An adaptive neural network algorithm for assessment and improvement of job satisfaction with respect to HSE and ergonomics program: The case of a gas refinery

Researchers have been continuously trying to improve human performance with respect to Health, Safety and Environment (HSE) and ergonomics (hence HSEE). This study proposes an adaptive neural network (ANN) algorithm for measuring and improving job satisfaction among operators with respect to HSEE in a gas refinery. To achieve the objectives of this study, standard questionnaires with respect to HSEE are completed by operators. The average results for each category of HSEE are used as inputs and job satisfaction is used as output for the ANN algorithm. Moreover, ANN is used to rank operators performance with respect to HSEE and job satisfaction. Finally, Normal probability technique is used to identify outlier operators. Moreover, operators with inadequate job satisfaction with respect to HSEE are identified. This would help managers to see if operators are satisfied with their jobs in the context of HSEE. This is the first study that introduces an integrated ANN algorithm for assessment and improvement of human job satisfaction with respect to HSEE program in complex systems.     

An intelligent algorithm for performance evaluation of job stress and HSE factors in petrochemical plants with noise and uncertainty

This study presents an intelligent algorithm based on Adaptive Neuro-Fuzzy Inference System (ANFIS) and statistical methods for measuring job stress in noisy and complex petrochemical plants. Job stress is evaluated against health, safety, environment and ergonomics (HSEE) program in the integrated algorithm. The algorithm is composed of seventeen distinct steps. To achieve the objectives of this study, standard questionnaires with respect to HSEE are completed by operators. The average results for each category of HSEE are used as inputs and job stress is used as output for the algorithm. Moreover, operators' stress level with respect to HSEE is evaluated by the algorithm. Finally, operators with weak stress level are identified. The advantage and superiority of the intelligent algorithm are shown by error analysis in contrast with conventional regression approaches. This is the first study that introduces an integrated intelligent algorithm for assessment and improvement of job stress and HSEE in noisy, complex and uncertain environment.     

A flexible intelligent algorithm for identification of optimum mix of demographic variables for integrated HSEE-ISO systems: The case of a gas transmission refinery

This study proposes a flexible intelligent algorithm for assessment and optimization of demographic features on integrated health, safety, and environment and ergonomics (HSEE)-ISO systems among operators of a gas transmission refinery. To achieve the objectives of this study, standard questionnaires with respect to HSEE and ISO standards are completed by 80 operators. Demographic features include age, education, gender, weight, stature, marital status, and work type. The average results for each category of HSEE are used as inputs and effectiveness of ISO systems (ISO 18000, ISO 14000, and ISO 9000) are used as output for the intelligent algorithm. Artificial Neural Networks (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) in addition to conventional regression are used in this paper. Result shows the applicability and superiority of the flexible intelligent algorithm over conventional methods through mean absolute percentage error (MAPE). Computational results show that the proposed ANN performs better than ANFIS and conventional regressions based on its relative error. Finally, the optimum mix of demographic variables from viewpoint of HSEE and ISO are identified. This is the first study that proposes a flexible intelligent algorithm for assessment of optimum mix of demographic features for HSEE and ISO systems in a complex system such as a gas transmission refinery.     

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

Process plants such as petrochemical units have been continuously trying to improve Health, Safety, Environment and Ergonomics (HSEE) programs. This study proposes an adaptive network-based fuzzy inference system (ANFIS) for assessment of HSEE programs in a petrochemical plant. The proposed neuro-fuzzy approach is applied to a set of operators in the petrochemical unit to show its applicability and superiority. To achieve the objectives of this study, standard questionnaires with respect to HSEE are completed by operators. The average results for each category of HSEE are used as inputs and accomplishment of HSEE programs is used as output for the algorithm. Moreover, this algorithm is used to rank operators performance with respect to HSEE. Finally, the algorithm identifies efficient operators with respect to HSEE. This is the first study that introduces an intelligence algorithm for assessment and improvement of HSEE program in a petrochemical plant.     

中国民航业安全风险监测与仿真研究

根据系统安全的思想,通过对航空安全历史数据的分析和专家经验,从人员、设备设施、环境和组织管理4个方面,提出中国民航机务、空管、飞行、机场4个分系统安全风险监测指标体系,共102个风险因素指标,并合成为27个行业安全风险监测指标。以民航历史数据为样本,建立资源优化神经网络(RON)模型,将安全风险监测指标与中国民航安全指数相联系,分析安全指数的关键影响因素,达到安全管理决策支持的目的。通过建立的风险监测指标体系和RON模型,可以实现民航整个行业、各分系统及单个指标的安全风险监测和预警。     

Impact of individual resilience and safety climate on safety performance and psychological stress of construction workers: A case study of the Ontario construction industry

IntroductionThe construction industry has hit a plateau in terms of safety performance. Safety climate is regarded as a leading indicator of safety performance; however, relatively little safety climate research has been done in the Canadian construction industry. Safety climate may be geographically sensitive, thus it is necessary to examine how the construct of safety climate is defined and used to improve safety performance in different regions. On the other hand, more and more attention has been paid to job related stress in the construction industry. Previous research proposed that individual resilience may be associated with a better safety performance and may help employees manage stress. Unfortunately, few empirical research studies have examined this hypothesis. This paper aims to examine the role of safety climate and individual resilience in safety performance and job stress in the Canadian construction industry.MethodThe research was based on 837 surveys collected in Ontario between June 2015 and June 2016. Structural equation modeling (SEM) techniques were used to explore the impact of individual resilience and safety climate on physical safety outcomes and on psychological stress among construction workers.ResultsThe results show that safety climate not only affected construction workers' safety performance but also indirectly affected their psychological stress. In addition, it was found that individual resilience had a direct negative impact on psychological stress but had no impact on physical safety outcomes.ConclusionsThese findings highlight the roles of both organizational and individual factors in individual safety performance and in psychological well-being.Practical applicationsConstruction organizations need to not only monitor employees' safety performance, but also to assess their employees' psychological well-being. Promoting a positive safety climate together with developing training programs focusing on improving employees' psychological health — especially post-trauma psychological health — can improve the safety performance of an organization.     

Exploration of relationships between safety performance and unsafe behavior in the Chinese oil industry

Safety performance is comprised of two components, safety compliance and safety participation. However, relationships between safety performance and unsafe behavior have not been thoroughly investigated. In this work, scales for safety compliance and safety participation were revised for use in the oil industry, and job burnout scale was developed on the basis of the Maslach Burnout Inventory-General Survey (MBI-GS). A structural equation model was then employed to investigate the interactions of these factors for 238 front-line oil workers from the PetroChina Huabei Oilfield Company in China. From the results, it was determined that workers' unsafe behavior could not be reduced significantly solely from these two dimensions of safety performance. Compared with safety participation, safety compliance was found to have a greater influence on unsafe behavior. However, job burnout was found to be a significant moderator between these two components and unsafe behavior. Furthermore, it was determined that oil workers' occupational psychological health conditions must be taken into account to improve organizational safety management and reduce workers’ unsafe behavior.     

中国职业安全卫生一体化发展模式探索

一体化管理是现代企业安全管理发展的必然趋势,中国职业安全卫生在不断的发展和完善过程中正从狭隘的劳动保护朝着一体化可持续的方式发展。针对当前影响安全生产的主体要素,探讨了从安全观念、统一立法、管理体系、人才培养、社会保障5个层面构建中国职业安全卫生一体化发展模式的可能性和必要性,并指出了OSH一体化发展模式的要害与对策。     

Work-related injuries among commercial janitors in Washington State,comparisons by gender

IntroductionWe analyzed workers' compensation (WC) data to identify characteristics related to workers' compensation claim outcomes among janitorial service workers in Washington State.MethodWe analyzed WC data from the Washington State Department of Labor & Industries (L&I) State Fund (SF) from January 1, 2003 through December 31, 2013, for janitorial service workers employed in the National Occupational Research Agenda (NORA) Services Sector. We constructed multivariable models to identify factors associated with higher medical costs and increased time lost from work.ResultsThere were 2,390 janitorial service compensable claims available for analysis. There were significant differences in injury type and other factors by gender, age, and language preference. Linguistic minority status was associated with longer time loss and higher median medical costs. Women were estimated to account for 35% of janitorial service workers but made up 55% of the compensable claims in this study.ConclusionsJanitorial service workers comprise a large vulnerable occupational group in the U.S. workforce. Identifying differences by injury type and potential inequitable outcomes by gender and language is important to ensuring equal treatment in the workers' compensation process.Practical applicationsThere were significant differences in injury and individual characteristics between men and women in this study. Women had twice the estimated rate of injury to men, and were more likely to require Spanish language materials. Improving communication for training and knowledge about the workers' compensation system appear to be high priorities in this population of injured janitorial service workers.     

The effect of a participative product design process on user performance

The use of hand tools can lead to accidents, overexertion injuries and discomfort. So, there is certainly room for better-designed hand tools, especially hand tools that contribute to better performance. In the literature, the benefits of a participative product design approach are clearly shown. However, the effect of this approach is hardly ever measured at the hand tool performance level.The goal of this project was to study the effect of a participative product design process on indicators of health, performance and comfort.Two sets of screwdrivers were tested. One set was developed by a participative product design approach and the control by a traditional approach.The study indicates positive effects of the participative approach. Some indicators for health and safety (discomfort in the hand and blisters) were significantly better for the test set compared with the control set. The effect on productivity is clearly shown (16% higher productivity) and the positive effects on comfort are also shown.It is discussed that it is plausible that in the long run some of the effects found in this study would still be seen under real working conditions, but long-term effects on health and safety still need to be studied.     

Actual safety performance of the Malaysian offshore oil platforms: Correlations between the leading and lagging indicators

IntroductionThis study establishes the correlations between performance of a set of key safety factors and the actual lagging performance of oil platforms in Malaysia, hence the relevance of the key safety factors in evaluating and predicting the safety performance of oil and gas platforms. The key factors are crucial components of a safety performance evaluation framework and each key safety factor corresponds to a list of underlying safety indicators.MethodIn this study, participating industrial practitioners rated the compliance status of each indicator using a numbering system adapted from the traffic light system, based on the actual performance of 10 oil platforms in Malaysia. Safety scores of the platforms were calculated based on the ratings and compared with the actual lagging performance of the platforms. Safety scores of two platforms were compared with the facility status reports' findings of the respective platforms.ResultsThe platforms studied generally had good performance. Total recordable incident rates of the platforms were found to show significant negative correlations with management and work engagement on safety, compliance score for number of incident and near misses, personal safety, and management of change. Lost time injury rates, however, correlated negatively with hazard identification and risk assessment. The safety scores generally agreed with findings of the facility status reports with substandard process containment found as a contributor of hydrocarbon leaks.ConclusionsThis study proves the criterion validity of the safety performance evaluation framework and demonstrates its usability for benchmarking and continuous improvement of safety practices on the Malaysian offshore oil and gas platforms.Practical applicationsThis study reveals the applicability of the framework and the potential of extending safety reporting beyond the few conventional lagging safety performance indicators used. The study also highlights the synergy between correlating safety factors to streamline safety management on offshore platforms.     

Is there agreement between worker self and supervisor assessment of worker safety performance? An examination in the construction industry

Introduction: Individual safety performance (behavior) critically influences safety outcomes in high-risk workplaces. Compared to the study of generic work performance on different measurements, few studies have investigated different measurements of safety performance, typically relying on employees' self-reflection of their safety behavior. This research aims to address this limitation by including worker self-reflection and other (i.e., supervisor) assessment of two worker safety performance dimensions, safety compliance and safety participation. Method: A sample of 105 workers and 17 supervisors in 17 groups in the Chinese construction industry participated in this study. Comparisons were made between worker compliance and participation in each measurement, and between workers' and supervisors' assessment of workers' compliance and participation. Multilevel modeling was adopted to test the moderating effects on the worker self-reflection and supervisor-assessment relationship by group safety climate and the work experience of supervisors. Results: Higher levels of safety compliance than participation were found for self-reflection and supervisor assessment. The discrepancy between the two measurements in each safety performance dimension was significant. The work experience of supervisors attenuated the discrepancy between self- and supervisor-assessment of compliance. Contrary to our expectations, the moderating effect of group safety climate was not supported. Conclusions: The discrepancy between worker self- and supervisor-assessment of worker safety performance, thus, suggests the importance of including alternative measurements of safety performance in addition to self-reflection. Lower levels of participation behavior in both raters suggest more research on the motivators of participatory behavior. Practical applications The discrepancy between different raters can lead to negative reactions of ratees, suggesting that managers should be aware of that difference. Assigning experienced supervisors as raters can be effective at mitigating interrater discrepancy and conflicts in the assessment of compliance behavior.     

A new approach for layout optimization in maintenance workshops with safety factors: The case of a gas transmission unit

In this study, an Integrated Simulation-Data Envelopment Analysis (DEA) approach is presented for optimum facility layout of maintenance workshop in a gas transmission unit. The process of repair of incoming parts includes various operations on different facilities. The layout problem in this system involves determining the optimum location of all maintenance shop facilities. Layout optimization plays a crucial role in this type of problems in terms of increasing the efficiency of main production line. Standard types of layouts including U, S, W, Z and straight lines are considered. First, the maintenance workshop is modeled with discrete-event-simulation. Time in system, average waiting time, average machine utilization, average availability of facilities, average queue length of facilities (AL) and average operator utilization are obtained from simulation as key performance indicators (KPIs) of DEA. Also, safety index and number of operators are considered as other KPIs. Finally, a unified non-radial Data Envelopment Analysis (DEA) is presented with respect to the stated KPIs to rank all layouts alternatives and to identify the best configuration. Principle Component Analysis (PCA) is used to validate and verify the results. Previous studies do not consider safety factor in layout design problems. This is the first study that presents an integrated approach for identification of optimum layout in a maintenance workshop of gas transmission unit by incorporating safety and conventional factors.     

Organizational Climate Metrics as Safety,Health and Environment Performance Indicators and an Aid to Relative Risk Ranking within Industry

The chemical, pharmaceutical and other related process industries are characterized by inherently hazardous processes and activities. To ensure that considered risk management decisions are made it is essential that organizations have the ability to rank the risk profiles of their assets and operations. Current industry risk ranking techniques are biased toward the assessment of the risk potential of the asset or operation. Methodologies used to assess these risks tend to be engineering-based and include, for example, hazard identification and event rate estimation techniques. Recent research has associated lagging safety performance indicators with metrics of organizational safety climate. Despite the evidence suggesting their potential usefulness, organizational climate metrics have not yet been exploited as a proactive safety, health and environmental performance indicator or as an aid to relative risk ranking. This paper summarizes research that successfully produced a statistical model of organizational climate and its relationship to site significant injury frequency rates, allowing the relative risk ranking of sites based upon organizational climate metrics. The responses to an industrial organizational survey are examined for a pharmaceutical company's sites in the United Kingdom, Sweden and the United States. Projection to Latent Structures Analysis is performed on the survey responses. The resultant models are shown to be able to accurately model the site significant injury frequency rates. The organizational climate metrics that discriminate between the safety performance levels of different sites are identified.     

Predicting workers' compensation claims and disciplinary actions using SecureFit®: Further support for integrative models of workplace safety

IntroductionA growing body of applied research has identified certain psychological traits that are predictive of worker safety. However, most of these studies suffer from an overreliance on common method bias caused by self-report measures of both: (a) personal factors such as personality traits; and (b) outcomes such as safety behaviors and injuries.MethodThis study utilized archival data from 796 employees at a large U.S. automobile manufacturer. Data were gathered on a pre-employment assessment, SecureFit®, that measured key personality characteristics such as conscientiousness, locus of control, and risk taking. In addition, objective measures of workers' compensation claims and disciplinary actions were also gathered.ResultsThe results indicated that disciplinary actions and workers' compensation claims were strongly correlated. It also demonstrated that the pre-employment assessment was able to predict both disciplinary actions and workers' compensation claims up to 12 months in the future. Screening out just 8% of the applicant sample using the assessment would have resulted in a 35% reduction in disciplinary actions and 46% in workers' compensation claims, respectively.ConclusionsThe study found a very strong relationship between counterproductive work behaviors (CWBs), such as not following rules, and workers' compensation claims. It also found a strong relationship between a combination of personality traits that have been shown to be associated with both variables, although the current study was able to demonstrate that relationship with objective measure of both variables.Practical applicationsIndividuals who receive disciplinary actions for things such as not following rules, not coming to work on time, etc. are significantly more likely to also be involved in serious safety incidents, and vice versa. Identifying those individuals early on in the hiring process and screening them out can significantly reduce the number of CWBs as well as workers' compensation claims.     

Analysis of injury events with fuzzy cognitive maps

Issues related to health and safety at work, such as accidents at work, are one of the most important areas of action for global social policy. This paper presents a fuzzy cognitive map (FCM) approach to explore the importance of the relevant factors in industrial plants. For this purpose, industrial plants are described in terms of factors that affect injury risk and the causal relationships involved.In this work, the injuries in an Italian refinery have been studied. The company in this account has a system for monitoring and controlling the machinery but has a large number of minor injuries at work. The causes of these injuries have been found in human behaviours. To analyse the injuries, it is necessary to investigate what individual-level concerns are involved in the perception of risk. For this investigation, an FCM permits us to build a schema of the perception of risk. The resulting analysis of all of these schemas has allowed us to define a method that generically permits a determination of the causes for each type of injury. In fact, it has been possible to determine that factors such as poor attention and concentration or fatigue are the main causes of injuries at work.In light of the results obtained, managers can define appropriate control procedures to diminish the occurrences of the injuries.     

Analysis of motorcycle accidents using association rule mining-based framework with parameter optimization and GIS technology

IntroductionAnalyzing key factors of motorcycle accidents is an effective method to reduce fatalities and improve road safety. Association Rule Mining (ARM) is an efficient data mining method to identify critical factors associated with injury severity. However, the existing studies have some limitations in applying ARM: (a) Most studies determined parameter thresholds of ARM subjectively, which lacks objectiveness and efficiency; (b) Most studies only listed rules with high parameter thresholds, while lacking in-depth analysis of multiple-item rules. Besides, the existing studies seldom conducted a spatial analysis of motorcycle accidents, which can provide intuitive suggestions for policymakers. Method: To address these limitations, this study proposes an ARM-based framework to identify critical factors related to motorcycle injury severity. A method for parameter optimization is proposed to objectively determine parameter thresholds in ARM. A method of factor extraction is proposed to identify individual key factors from 2-item rules and boosting factors from multiple-item rules. Geographic information system (GIS) is adopted to explore the spatial relationship between key factors and motorcycle injury severity. Results and conclusions: The framework is applied to a case study of motorcycle accidents in Victoria, Australia. Fifteen attributes are selected after data preprocessing. 0.03 and 0.7 are determined as the best thresholds of support and confidence in ARM. Five individual key factors and four boosting factors are identified to be related to fatal injury. Spatial analysis is conducted by GIS to present hot spots of motorcycle accidents. The proposed framework has been validated to have better performance on parameter optimization and rule analysis in ARM. Practical applications: The hot spots of motorcycle accidents related to fatal factors are presented in GIS maps. Policymakers can refer to those maps straightforwardly when decision making. This framework can be applied to various kinds of traffic accidents to improve the performance of severity analysis.     

Optimization of HSE in maintenance activities by integration of continuous improvement cycle and fuzzy multivariate approach: A gas refinery

Gas refineries have been continuously focusing on Health, Safety and Environment programs to improve maintenance activities. Several researches have studied on this area with different analysis methods. This study presents an integrated approach for optimization of factors contributing to the implementation of Health, Safety and Environment (HSE) in maintenance activities. HSE managers in each sector answered standard questionnaire whit respect to HES. The methodology is based on fuzzy data envelopment analysis (FDEA) and Deming's continuous improvement cycle. Also, this method is used to rank the relevant performance efficiencies in certain and uncertain conditions of each HSE sectors whit considering HSE in maintenance activities. It corresponds and integrates its registered HSE-MS with OHSAS 18001:2007 and ISO 14001:2004 to evaluate multiple inputs and outputs of over 36 subsidiary HSE divisions with parallel mission and objectives simultaneously. Also, it determines efficient target indices and could assure continuous improvement in the organization. This is the first study that introduces an integrated approach to improve HSE management programs in a gas refinery by a robust and continuous improvement approach.     

The effect of integrated management system on safety and productivity indices: Case study; Iranian cement industries

Nowadays, with implementation of management systems and environment management and due to the influence of safety and health issues on working processes, organizations have also sought to acquire health and safety management systems. This study which aims to examine the influence of integrated management system on safety and productivity indices has retrospective experimental nature. It was conducted in Cement Factories in which three systems are used: quality, environment and safety systems. The collected data were: accident reports and the investigation of events in 6 years during 2005-2010 (3 years before and 3 years after the implementation of the system). The safety indices that used in this study are: IFR, ISR, FSI, and Safe T. Score. Then, the data analyzed with the T-test, mean and standard deviation. The results showed a significant difference between various safety indices before and after the implementation. The examination of production indices such as increasing rate of productivity and production indicates the influence of these systems on production and productivity indices. The results have showed that the safety system existence cannot ensure productivity increase. Indices definition can be helpful for the safety system effectiveness and system continual improvement. It is important to say that there might be various indices definition in different industries.