Fire incident at a refinery in West Malaysia: the causes and lessons learned

Refineries are major hazard installations (MHI) which possess large quantities of hazardous substances. Refineries are characterized by high complexity and tight-coupled organization. Due to the high complexity and level of interaction among subsystems, designers and operators are unable to predict failures at the refinery units. The world has seen many incidents in refineries through leakage, fire and explosions. The consequences of the accidents sometimes extend beyond the boundary of the property and reach the neighboring residents. This paper reviews refinery incidents worldwide and also outlines the causes of a fire incident at a refinery in West Malaysia and the lessons learned.     

Developing a risk-based maintenance model for a Natural Gas Regulating and Metering Station using Bayesian Network

During the last decades, the vital role of maintenance activities in industries including natural gas distribution system has cleared up progressively. High costs may induce to reduced maintenance and, in turn, lead to a lower availability and high risk of undesired events. Therefore, a probabilistic model, based on an acceptable level of risk, is required to avoid under and over estimation of maintenance time interval. This paper presents an advanced Risk-based Maintenance (RBM) methodology to optimize maintenance time schedule. Bayesian Network (BN) is applied to model the risk and the associated uncertainty. The developed method can assist the asset managers to work out the exact maintenance time for each component according to the risk level. To demonstrate and discuss the applicability of the methodology, a case study of Natural Gas Reduction and Measuring Station in Italy is considered. Results prove that the most critical components are the calculator and pilots, while the most reliable one is the odorization. Furthermore, the pressure and temperature gauge (PTG), the remote control system (RCS) and the meter are predicted as the components that require less time to transit from minor risk to catastrophic risk.     

Development of a risk-based maintenance (RBM) strategy for a power-generating plant

The unexpected failures, the down time associated with such failures, the loss of production and, the higher maintenance costs are major problems in any process plant. Risk-based maintenance (RBM) approach helps in designing an alternative strategy to minimize the risk resulting from breakdowns or failures. Adapting a risk-based maintenance strategy is essential in developing cost-effective maintenance policies.The RBM methodology is comprised of four modules: identification of the scope, risk assessment, risk evaluation, and maintenance planning. Using this methodology, one is able to estimate risk caused by the unexpected failure as a function of the probability and the consequence of failure. Critical equipment can be identified based on the level of risk and a pre-selected acceptable level of risk. Maintenance of equipment is prioritized based on the risk, which helps in reducing the overall risk of the plant.The case study of a power-generating unit in the Holyrood thermal power generation plant is used to illustrate the methodology. Results indicate that the methodology is successful in identifying the critical equipment and in reducing the risk of resulting from the failure of the equipment. Risk reduction is achieved through the adoption of a maintenance plan which not only increases the reliability of the equipment but also reduces the cost of maintenance including the cost of failure.     

Dynamic management of human error to reduce total risk

Safety management in companies at the limit of risk criteria must be implemented in order to survive in the very aggressive and competitive environment of modern society. It implies that the risk in process industries is crossing the limit of safe practices. Most major accidents consist of human errors and mechanical component failures, and cannot be explained by a stochastic coincidence of independent events. This work focuses on the coincidence of human error and mechanical failure to introduce a concept of dynamic management of human error. By the dynamic management of human error during a short period, when a mechanical component is temporarily unavailable during periodic testing or maintenance, the probability of a major accident may be reduced significantly without additional investment on improving safety. For the periodically-tested standby component, the majority of total average unavailability of the component may be recognized by operators or workers as well as maintenance mechanics. During this short period, an appropriate dynamic management of human error for improving human performance temporarily may be very effective in reducing total risk in industries. The dynamic management of human error may be a useful method to prevent loss effectively in the process industries     

Process industry accidents in Sri Lanka: Analysis and basic lessons learnt

Accidents in the process industry could be prevented or reduced by having good safety management measures. Such preventive measures could be further improved through the experiences and lessons learnt from past accidents. Therefore, analysis results of past accidents are valuable sources of information for determining root causes and as case material to prevent and reduce the adverse consequences of accidents in the process industry.This paper looks at accidents in the process industry that have occurred in the past 10 years from 1997 to 2006 in Sri Lanka to gain an understanding of the nature and consequences of accidents. Lessons and main areas of concern to improve safety in the Sri Lanka process industry are discussed. The analysis is done for different event types based on specific operating process stage during which the accident occurred such as processing, loading and unloading, repair and maintenance and storage, the immediate effect types such as fire, explosion, chemical releases and emissions and the consequences of each accident. Fire incidents were observed in 38 accidents analyzed. The results show that the highest number of accidents has occurred during processing operations followed by accidents during maintenance and repair work. The cause analysis shows that many accidents have occurred due to technical and human failures.The accidents are then classified according to the severity of the consequences in order to compare the nature of accidents experienced in Sri Lanka with respect to accidents in other countries in the world.     

Fuzzy dynamic risk-based maintenance investment optimization for offshore process facilities

A methodology for maintenance planning is developed which helps in improving the reliability of the components and safety performance in process facilities. This methodology helps design an optimum safety maintenance investment plan by integrating the optimization techniques and a fuzzy dynamic risk-based method. Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) is applied to deal with uncertain data. The proposed approach employs multi-experts’ knowledge which helps to optimize the maintenance investments. A separator system in an offshore process facility platform is selected as a case study to demonstrate the application of the proposed methodology. A practical example in the separator system is surveyed and potential failures and Basic Events (BEs) are identified. Finally, a risk-based maintenance plan is provided for future safety investment analysis. The results indicate that the developed methodology estimates the risk more accurately, which enhances the reliability of future process operations.     

Equipment failures and their contribution to industrial incidents and accidents in the manufacturing industry

Accidental events in manufacturing industries can be caused by many factors, including work methods, lack of training, equipment design, maintenance and reliability. This study is aimed at determining the contribution of failures of commonly used industrial equipment, such as machines, tools and material handling equipment, to the chain of causality of industrial accidents and incidents. Based on a case study which aimed at the analysis of an existing pulp and paper company's accident database, this paper examines the number, type and gravity of the failures involved in these events and their causes. Results from this study show that equipment failures had a major effect on the number and severity of accidents accounted for in the database: 272 out of 773 accidental events were related to equipment failure, where 13 of them had direct human consequences. Failures that contributed directly or indirectly to these events are analyzed.     

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.     

A study of storage tank accidents

This paper reviews 242 accidents of storage tanks that occurred in industrial facilities over last 40 years. Fishbone Diagram is applied to analyze the causes that lead to accidents. Corrective actions are also provided to help operating engineers handling similar situations in the future. The results show that 74% of accidents occurred in petroleum refineries, oil terminals or storage. Fire and explosion account for 85% of the accidents. There were 80 accidents (33%) caused by lightning and 72 (30%) caused by human errors including poor operations and maintenance. Other causes were equipment failure, sabotage, crack and rupture, leak and line rupture, static electricity, open flames etc. Most of those accidents would have been avoided if good engineering have been practiced.     

TORAP—a new tool for conducting rapid risk assessment in petroleum refineries and petrochemical industries

The use of a new computer-automated tool TORAP (TOol for Rapid risk Assessment in Petroleum refinery and petrochemical industries) is demonstrated through a rapid and quantitative risk assessment of a typical petroleum refinery. The package has been applied for an appraisal of the risks of accidents (fires, explosions, toxic release) posed by different units of the refinery, and to identify steps to prevent/manage accidents. The studies reveal that TORAP enables a user to quickly focus on the accidents likely to occur, and enables forecasting the nature and impacts of such accidents. This information is directly utilisable in identifying “soft” spots and in taking appropriate remedial measures to prevent or control accidents. The special attributes of TORAP are: (a) a wide range of applications—achieved by incorporating models capable of handling all types of industrial fires and explosions, (b) sophistication—brought about by including state-of-the-art models developed by these authors and others, (c) user-friendliness—achieved by incorporating on-line help, graphics, carefully formatted output, and, above all, an automatic module with which even a lay user can conduct risk assessment. The entire package, especially its automatic module, is supported by an extensive knowledge-base built into the software.     

Loss prevention in turnaround maintenance projects by selecting contractors based on safety criteria using the analytic hierarchy process (AHP)

Turnaround maintenance (TAM) is a usual plant shutdown that is done by process industries to perform asset inspections, repairs, and overhauls. TAM engineering projects are needed on a periodic basis to optimize a plant's performance. Process industrial plants usually don't have enough in-house manpower to carry out needed TAM jobs; it is not uncommon for a process industrial plant to outsource its TAM manpower supply to external contractors. This will create a peculiar management challenge regarding how to assure orientation of safety practices for the newly hired labor. Although accidents during process plant shutdowns may have severe consequences, the safety management systems in place for many companies only cover normal operations and few explicitly address TAM projects. Usually, contractors are evaluated from a safety perspective after handling the project by monitoring safety indicators such as number of injuries, incidents, etc. This paper emphasizes safety attributes to be included in selecting contractors at the bidding stage to assure loss prevention and better safety orientation during TAM implementation. The paper starts with reviewing TAM literature and defining main needed safety attributes to prequalify contractors. It develops an analytic hierarchy process (AHP) model that is applied to rank TAM contractors' selection. A case study is presented for a petrochemical plant in Saudi Arabia to demonstrate the AHP model.     

Risk management in operations of petrochemical plants: Can better planning prevent major accidents and save money at the same time?

This paper presents an argument that improvement in operational safety can be achieved concurrently with increased operational efficiency. This is a fundamentally different viewpoint on the investment in safety. Traditionally, the cost of providing safety barriers is offset by the expected benefits of reducing the occurrence and severity of accidents. Our approach departs from this method of accounting for safety improvements and focuses on planning as a means of managing systems' response uncertainty and consequently reducing both major accident risk and the cost of operations. The scope of the paper is limited to interventions such as maintenance and repairs and defined in the context of major accident prevention e.g. hydrocarbon leaks. However, the developed methodology is general enough to be applied across the spectrum of process industry facilities and operations.     

Allocation of performance shaping factors in the risk assessment of an offshore installation

Offshore oil production is one of the most important human productive activities. There are many risks associated with the process of constructing a subsea well, pumping oil to the platform, and transporting it to refineries via underwater pipes or oil tankers. All actions performed by workers in those operations are influenced by specific working conditions, involving the use of complex systems. Contextual factors such as high noise, low and high temperatures and hazardous chemicals are considered to be contributors to unsafe human actions in accident analysis and also give a basis for assessing human factors in safety analysis. Some failure modes are particularly dangerous and can result in severe accidents and damage to humans, the environment and material assets. Fires and explosions on oil rigs are some of the most devastating types of offshore accidents and can result in long-term consequences. The most typical root causes related to accidents include equipment failure, human error, environmental factors, work organization, training and, communication, among others. The principal objective of this study is to propose a methodological framework to identify the factors that affect the performance of operators of an offshore unit for oil processing and treatment. In this phase, an ergonomics approach based on operators' work analysis is used as a supporting tool. After identification of factors that affect the performance of operators, a decision-making model based on AHP (analytic hierarchy process) is applied to rank and weight the principal performance shaping factors (PSFs) that influence safe operations. The next step involves the use of the SHELLO model to group the main PSFs in elements named software, hardware, environment, liveware and organization. In the last phase, a relevant accident that occurred aboard a floating production storage and offloading (FPSO) vessel is analyzed. The allocation process of the factors that affect the operator's performance in risk assessment was developed through fuzzy logic and the ISO 17776 standard.     

Maintenance-related major accidents: Classification of causes and case study

The potential for major accidents is inherent in most industries that handle or store hazardous substances, for e.g. the hydrocarbon and chemical process industries. Several major accidents have been experienced over the past three decades. Flixborough Disaster (1974), Seveso Disaster (1976), Alexander Kielland Disaster (1980), Bhopal Gas Tragedy (1984), Sandoz Chemical Spill (1986), Piper Alpha Disaster (1988), Philips 66 Disaster (1989), Esso Longford Gas Explosion (1998), Texas City Refinery Explosion (2005), and most recently the Macondo Blowout (2010) are a few examples of accidents with devastating consequences.Causes are being exposed over time, but in recent years maintenance influence tends to be given less attention. However, given that some major accidents are maintenance-related, we intend to concentrate on classifying them to give a better insight into the underlying and contributing causes.High degree of technological and organizational complexity are attributes of these industries, and in order to control the risk, it is common to deploy multiple and independent safety barriers whose integrity cannot be maintained without adequate level of maintenance. However, maintenance may have a negative effect on barrier performance if the execution is incorrect, insufficient, delayed, or excessive. Maintenance can also be the triggering event.The objectives of this article are: (1) To investigate how maintenance impacts the occurrence of major accidents, and (2) To develop classification schemes for causes of maintenance-related major accidents.The paper builds primarily on model-based and empirical approaches, the latter being applied to reports on accident investigation and analysis. Based on this, the Work and Accident Process (WAP) classification scheme was proposed in the paper.     

A hybrid model for human factor analysis in process accidents: FBN-HFACS

Human factors are the largest contributing factors to unsafe operation of the chemical process systems. Conventional methods of human factor assessment are often static, unable to deal with data and model uncertainty, and to consider independencies among failure modes. To overcome the above limitations, this paper presents a hybrid dynamic human factor model considering Human Factor Analysis and Classification System (HFACS), intuitionistic fuzzy set theory, and Bayesian network. The model is tested on accident scenarios which have occurred in a hot tapping operation of a natural gas pipeline. The results demonstrate that poor occupational safety training, failure to implement risk management principles, and ignoring reporting unsafe conditions were the factors that contributed most failures causing accident. The potential risk-based safety measures for preventing similar accidents are discussed. The application of the model confirms its robustness in estimating impact rate (degree) of human factor induced failures, consideration of the conditional dependency, and a dynamic and flexible modelling structure.     

Accidents: A discrepancy between indicators and facts!

Despite, the overwhelming amount of currently available safety management systems (and accompanying tools) accidents with hazardous substances still occur every now and then in the process industries.In this paper a large number of recently occurred accidents in the process industries are analysed showing that reoccurring disruptions during daily operation were present in the causal path of these accidents. The reoccurring disruptions can be seen as pre-warning signals. Their existence forms a gap with the common proactive safety indicators. This gap exists of information, already present and available in daily operation, of which it is UNKNOWN (to the local assessor) that it may lead to unsafe situations/accidents, e.g. maintenance backlogs, quality reports, etc.It is argued that these reoccurring events should be considered to be included in the safety indicators after assessment by an extended body of knowledge, because these events seem to become increasingly important regarding the prevention of accidents that still occur nowadays.     

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.     

Development of a risk-based maintenance strategy using FMEA for a continuous catalytic reforming plant

Petrochemical facilities and plants require essential ongoing maintenance to ensure high levels of reliability and safety. A risk-based maintenance (RBM) strategy is a useful tool to design a cost-effective maintenance schedule; its objective is to reduce overall risk in the operating facility. In risk assessment of a failure scenario, consequences often have three key features: personnel safety effect, environmental threat and economic loss. In this paper, to quantify the severity of personnel injury and environmental pollution, a failure modes and effects analysis (FMEA) method is developed using subjective information derived from domain experts. On the basis of failure probability and consequence analysis, the risk is calculated and compared against the known acceptable risk criteria. To facilitate the comparison, a risk index is introduced, and weight factors are determined by an analytic hierarchy process. Finally, the appropriate maintenance tasks are scheduled under the risk constraints. A case study of a continuous catalytic reforming plant is used to illustrate the proposed approach. The results indicate that FMEA is helpful to identify critical facilities; the RBM strategy can increase the reliability of high-risk facilities, and corrective maintenance is the preferred approach for low-risk facilities to reduce maintenance expenditure.     

Dynamic failure assessment of an ammonia storage unit: A case study

Chemical Process Industries usually contain a diverse inventory of hazardous chemicals and complex systems required to perform process operations such as storage, separation, reaction, compression etc. The complex interactions between the equipment make them vulnerable to catastrophic accidents. Risk and failure assessment provide engineers with an intuitive tool for decision making in the operation of such plants. Abnormal events and near-miss situations occur regularly during the operation of a system. Accident Sequence Precursors (ASP) can be used to demonstrate the real-time operating condition of a plant. Dynamic Failure Assessment (DFA) methodology is based on Bayesian statistical methods incorporates ASP data to revise the generic failure probabilities of the systems during its operational lifetime.In this paper, DFA methodology is applied on an ammonia storage unit in a specialized chemical industry. Ammonia is stored in cold storage tanks as liquefied gas at atmospheric pressure. These tanks are susceptible to failures due to various abnormal conditions arising due process failures.Tank failures due to three such abnormal conditions are considered. Variation of the failure probability of the safety systems is demonstrated. The authors use ASP data collected from plant specific sources and safety expert judgement. The failure probabilities of some safety systems concerned show considerable deviation from the generic values. The method helps to locate the components which have undergone more degradation over the period and hence must be paid attention to. In addition, a Bayesian predictive model has been used to predict the number of abnormal events in the next time interval. The user-friendly and intuitive nature of the tool makes it appropriate for application in safety assessment reports in process industries.