Continuous performance assessment and improvement of integrated HSE and maintenance systems by multivariate analysis in gas transmission units

In this study, an integrated “Health, Safety, and Environment (HSE)” and maintenance systems are presented. Multivariate analysis is used for continuous performance assessment and improvement of these systems. The two subjects of “Maintenance System” and “HSE” have been individually investigated several times in different studies. However, few studies have been done to integrate these two systems and provide an integrated system for their implementation. This study evaluates current maintenance and HSE systems of a Gas Transmission Unit by Data Envelopment Analysis (DEA) and Principal Component Analysis (PCA). Moreover, decision making units (DMUs) are examined and ranked. Employees are considered as DMUs. This is done through investigating and measuring their efficiencies and identifying the inefficient and less-efficient units. Since an increase in the number of inputs does not lead to an increase in the number of outputs with the same scale, an output-oriented DEA with a Variable Returns to Scale (VRS) is used. The Fuzzy DEA (FDEA) is also used in this research to decrease uncertainty existing in qualitative indicators and human error. Finally, suggestions are given to improve those DMUs. The managers and employees of the gas transmission unit constitute the statistical population of the study. To achieve the objectives of this study, standard questionnaires with respect to HSE and Maintenance system are completed by operators. The proposed approach would help policy makers and top managers of Gas Transmission Company to have a more comprehensive and thorough understanding the working conditions with respect to the maintenance and HSE features.     

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.     

Assessment and improvement of integrated HSE and macro-ergonomics factors by fuzzy cognitive maps: The case of a large gas refinery

This study analyzes and assesses the integrated health, safety, environment (HSE) and ergonomics (HSEE) factors by fuzzy cognitive maps (FCM) approach. This is achieved through integrating ergonomic and macro-ergonomic as well as occupational health and safety arrangements in an integrated modeling for assessment of their multi-faceted impact on workers' productivity, injury rate and satisfaction. This paper uses FCM to assess the direct and indirect effects of HSEE factors on system performance indicators. The results of FCM are used to develop leading indicators useful for proactive management of productivity, injury rate, and job satisfaction. The result of a comprehensive survey of 37 experts in control rooms and maintenance activities in a large gas refinery is used to show the applicability and usefulness of FCM approach. Moreover, FCM results are used to determine the causal structure of HSEE factors and system performance indicators. It is concluded that macro-ergonomics factors such as instructions and education, familiarity with organization's rules, and proper communications most contribute to improve workers' safety, satisfaction, and productivity.     

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.     

Modeling and optimizing efficiency gap between managers and operators in integrated resilient systems: The case of a petrochemical plant

The reliability issue in complex industrial systems such as oil, gas, petrochemical companies, nuclear and aviation industries has been of great importance. Resilience engineering (RE) is a new attitude toward the improvement of safety and reliability in the stated systems. One of the challenges a resilient system might face is the gap between work as imagined by managers and work as actually done by operators. This study will introduce a new framework named integrated resilience engineering (IRE) as a result of developing the concept of RE. The data used in this research have been obtained by means of questionnaire from a petrochemical company. Thereafter, the efficiency of operators and managers are calculated in RE and IRE frameworks through data envelopment analysis (DEA) approach. Then, the gaps between managers and operators are analyzed in two frameworks. The results are indicative of a significant growth in the number of efficient operators and managers in IRE framework compared to RE framework. Besides, the efficiency mean of managers and operators in IRE framework has experienced the growth of 1.8% and 5% compared to RE framework, respectively. The efficiency gap between managers and operators in IRE framework has also enjoyed the improvement of 88% compared to RE framework. Generally, it can be said that the suggested items of this research has led to the betterment of managers and operators’ efficiency and of the efficiency gap between them. Therefore, these items can improve the resilience and safety of complex systems. The results of Spearman test show that there is a strong direct correlation between the DEA results in two frameworks. This is the first study that examines the efficiency gap between operators and managers based on the RE principles and by means of DEA approach.     

永安火电厂人为继电保护不正确动作事故分析及预防对策

通过历年来永安火电厂继电保护人为不正确动作事故情况,进行原因分析,并采取一系列措施,取得了较好效果。     

Technical,human, and organizational factors affecting failures of firefighting systems (FSs) of atmospheric storage tanks: Providing a risk assessment approach using Fuzzy Bayesian Network (FBN) and content validity indicators

Most risk assessment methods have problems such as uncertainty, static structure, and lack of validation. Also, in most of these studies, less attention has been paid to human, managerial, and organizational issues. Therefore, this study proposes a risk assessment method based on the Fuzzy Bayesian Network (FBN) to prevent failure of firefighting systems (FFSs) in the atmospheric Storage Tanks of a Petrochemical Industry. The first stage of the study is the development of a fault tree (FT) and investigation of basic events (BEs). In this study, content validity indices and brainstorming technique were used to validate the FT structure and reduce the uncertainties of Completeness, Modeling, and Parameter. After determining the probability of basic events (BEs) by the expert team opinions and fuzzy logic, events were transmitted to the Bayesian Network (BN) and then analyzed with deductive and inductive reasoning, followed by sensitivity analysis in the GeNIe software. Finally, results of a case study in the Atmospheric Storage Tanks of the Methanol Floating Roof of a Petrochemical Industry showed that FBN simulation and FT validation could provide a practical way to determine FFSs probabilities, identify impactful events, and reduce the above uncertainties. Also, taking account of hidden factors of events, such as organizational and managerial factors, can help managers to prevent FFSs in tanks.     

Validation of a booted finite element model of the WIAMan ATD lower limb in component and whole-body vertical loading impacts with an assessment of the boot influence model on response

Objective: A novel anthropomorphic test device (ATD) representative of the 50th percentile male soldier is being developed to predict injuries to a vehicle occupant during an underbody blast (UBB). The main objective of this study was to develop and validate a finite element (FE) model of the ATD lower limb outfitted with a military combat boot and to insert the validated lower limb into a model of the full ATD and simulate vertical loading experiments.

Methods: A Belleville desert combat boot model was assigned contacts and material properties based on previous experiments. The boot model was fit to a previously developed model of the barefoot ATD. Validation was performed through 6 matched pair component tests conducted on the Vertically Accelerated Loads Transfer System (VALTS). The load transfer capabilities of the FE model were assessed along with the force-mitigating properties of the boot. The booted lower limb subassembly was then incorporated into a whole-body model of the ATD. Two whole-body VALTS experiments were simulated to evaluate lower limb performance in the whole body.

Results: The lower limb model accurately predicted axial loads measured at heel, tibia, and knee load cells during matched pair component tests. Forces in booted simulations were compared to unbooted simulations and an amount of mitigation similar to that of experiments was observed. In a whole-body loading environment, the model kinematics match those recorded in experiments. The shape and magnitude of experimental force–time curves were accurately predicted by the model. Correlation between the experiments and simulations was backed up by high objective rating scores for all experiments.

Conclusion: The booted lower limb model is accurate in its ability to articulate and transfer loads similar to the physical dummy in simulated underbody loading experiments. The performance of the model leads to the recommendation to use it appropriately as an alternative to costly ATD experiments.