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The HAZOP and LOPA methods are commonly used for qualitative hazard identification and semi-quantitative assessment of risk in the process industries. Integration of HAZOP and LOPA techniques into a single study has provided the practical advantage of utilizing the same team of subject matter experts to complete evaluation of hazard scenarios, identify needs for further risk reduction, recommend specific safeguards required and confirm resulting residual risk is acceptable. While practical and efficient, the one-step comprehensive integrated HAZOP/LOPA method can have pitfalls. In particular, use of LOPA alone to confirm risk acceptability can lead to complex solutions to meet order-of-magnitude threshold requirements for risk reduction and restrictive requirements for independent protection layers (IPLs). Quantitative methods are sometimes required beyond HAZOP/LOPA to obtain a more precise evaluation of identified hazards and benefits of the associated safeguards. This article presents a risk assessment approach incorporating advanced analysis, including human factors task, fault tree and cost-benefit analysis, following HAZOP/LOPA analysis. To illustrate this approach, an example is shown on the selection of appropriate engineering design options for cyclic regeneration of dense phase ethylene treaters, which have unique safety concerns. Using advanced analysis, a cost effective design solution is developed and is shown to reduce risk to as low as reasonably practicable (ALARP). © 2016 American Institute of Chemical Engineers Process Saf Prog 36: 192–201, 2017

Flare systems are typically designed to meet recognized and generally accepted good engineering practice for foreseeable vent and relief scenarios. API 521 [American Petroleum Institute, ANSI/API Standard 521 Guide for Pressure-Relieving and Depressuring Systems: Petroleum Petrochemical and Natural Gas Industries, Fifth Edition, American Petroleum Institute, 2007] allows for multitrain units to be protected by the same flare system. Therefore, these systems must be reliable, available, auditable, and maintainable. However, any designer's concern should be the possibility of a common-cause failure (CCF) that impairs several safeguards or causes a plant-wide failure. A shutdown incident can result in flare relief demands that are higher than the designed capacity. CCF is defined as a failure of more than one device, function, or system due to the same cause. Examples of common causes are errors in design, installation, maintenance, or operation of redundant components. To ensure that the designed flare capacity for a Liquefied Natural Gas (LNG) facility is appropriate, it is necessary to assess the frequency of relieving combinations that have the potential of exceeding flare capacity during a shutdown which is the result from a CCF. A common practice for this purpose is to perform probabilistic risk assessment using fault tree analysis (FTA) techniques during the front-end engineering design stage. However, CCFs are rarely or not commonly considered in the analysis. CCFs might have a significant impact on the final calculations, resulting in probabilities of overloading the flare system by one or more orders of magnitude greater, with the potential of not meeting the project's tolerability threshold. The analysis starts with the identification of CCF scenarios resulting in relief loads from one and multiple trains. Following the identification of these scenarios, the frequency of such events is quantified and compared with each facility's tolerability threshold. Historical data from published sources were used to calculate the likelihood for both CCFs and their impacts. A FTA was used to illustrate the various outcomes that may arise from a CCF producing simultaneous reliefs. The scope of each analysis included a facility in multitrain operation with common infrastructure and supporting utility systems. A one train (initial startup case) analysis was done for a baseline comparison, and different scenarios were then analyzed for potential flare overload (e.g., gas compressors from two or more trains failing to stop on demand once blowdown has started, coupled with feed gas valves failing to close). Finally, the probability of exceeding the flare capacity and the associated consequences were compared against the project's qualitative risk assessment matrix to determine if the probability of flare exceedance was tolerable. © 2014 American Institute of Chemical Engineers Process Saf Prog 34: 250–258, 2015

Bow-tie diagrams are emerging as a very useful tool to depict and maintain an up-to-date, real-time, working risk management system embedded in daily operations. They are a proven concept in the worldwide offshore industry. These diagrams provide a pictorial representation of the risk assessment process. This article introduces the bow-tie concept to the downstream and chemical process industries in the United States. The authors believe that bow-tie diagrams can be a resourceful method in the safety and risk practitioner's toolkit to improve performance of the hazard identification and risk assessment process and to demonstrate that major hazards are identified and managed to as low as reasonably practicable. Because of their graphical nature, the biggest advantage of bow-tie diagrams is the ease to understanding of risk management by upper management and operations groups. © 2013 American Institute of Chemical Engineers Process Saf Prog, 33: 26–35, 2014

The principle that the risks for a facility should be reduced to As Low As Reasonably Practicable (ALARP) increasingly is embraced around the world. This article describes how the principle can be used to establish both individual and group risk tolerance criteria that are needed for risk analysis studies using techniques such as Layers of Protection Analysis. The consideration of uncertainties in risk estimates in the ALARP context and the use of the precautionary principle are also described, and the use of cost–benefit analysis in applying the ALARP principle is discussed. Other related principles used in risk management are described. © 2013 American Institute of Chemical Engineers Process Saf Prog 33: 36–40, 2014