Risk Assessment In Process Industries Research Articles

Chronicles of security risk assessment in process industries: Past, present and future perspectives

Security incidents around the world causes enormous loss in terms of life, economy, and environment. The 9/11 ′triggered the serious onset of research initiatives in the field of security with a more specific focus on the protection of high sensitive and hazardous facilities. It is well known that technology is advancing in a very rapid phase, proportionally increasing the security risk of the facilities. Conventional deterministic risk techniques widely found their applications in the earlier stage but owing to the increasing dynamic nature of the security risk, probabilistic dynamic risk assessment models were developed over time. In this article, the authors attempted to present the evolution of security risk concepts, their present status, and their future scope in a precise and consolidated form. The last 20 years of development in the security risk assessment concept involving deterministic and dynamic risk assessment models and applications in security risk assessment relevant to physical security are discussed in this article. The objective of the article is to outline the past, current and future directions of security risk highlighting their strength, weakness and limitations.

An integrated framework based on intuitionistic fuzzy FMEA, COPRAS and TOPSIS for risk assessment in process industry

An integrated framework based on intuitionistic fuzzy FMEA, COPRAS and TOPSIS for risk assessment in process industry

Multi-hazard risk assessment in process industries: State-of-the-Art

Multi-hazard accidents in process industries, which can cause more severe consequences compared to individual accidents, have gained growing attention from administrators and scholars in recent years. With the development of process industries and the expansion of the urban area, high-risk zones may emerge in densely populated areas. Accurate risk assessment of the multi-hazard accidents in process industries is essential for protecting properties, human life, and the environment. This study reviews past studies on the risk assessment of three types of multi-hazard accidents in process industries: Natech events, domino effects, and concurrent hazards. The development trends of risk assessment of multi-hazard accidents are analyzed and the research gasps of past research are identified. Based on the identified gaps in previous research, future perspectives on multi-hazard research in process industries are discussed. To improve the assessment methods for multi-hazard risks, more advanced basic models and applicative risk analysis methods are required. Considering multi-hazard interactions and other factors are also important for process plants against multi hazards. This study can potentially contribute to developing better risk assessment models of multi-hazard accidents and therefore safer and resilient process industries.

A combined fuzzy DEMATEL and cloud model approach for risk assessment in process industries to improve system reliability

AbstractDecision‐making trial and evaluation laboratory (DEMATEL) analysis is an effective and comprehensive method for identifying accident factors and converting the relationships among them into a visual structural model. Traditionally, the mean value method is adopted to summarize the initial direct‐relation matrix, but it ignores the errors caused by differences in expert knowledge. In addition, a single qualitative risk assessment may not be sufficiently comprehensive and persuasive. The qualitative risk assessment results may not play a complete role in helping industrial plants carry out safety management. Therefore, this study proposes a quantitative risk assessment model based on the cloud model (CM) called the fuzzy DEMATEL‐CM. An assessment index model is established by identifying the hazards associated with a converter steelmaking system. Subsequently, fuzzy DEMATEL analysis is applied to determine the relationships among the assessment indices and calculate their weights. Then, the CM is utilized to calculate the risk levels of the assessment indices and determine the comprehensive risk level. Finally, a case study is introduced to verify the practicability and validity of this model, and it is observed that the model has a certain superiority in solving uncertain problems. The quantitative risk assessment results are helpful for preventing accidents to improve the reliability of converter steelmaking plants.

An integrated framework based on Intuitionistic fuzzy FMEA, COPRAS and TOPSIS for risk assessment in process industry

An integrated framework based on Intuitionistic fuzzy FMEA, COPRAS and TOPSIS for risk assessment in process industry

A fuzzy Bayesian network approach for risk analysis in process industries

Abstract Fault tree analysis is a widely used method of risk assessment in process industries. However, the classical fault tree approach has its own limitations such as the inability to deal with uncertain failure data and to consider statistical dependence among the failure events. In this paper, we propose a comprehensive framework for the risk assessment in process industries under the conditions of uncertainty and statistical dependency of events. The proposed approach makes the use of expert knowledge and fuzzy set theory for handling the uncertainty in the failure data and employs the Bayesian network modeling for capturing dependency among the events and for a robust probabilistic reasoning in the conditions of uncertainty. The effectiveness of the approach was demonstrated by performing risk assessment in an ethylene transportation line unit in an ethylene oxide (EO) production plant.

Worst maximum credible accidental scenarios (WMCAS) - A new methodology to identify accident scenarios for risk assessment

The identification of accident scenarios is the key step for risk assessment in process industries. In this paper, the methodology of worst maximum credible accidental scenarios (WMCAS) was put forward based on the analysis of the existing accident scenarios (the worst accident scenarios (WAS), the maximum-credible accident scenarios (MAS) and reference accident scenarios (RAS)). The principle and procedure of WMCAS identification have also been established. Firstly, WAS can be determined based on the Methodology for the Identification of Major Accident Hazards (MIMAH) used in the frame of the Accidental Risk Assessment Methodology for Industries (ARAMIS) project. Secondly, the modified method of credibility factor in MAS is used to calculate the credibility of WAS. Finally, the WMCAS will be identified by comparing the modified credibility results of WAS. Simultaneously, a pulverized coal gasification device was selected as an illustrative example to show the application of the methodology of WMCAS. The results show that the WMCAS for the device are pool fire for the methanol vessel, mechanical explosion for the gasification furnace, vapour cloud explosion (VCE) for the scrubber and VCE for the carbon dioxide absorption tower.

Human and organizational factor risk assessment in process industry and a risk assessment methodology (MEDIA) to incorporate human and organizational factors

Human and organizational factors (HOF) contribute to large number of accidents in process industries, therefore it is of prime importance to include HOF into risk assessment. In this paper, a newly developed methodology Method for Error Deduction and Incident Analysis (MEDIA) is presented. MEDIA is a taxonomy based HOF assessment methodology which can be used to quantify the HOF risk based on an accidental database (EMARS). Primarily, MEDIA analyzes different organizational characteristics and their effect on human action's outcome. This methodology also accounts for available risk reduction factors and critically of human action failure

Simultaneous measurement of ignition energy and current signature for brush discharges

Accurate prediction of the probability of ignition arising from charged insulators is a crucial element of risk assessment in process industry. Incendiary brush discharges can occur when a large or grounded conductor approaches a charged insulator in the presence of a flammable atmosphere. This paper describes ignition tests based on an IEC standard method and simultaneously recorded temporal distribution of current released in the discharges, using a discharge probe integrated with the ignition probe. Ignition and non-ignition results are compared with peak discharge current and charge transferred in the discharge. No clear ignition threshold was found for either of these parameters. No major differences were found between igniting and non-igniting waveforms.

Comparison of current signatures for brush discharges using different resistance values in the discharge probes

Incendiary brush discharges can occur when a large or grounded conductor approaches a charged insulator in the presence of flammable atmosphere. The probability of ignition of these discharges is essential to risk assessment in process industry. It is known that even if the total energy released in the discharge exceeds the minimum ignition energy (MIE), there may not be an ignition [1]. In a companion paper in this conference, we have reported simultaneous measurements of ignition and discharge current waveforms for brush discharges in an ethylene-air mixture in ignition tests based on an IEC standard test method [2]. In this paper we show that the resistance of the electrostatic discharge measurement system can have an effect on the peak discharge current signatures and charge transferred in the brush discharge from an insulating surface. The resistance of the discharge probe seems to affect the peak current value, but also to lesser extent the amount of charge transferred in the discharge.