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.     

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.     

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.     

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 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.     

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.     

Performance evaluation of integrated resilience engineering factors by data envelopment analysis: The case of a petrochemical plant

Petrochemical units are potentially prone to incidents that have catastrophic consequences such as explosion, leakage of toxic materials, and the stoppage of the production process. Resilience engineering (RE) is a new method that can control incidents and limit their consequences. It includes top-level commitment, reporting culture, learning, awareness, preparedness, and flexibility. However, this study introduces a new concept of RE (referred to as integrated RE or IRE) which includes the above factors in addition to self-organization, teamwork, redundancy and fault-tolerant. This study evaluates performance of IRE in a petrochemical plant through considering the obtained data from questionnaires and data envelopment analysis (DEA) approach. Moreover, the performance of RE and the new IRE are compared and discussed. The results show that although there is a strong direct correlation between the DEA results in two frameworks, the mean scores of efficiency in IRE is slightly higher than RE. This is the first study that introduces an integrated approach for RE. In addition, this study is amongst the first ones that examine the behavior of resilience engineering by DEA. Moreover, the superiority of IRE is shown through robust statistical analysis.     

The oil and gas industry,the Offshore Installation Manager (OIM) and the management of emergencies - Changes necessary to achieve effective competence assessment of OIMs in controlling emergencies

Within the UK offshore oil and gas industry all installations require to be under the charge of a ‘competent’ installation manager in accordance with the Offshore Installations and Pipeline Works (Management and Administration) Regulations (MAR) 1995. The Offshore Installation Manager (OIM) is responsible for the safety of all persons onboard and within 500 m of an installation. Should an incident arise, the OIM performs one of the most critical roles within the offshore industry - management of the response to the emergency to mitigate and make safe the installation to secure a place of safety for persons onboard or organise their safe evacuation. The emergency response also includes limiting the loss of hydrocarbons to the environment.Research at the University of Aberdeen has identified 8 potential barriers to the effective competence assessment of OIMs in controlling emergencies. These underlying barriers are a consequence of current UK legislation and industry practices in the assessment of OIM competence and result from:

• •multiple definitions of competence,
• •competence assessment predominantly by observation,
• •lack of specific and unambiguous competence requirements for trainers and assessors,
• •complexity in UK legislation and complicated interpretation of terms,
• •lack of statutory competence requirements for OIMs in controlling emergencies,
• •lack of ownership of OIM competence and competence assessment,
• •complex interactions across multiple UK Government departments, and
• •lack of regulation and independent audit of the competence assessment process of OIMs in controlling emergencies.

The potential barriers were identified by qualitative analysis of key documentation, including legislation, using a critical hermeneutic approach. Hermeneutics has historically been used to analyse texts within the domains of theology, business and law. It arguably, however, represents a powerful approach to the study of documents within the engineering domain and the offshore oil and gas industry.This paper discusses the identified potential barriers, research conclusions and recommendations and represents the culmination of three years of doctoral research investigating the competence assessment of OIMs in controlling emergencies within the offshore oil and gas industry. The research, in particular, is relevant to Duty Holders within the offshore industry, safety engineers and UK Government departments.