]. These results support our qualitative ndings related to the unsafe workplace conditions theme.…”

Section: Discussionmentioning

confidence: 99%

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Safe Behaviour in The Petrochemical Industry: Evaluating The Consistency Between Conceptual Frameworks and Factors Reported by Iranian Workers

Harsini

Bohle

Matthews

et al. 2020

Preprint

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Background: Unsafe worker behaviour is often identified as a major cause of dangerous incidents in the petrochemical industry. Behavioural safety models provide frameworks that may help to prevent such incidents by identifying factors promoting safe or unsafe behaviour. A literature review was conducted to identify models of safe behaviour and determine which were most consistent with the experiences reported by workers in our qualitative study of the Iranian petrochemical industry.Methods: Five databases (EBSCOhost, Google Scholar, ProQuest, Science Direct, Scopus) were searched for studies between 2000 and 2019 that evaluated antecedents and outcomes of safe workplace behaviours in the petrochemical industry or other industrial settings. After duplications were removed, 141 publications were screened and 31 that met the inclusion criteria were reviewed. Constructs described in each publication were assessed for consistency with themes derived from the interview responses from Iranian petrochemical workers in the qualitative study: poor direct safety management and supervision; unsafe workplace conditions; workers' perceptions, skills and training; and broader organisational factors. Results: The themes identified in the qualitative study most closely matched those in the model described by Wu et al. (2011): poor direct safety management and supervision matched with safety leadership and several subscales; unsafe workplace conditions matched with several subscales; workers' perceptions, skills and training matched with two subscales, and broader organisational factors matched with two other subscales. The model selected was the one that included the most constructs matching the themes identified in the qualitative study.Conclusions: Valid behavioural safety models can provide a basis for more effective safety cultures and management systems in selected contexts. This study identified most consistency between themes elicited from Iranian petrochemical workers and the constructs described by Wu et al. (2011), providing evidence of the validity of their model. Intervention studies are needed to assess the effectiveness of safety models in improving safe behaviours in industrial settings.Trial registration: Iranian Registry of Clinical Trials: IRCT20170515033981N2. Registered 19 June 2018. https://www.irct.ir/trial/26107

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Safe Behaviour in The Petrochemical Industry: Evaluating The Consistency Between Conceptual Frameworks and Factors Reported by Iranian Workers

Harsini

Bohle

Matthews

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Dynamic systems and models of artificial neural networks evaluated aspects related to the level of satisfaction in the service and therefore aided in the evaluation of absences to the work of the respective employees of a company [45]. The work carried out in [46][47][48][49][50] present studies on absenteeism at work treated through intelligent models.…”

Section: Artificial Neural Network and Absenteeismmentioning

confidence: 99%

A hybrid approach of intelligent systems to help predict absenteeism at work in companies

et al. 2019

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In recent years, several surveys have been conducted on absenteeism and how this affects the routine of conducting productive operations in companies. Therefore, having criteria for predicting absenteeism at work can help managers in contingency actions reduce financial losses due to the absence of a worker in their workplace. The objective of this work is to apply the artificial intelligence concepts of a regularized fuzzy neural network, which combines the benefits of artificial neural networks with the fuzzy set theory to obtain more accurate results in predicting corporate absenteeism. The database called absenteeism at work, taken from the UCI Machine Learning Repository, which captured elements of a Brazilian company, was applied in a fuzzy neural network model that allows the calculation of the regressors, defining the estimate of the lack of hours of an employee. The results of the experiments prove that the intelligent model can help in the creation of a specialist system that assists in the prediction of absenteeism.

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“…Another critical issue in managing safe behaviour in this industry is the development of educational interventions that minimize workers' exposure to hazards and related risks. Safety training is an effective strategy for changing unsafe behaviours, discouraging false beliefs about safety, and preventing occupational accidents [17]. However, understanding the key factors affecting safety is a prerequisite to identifying training needs and designing effective interventions [9,18].…”

Section: Introductionmentioning

confidence: 99%

Factors associated with unsafe work behaviours in an Iranian petrochemical company: perspectives of workers, supervisors, and safety managers

et al. 2020

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Background: The petrochemical industry is hazardous, in part because of the inherently dangerous nature of the work conducted, and incidents frequently result in significant financial and social losses. The most common immediate cause of incidents and injuries in this industry is unsafe worker behaviour. Identifying the factors encouraging unsafe work behaviours is the first step in taking action to discourage them. The aim of this study was to (a) explore workers', supervisors' and safety managers' attitudes and perceptions of safety in a petrochemical company in Iran, and (b) identify the factors that discourage safe work behaviours. Methods: A qualitative study was conducted by applying the steps described by Graneheim and Lundman (2004). Twenty participants were recruited from an Iranian petrochemical company using a multi-stage approach, with initial purposive sampling followed by snowball sampling to enhance recruitment. Individual face-to-face and semistructured interviews were conducted to gain an in-depth understanding of factors acting as barriers to safe behaviour. The interviews were recorded and transcribed in Persian and then translated into English. Conventional content analysis was performed. Results: The main themes emerging from the interviews were: (i) poor direct safety management and supervision; (ii) unsafe workplace conditions; (iii) workers' perceptions, skills and training; and (iv) broader organisational factors. Conclusions: The findings give insights into practical organisational measures that can be implemented by management to promote workers' commitment to safety and engage in safe behaviours in their workplace. Trial registration: Iranian Registry of Clinical Trials: IRCT20170515033981N2. Retrospectively registered 19 June 2018.

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A neuro-fuzzy algorithm for assessment of health, safety, environment and ergonomics in a large petrochemical plant

Cited by 29 publications

References 33 publications

Safe Behaviour in The Petrochemical Industry: Evaluating The Consistency Between Conceptual Frameworks and Factors Reported by Iranian Workers

Safe Behaviour in The Petrochemical Industry: Evaluating The Consistency Between Conceptual Frameworks and Factors Reported by Iranian Workers

A hybrid approach of intelligent systems to help predict absenteeism at work in companies

Factors associated with unsafe work behaviours in an Iranian petrochemical company: perspectives of workers, supervisors, and safety managers

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