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.     

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.     

Identification of managerial shaping factors in a petrochemical plant by resilience engineering and data envelopment analysis

Resilience engineering (RE) is a novel approach that is capable of controlling and limiting incidents and accidents. This study identifies managerial shaping factors in a petrochemical plant by RE and data envelopment analysis (DEA). To do this, a standard questionnaire containing resilient factors is completed by managers of a petrochemical plant. Then, the best DEA model is selected based on average efficiency and statistical test. In addition, sensitivity analysis are performed to identify the most important shaping factors. Reporting culture, management commitment, and preparedness are identified as the most important factors in this paper, respectively. Finally, the proposed model is validated and verified through statistical experiment. The proposed approach would help managers to have a comprehensive understanding of the plant with respect to the RE. To the best of our knowledge this is the first paper that examines resilient shaping factors in a petrochemical plant with respect to management and organization by DEA.     

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.     

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.     

Measuring and analyzing adaptive capacity at management levels of resilient systems

Resilience engineering (RE) is capable of handling disruptive events and controlling their consequences in process industries such as petrochemical plants. This study aims at analyzing the level of adaptive capacity and identifying effective factors on developing adaptive capacity in the organizational structure of process industries. The data of this study were obtained through direct observation and a structured questionnaire in a petrochemical plant. Managers at all levels participated in the survey. Data envelopment analysis (DEA), which is a mathematical approach, was used to compute and analyze the role of the factors contributing to adaptive capacity. The results indicated that reporting safety issues played a central role in enhancing adaptive capacity at all management levels. Both middle management and low-level management emphasized the importance of management commitment, whereas top-level management considered flexibility as a vital factor in managing disruptions and reducing accidents. The findings of this study could be useful for managers and other decision-makers to improve safety in process industries.     

IEC61511标准及在石化行业安全管理中的应用

功能安全的定量评定技术已成为确保石化行业安全生产的重要手段。针对石化行业普遍存在的功能安全问题,笔者以国际电工学会(IEC)专门制定的功能安全评定标准IEC61508及IEC61511为指导,介绍其标准制定的背景、目的、体系结构以及如何利用标准开展石化行业安全联锁系统(Safety Instrumented System,SIS)的安全与误跳车定量分析。通过对SIS开展定量安全评估,可发现联锁功能存在的安全不足与误跳车现象,对于提高我国石化行业安全生产水平具有重要的促进作用,标准中有关寿命周期功能安全管理方法及重要的工程经验也对提高我国石化安全生产水平具有借鉴作用。     

Human factors applied to alarm panel modernization of nuclear control room

Human factors deal with issues related to humans, their behavior and the physical aspect of the environment in which they work. A control room is a complex system where operators perform plant operation using control systems and carry out monitoring and administrative responsibilities. For safe operation of industrial installation, the performance of the control room crew plays an important role. In this respect, a well designed control room is crucial for safe and efficient operation. The aim of this paper is to propose a methodological framework applied to nuclear control room evaluation, through participatory ergonomics, using operator activity analysis and human factors questionnaire as aid tools. We describe a case study in which the methodology framework was used in the evaluation process of a nuclear control room. The information gathered made possible a series of recommendation for the adequacy of the control room design, assisting in the safety assessment of the nuclear plant operation and justifying the alarm panel modernization.     

基于模糊数学的石化企业安全状况评估系统

针对石化企业安全信息存在模糊性和随机性的特点,提出了一个多因素多指标石化企业安全状况模糊综合评价算法,基于这种算法,设计了一个石化企业安全状况评估系统,以安全管理、工艺运行管理、设备运行管理、清洁生产、安全教育和人员素质等因素为系统的输入,运用模糊逻辑理论,结合专家评分,定量计算出石化企业的安全等级情况。系统充分考虑了多个安全因素对安全状况的影响,融合了主观判断和客观计算,解决了石化企业安全评价中多因素多指标带来的烦琐评价过程和复杂运算的问题,为石油化工企业的安全管理提供相关理论依据和实践支持。实际应用表明,其结果与实际情况较为符合,该方法可以较好的提高石化企业安全现状综合评价的客观性和准确性。     

An entropy-based TOPSIS approach for analyzing and assessing crisis management systems in petrochemical industries

Crisis management systems should be assessed and updated in petrochemical industries due to hazards, such as fire and explosion. Successful crisis management systems can protect both personnel and property in the petrochemical industries. The present study aimed to assess crisis management systems of five petrochemical plants in terms of three aspects, including organizational aspects, human aspects, and technical aspects. A questionnaire was designed, encompassing 34 items to cover all three aspects at both management and staff levels. A multi-criteria decision making (MCDM) approach, including the entropy method and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), was used to analyze the collected data. The outcomes of the entropy method indicated that organizational and human aspects had the greatest influence on crisis management systems of the plants with 58% and 49% importance at management and staff levels, respectively. The crisis management systems of the investigated plants were ranked and analyzed using the TOPSIS approach. The findings of this study could assist managers and other decision-makers to address the issues of crisis management systems in petrochemical industries.     

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.     

Process safety data management program based on HAZOP analysis and its application to an ethylene oxide/ethylene glycol plant

HAZOP analysis is a process hazard analysis method that has been widely applied both within and outside the chemical processing industries. This paper presents a design method for a process safety data management program for petrochemical plants based on HAZOP analysis and demonstrates the steps of application involved in building a process safety data management system for an ethylene oxide/ethylene glycol production plant. Firstly, the production data files and relevant documents of the plants should be classified and stored in the program database as reference documents and treatment schemes for coping with abnormal situations should be collected and summarized as guidance documents. Secondly, the HAZOP analysis method is employed to identify all the dangerous deviations possibly existing in the production process of the ethylene oxide/ethylene glycol plant. Then, the relationships among the deviations, the reference documents and the guidance documents should be considered and evaluated. Finally, each dangerous deviation will be given a corresponding reference document and guidance document. The reference documents and guidance documents stored in the expert system can be utilized to help operators solve the corresponding technical problems and cope with abnormal situations. The process safety data management program will contribute to the identification, analysis and resolution of operation problems. When an abnormal situation occurs, according to the deviations exhibited in the system, the necessary reference documents and guidance documents will be quickly consulted by the operators, and an appropriate decision will be made to address the abnormal situation. Therefore, by using the process safety data management program, plant security and human safety in the petrochemical industries will be improved.     

Building an Executive Information System for Maintenance Efficiency in Petrochemical Plants—An Evaluation

This study used the manufacturing process in the petrochemical industries as an example and developed a dedicated maintenance programme and executive information system (EIS) for this industry. The software for EIS was established on a CMMS platform, with logical and extractive analysis used to store the information in a KPI databank. The system developed can provide plant managers and engineers with a complete summary of information and keep them updated regarding the present status of their maintenance efforts. The objective of this study was to establish a management system for maintaining knowledge in the petrochemical industries, such as the management of standard operating procedures (SOPs), historical records and the analysis of data for the facility. To design the software, a review of petrochemical facility was purposed to enhance the maintenance efforts and facilitate the decision-making process. The main functions of the system include asset reliability analysis, failure analysis and maintenance benefit cost analysis. For the petrochemical industry, the impact of safety and environment caused by equipment malfunction is more substantial than that of other industries. If executives can manage essential points effectively and make decisions according to a key performance index, risks to safety and environment, which result from equipment malfunction, can be decreased and safety can be enhanced for petrochemical refineries.     

An extension to Fuzzy Fault Tree Analysis (FFTA) application in petrochemical process industry

Fault Tree Analysis (FTA) is an established technique in risk management associated with identified hazards specific to focused fields. It is a comprehensive, structured and logical analysis method aimed at identifying and assessing hazards of complex systems. To conduct a quantitative FTA, it is essential to have sufficient data. By considering the fact that sufficient data is not always available, the FTA method can be adopted into the problems under fuzzy environment, so called as Fuzzy Fault Tree Analysis (FFTA). This research extends FFTA methodology to petrochemical process industry in which fire, explosion and toxic gas releases are recognized as potential hazards. Specifically, the case study focuses on Deethanizer failure in petrochemical plant operations to demonstrate the proposed methodology. Consequently, the study has provided theoretical and practical values to challenge with operational data shortage in risk assessment.     

A mathematical approach for retrofit and optimization of total site steam distribution networks

This paper presents a generic mathematical model for retrofitting the steam power plants in an industrial site. The industrial sector under review consists of one steel mill, one oil refinery, and several petrochemical plants, where only small-scale steam integration has been implemented before this study. The relevant unit models in a typical steam power plant are established, and the steam plant retrofit problem is formulated as a mixed-integer nonlinear program (MINLP). Feasible retrofit alternatives suggested by experienced field engineers are investigated in sequence to examine the revenue of those possible modifications. The first scenario examines operational optimization of existent plants; the second option allows installation of one new turbine and replacement of several boilers and turbines with lower efficiency; the third scenario considers using a steam ejector to upgrade the disqualified import steam in the oil refinery. The significant merits from these three retrofit alternatives show that the proposed MINLP formulation has been a great help to enhance the inter-plant steam integration in an industrial sector.     

催化裂解装置火灾爆炸危险性评价

道氏方法是对石化装置风险性进行量化评价的一种行之有效的方法,尤其是对装置的系统和单元的固有危险性及安全设施降低危险性的安全补偿作用进行认识和评价,采用道化学公司的火灾、爆炸危险指数法,对安庆石化炼油厂65×104t/a催化裂解装置的潜在火灾爆炸和反应危险性进行评价和分析,得到“严重”以上程度的单元有:加热炉、丙烷塔、丙烯塔、液化气储罐和汽油柴油储罐、反应器、瓦斯发生器、乙烷塔和稳定器,同时给出单元的危险等级和薄弱环节,为工厂的风险管理和安全管理决策提供了科学依据,并为降低装置风险提出了建议。     

How do different process options and evaluation settings affect economic and environmental assessments? A case study on methyl methacrylate (MMA) production processes

We present an investigation on how economic and environmental assessment results change when different process options or evaluation settings are considered. As the main case study the production technology of methyl methacrylate (MMA) is investigated. Six commercial processes using different reaction routes are modelled and evaluated with respect to their economic and environmental performance. On these six base case models different process options and evaluation settings are considered and the resulting impacts on the assessment results are quantified. Major findings of the study are that the more decision-variables become fixed, the smaller becomes the impact of the decisions still to be taken—but not only with respect to the economic performance but also with regard to the environmental assessment result. Along the process development steps the potential impacts on the economic and environmental performance decrease to the same degree. The results obtained for the evaluation settings do not show such a systematic pattern as those for the process options. This finding indicates that decision makers face many options in the economic and especially the environmental assessment of chemical processes which might lead to quite different magnitudes in variability due to either the choice of method or the choice of method parameters. This paper demonstrates that the resulting variability might be crucial with respect to the decision making outcome.     

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.