Fuzzy risk modeling of process operations in the oil and gas refineries

Operating several assets has resulted in more complexity and so occurrence of some major accidents in the refining industries. The process operations risk factors including failure frequency and the consequence components like employees' safety and environment impacts, operation downtime, direct and indirect cost of operations and maintenance, and mean time to repair should be considered in the analysis of these major accidents in any refinery. Considering all of these factors, the risk based maintenance (RBM) as a proper risk assessment methodology minimizes the risk resulting from asset failures. But, one of the main engineering problems in risk modeling of the complex industries like refineries is uncertainty due to the lack of information. This paper proposes a model for the risk of the process operations in the oil and gas refineries. The fuzzy logic system (FLS) was proposed for risk modeling. The merit of using fuzzy model is to overcome the uncertainty of the RBM components. This approach also can be accounted as a benchmark for future failures. A unified risk number would be obtained to show how the criticality of units is. The case study of a gas plant in an oil refinery is performed to illustrate the application of the proposed model and a comparison between the results of both traditional RBM and fuzzy method is made.For the case study, 26 asset failures were identified. The fuzzy risk results show that 3 failures have semi-critical level and other 23 failures are non-critical. In both traditional and fuzzy RBM methods, some condenser failures had the highest risk number and some pumps were prioritized to have the lowest risk level. The unit with unified risk number less than 40 is in the non-critical conditions. Proposed methodology is also applicable to other industries dealing with process operations risks.     

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.     

Risk-based maintenance policy selection using AHP and goal programming

Maintenance policy selection is a multiple criteria decision making. The criteria often considered are cost and reliability of maintenance. There has been a growing interest in using risk of accidents as a criterion for maintenance selection. This paper presents an approach of maintenance selection based on risk of equipment failure and cost of maintenance. Analytic hierarchy process (AHP) and goal programming (GP) are used for maintenance policy selection. A case study in a benzene extraction unit of a chemical plant was done. The AHP results show that considering risk as a criterion, condition based maintenance (CBM) is a preferred policy over time-based maintenance (TBM) as CBM has better risk reduction capability than TBM. Similarly, considering cost as a criterion, corrective maintenance (CM) is preferred. However, considering both risk and cost as multiple criteria, the AHP–GP results show that CBM is a preferred approach for high-risk equipment and CM for low risk equipment.     

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.     

A framework to estimate the risk-based shutdown interval for a processing plant

Petrochemical plants and refineries consist of hundreds of pieces of complex equipment and machinery that run under rigorous operating conditions and are subjected to deterioration over time due to aging, wear, corrosion, erosion, fatigue and other reasons. These devices operate under extreme operating pressures and temperatures, and any failure may result in huge financial consequences for the operating company. To minimize the risk and to maintain operational reliability and availability, companies adopt various maintenance strategies. Shutdown or turnaround maintenance is one such strategy. In general, shutdown for inspection and maintenance is based on the original equipment manufacturer's (OEM) suggested recommended periods. However, this may not be the most optimum strategy given that operating conditions may vary significantly from company to company.The framework proposed in this work estimates the risk-based shutdown interval for inspection and maintenance. It provides a tool for maintenance planning and decision making by considering the probability of the equipment or system for failure and the likely consequences that may follow. The novel risk-based approach is compared with the conventional fixed interval approach. This former approach, characterized as it is by optimized inspection, maintenance and risk management, leads to extended intervals between shutdowns. The result is the increase in production and the consequent income of millions of dollars.The proposed framework is a cost effective way to minimize the overall financial risk for asset inspection and maintenance while fulfilling safety and availability requirements.     

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.     

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.     

An evaluation of maintenance strategy using risk based inspection

Risk based inspection (RBI) methodology was proposed to evaluate the maintenance strategy in industrial process which was constructed in one of the units of Fujian Oil Refinery ISOMAX unit. Using classic definition of risk, both the probability and consequence of accident or failure were investigated respectively under the support of risk-specific code. All equipment in this unit were evaluated and categorized into five risk zone based on the RBI result which covered five levels. In addition, an application of the analytical hierarchy process (AHP) to select the most practicable maintenance strategy for equipment which was located in each risk rating scale was described. To arrange the hierarchic structure and evaluation, four main criteria were defined for pairwise judgments. Finally, four possible alternative strategies were proposed for administrators on the site.     

配电设备的风险评估与状态检修决策方法

针对当前配电设备采用的定期检修方式未将可靠性与经济性综合考虑的问题,提出1种基于风险评估结果确定配电设备状态检修决策的方法。首先,根据配电设备健康状态评估结果计算配电设备实时健康指数,利用指数模型对配电设备的实时故障率进行计算;然后,采用最小路法计算配网中所有设备的平均实时故障率,并结合停电时用户损失严重度、配电设备损失严重度和环境损失严重度确定配电设备故障后果严重度;最后,利用风险偏好型效用函数量化计算配电设备的经济运行风险水平,计算各配电设备的相对风险值,并以相对风险值为指标确定各配电设备的状态检修策略。结合算例对所提的方法进行验证,结果表明该方法合理有效。     

Application of risk based inspection in refinery and processing piping

In refineries and processing plants, the enormous amount of piping is more complex in distribution than other types of equipment. In general, compared with other types of equipment in these industries, more difficulty in inspection planning is encountered.

However, under-inspection or over-inspection can occur due to the lack of jurisdictional requirements on the inspection interval and method for piping, or the inspection interval being based only on piping service classifications in the existing regulations, such as API 570. This can result in unacceptable risks, along with costly loss of resources.

To lessen the piping risk level, more and more companies have adopted and applied risk based inspection (RBI) methodology, leading to risk reduction and cost benefits since the last decade. This study applied RBI methodology to optimize the inspection strategy of the piping in a refinery and petrochemical plants in Taiwan. Two actual case studies were corroborated better with quantitative RBI methodology than without the methodology in terms of risk and cost reductions.     

Priority analysis for risk factors of equipment in a hydraulic turbine generator unit

Ensuring the safe operation of hydropower stations is one of the key challenges for electric generation. Clearly the safe operation of such systems can only be archived with proper and effective maintenance scheduling. The objective of this study is to analyze, rank and prioritize the risk factors responsible for equipment failures of a hydraulic turbine generator unit (HTGU) based on operating data and expert elicitation. Here a simple qualitative risk evaluation model is proposed able to consider seven typical failures in HTGU. The proposed tool is applied for the risk prioritization of equipment failures, e.g. shaft torsion, misalignment, rotating fault, axis bend, runner fault, water guide, and wicket gate of a hydropower station in China. The obtained results have been compared against the actual statistics of equipment failures of a hydropower station in China, considered showing good agreement. All of these results provide theoretical guidance for digitalization realization of equipment failures.     

Risk-based maintenance (RBM): a quantitative approach for maintenance/inspection scheduling and planning

The overall objective of the maintenance process is to increase the profitability of the operation and optimize the total life cycle cost without compromising safety or environmental issues. Risk assessment integrates reliability with safety and environmental issues and therefore can be used as a decision tool for preventive maintenance planning. Maintenance planning based on risk analysis minimizes the probability of system failure and its consequences (related to safety, economic, and environment). It helps management in making correct decisions concerning investment in maintenance or related field. This will, in turn, result in better asset and capital utilization.

This paper presents a new methodology for risk-based maintenance. The proposed methodology is comprehensive and quantitative. It comprises three main modules: risk estimation module, risk evaluation module, and maintenance planning module. Details of the three modules are given. A case study, which exemplifies the use of methodology to a heating, ventilation and air-conditioning (HVAC) system, is also discussed.     

成套装置动态风险管理专家系统

传统的设备管理模式造成设备非计划停机次数较多、故障频繁、可靠性和可用性不高等问题。为了解决上述问题,开发了成套装置动态风险管理专家系统,该系统包括动态风险监控、数据存储、失效模式及损伤机理判别、动态风险评估、风险辅助分析5个流程。该系统通过GIS平台进行展示,使用户可以直观、方便地查找、定位管线和容器位置,实现了高风险设备的风险展示、管道剩余寿命不足报警功能和管道冲蚀图例展示。将该专家系统进行了工程应用,得到容器和管道的潜在损伤机及其风险等级,针对不同风险等级的设备,生成了不同的检维修策略,为工程应用带来了很大的方便。     

Study and application of Reliability-centered Maintenance considering Radical Maintenance

Radical Maintenance (RM) takes the root causes of failures as executive objects to make maintenance decisions. A Root Cause Analysis (RCA) is carried out on the function failure of equipment to perform RM and to create a maintenance plan using the combined methods of Failure Mode, Effects and Criticality Analysis (FMECA), and Fault Tree Analysis (FTA). Evaluation criteria and matrixes of criticality are used to evaluate the criticality level of failure modes. Moreover, Minimum Cut Sets (MCS) and importance calculation are applied to analyze the fault tree quantitatively. Based on our research, the concept and the analysis process of Reliability-centered Maintenance (RCM) considering RM are proposed and then applied to an actual engineering project in the petrochemical industry. The results of the application are presented through a maintenance strategy based on the project analysis by establishing the evaluation criteria and matrixes of criticality for petrochemical rotating machines and a fault tree of compressor vibrations. The direct causes of the induction of vibration faults in rotating machinery are classified according to the fault mechanism and frequency domain features in this paper. The research shows that using RM in the traditional RCM can help assign maintenance resources rationally and improve the quality of maintenance strategies.     

Development and application of equipment maintenance and safety integrity management system

Equipment management in process industry in China essentially belongs to the traditional breakdown maintenance pattern, and the basic inspection/maintenance decision-making is weak. Equipment inspection/maintenance tasks are mainly based on the empirical or qualitative method, and it lacks identification and classification of critical equipment, so that maintenance resources can’t be reasonably allocated. Reliability, availability and safety of equipment are difficult to control and guarantee due to the existing maintenance deficiencies, maintenance surplus, potential danger and possible accidents. In order to ensure stable production and reduce operation cost, equipment maintenance and safety integrity management system (MSI) is established in this paper, which integrates ERP, MES, RBI, RCM, SIL and PMIS together. MSI can provide dynamic risk rank data, predictive maintenance data and RAM decision-making data, through which the personnel at all levels can grasp the risk state of equipment timely and accurately and optimize maintenance schedules to support the decision-making. The result of an engineering case shows that the system can improve reliability, availability, and safety, lower failure frequency, decrease failure consequences and make full use of maintenance resources, thus achieving the reasonable and positive result.     

A new approach for facility siting using mapping risks on a plant grid area and optimization

The present work is focused on developing a methodology to find the optimal placement of a hazardous process unit and other facilities using optimization theory while considering a risk map in the plant area. Incidents can have possible consequences resulting from flammable gas releases, which can be evaluated by using consequence modeling programs. The probability of each incident can be derived from initial leak hole size estimation through event tree analysis. In this methodology the plant area was divided into square grids and risk scores were estimated for each grid. The overall cost is a function of the probable cost of property damage due to fires or explosions and the interconnection cost including piping, cable, and management. The proposed approach uses a mixed integer linear optimization programming (MILP) that identifies attractive locations by minimizing the overall cost. A case study is presented for a hexane–heptane separation facility that considers the meteorological data for the given area in order to show the applicability of the proposed methodology. Results from this study will be useful in assisting the selection of locations for facilities and for risk management.     

油气集输站场失效可能性定量评价方法研究*

为了保证油气集输站场的安全生产和运行,基于标准《Risk-based Inspection Methodology》（API RP 581 2016）和可靠性分析方法GO法,提出1种可完全定量的站场失效可能性评价方法,为站场的全定量风险评价方法提供依据和参考。首先,分析站场内各设备的失效机理,计算其失效概率;然后,根据站场工艺特点,将其划分为若干个子系统,利用GO操作符的定量计算公式,确定各子系统及站场整体的失效可能性值;最后,以某油田联合处理站为实例,采用该方法对其工艺设备、站场子系统及站场整体的失效概率进行计算和分析,确定该站场的失效可能性等级。研究结果表明:通过失效可能性定量评价可使站场风险评价更加量化直观,为站场维护及安全生产运行工作提供更加客观的依据。     

Calibrate failure-based risk assessments to take into account the type of chemical processed in equipment

Currently, failure-based risk assessments in the process industry do not empirically take into account the type of chemicals processed in equipment, mainly because chemical-specific failure rate data barely exist. This paper suggests a methodology to calibrate failure-based risk assessment predicated on the chemical being processed in equipment. The methodology uses a data mining tool known as the association rule. Specifically, the lift association rule is utilized (the Lift Methodology). By extracting equipment failure information from incident databases based on the chemical involved in the process, the Lift Methodology leads to more accurate equipment-related risk assessment.     

Risk-based shutdown management of LNG units

Global demand for natural gas may double by 2030, with Liquefied Natural Gas (LNG) growing perhaps fivefold - driven by continued cost reduction. Propane Pre-cooled Mixed Refrigerant (PPMR) of Air Products and Chemicals Inc. (APCI) currently holds 78% of the liquefaction plants on the market. Since the PPMR process has the largest production capacity, its operational reliability needs to be high as any failure may result in catastrophic consequences. Therefore, operational reliability has a key importance in LNG plants. To achieve an acceptable reliability, usually, a constant interval of a preventive maintenance method is used. The limitation of such a method is that the shutdown strategy is not optimum. This study focuses on determining a risk-based shutdown management strategy for APCI plants with capacity of 4.5 million tons per annum. To achieve the minimum risk for the expected life of an LNG plant, a combination of preventive maintenance, active redundancy and standby redundancy is considered. Results of this study reveal that such a combination can significantly reduce the operational risk. This combination improves the plant reliability and maintains it above a minimum operational reliability.