SAFETY AND SECURITY: WHAT ARE THE PARALLELS, AND WHY RESEARCH IS NEEDED?

there is no abstract, this is an opinion pape

Process safety performance indicators

For over 50 years to measure safety performance the Lost Time Incident Rate, LTIR was used. Fortunately, over the years the learning attitude towards accidents changed from a retrospective to a pro-active one. In the 90-s the safety management system was introduced. No management though, without the Deming cycle of Plan, Do, Check, Act, and checking, means the need of indicators. Existing LTIR-values were used not realizing these refl ect personal rather than process safety. In 2005 after the BP Texas City refi nery vapor cloud explosion, awareness of the difference broke through and Process Safety Leading and Lagging Metrics were formulated. In January 2012 an international conference was held in Brussels organized by EPSC and CEFIC. Results will be summarized. The paper will explain briefl y, where we are now, and what still is ahead

Does a HAZOP reveal to us all the hazards we need to know, or are we overlooking serious threats?

PresentationThe HAZOP process as part of a PHA has been well established and in LinkedIn groups discussions have been on the best supporting software and best practices; the latter, e.g., on different opinions whether a checklist and pre-population is desirable. Of course, all are apprehensive to missing a significant scenario. On the other hand, required time and effort is also a concern. That there is good reason for being concerned about hazard identification completeness appears from various studies over the years, e.g., in which in hindsight after an incident is analyzed whether the scenario had been predicted. In those studies figures of only half of the important scenarios identified are common. Over the years several efforts have been published of attempts to semi-automate the process. Intelligent/smart P&ID is a jump forward. A recent report on automated HAZOP from a highly experienced engineer who can look back on many years of using it, shows good success. More is in the pipeline. Yet, the experience, competence, spirit and ingenuity of a HAZOP team in brainstorming sessions remain needed to see and weigh the risks, although it can be doubtful that, as some assert, it is the single source. The present study comprehends a relatively modest attempt with means that are on every laptop to support a HAZOP study, given the availability of an intelligent P&ID. This Data-based semi- Automatic HAZard IDentification (DAHAZID), seeks to identify possible scenarios with a semi-automated system applying both HAZOP and FMECA. The new method will minimize the limitations of each method. This will occur by means of a thorough systematic preparation before the tools are applied. Rather than depending on reading drawings to obtain connectivity information of process system equipment elements, this research is generating and presenting in prepopulated work sheets linked components together with all required information and space to note HAZID results. Next, this method can be integrated with proper guidelines regarding process safer design and hazard analysis. To examine its usefulness, the method has been applied to a case study

How to Treat Expert Judgment? With certainty it contains uncertainty!

PresentationTo be acceptably safe one must identify the risks one is exposed to. It is uncertain whether the threat really will materialize, but determining the size and probability of the risk is also full of uncertainty. When performing an analysis and preparing for decision making under uncertainty, quite frequently failure rate data, information on consequence severity or on a probability value, yes, even on the possibility an event can or cannot occur is lacking. In those cases, the only way to proceed is to revert to expert judgment. Even in case historical data are available, but one should like to know whether these data still hold in the current situation, an expert can be asked about their reliability. Anyhow, expert elicitation comes with an uncertainty depending on the expert’s reliability, which becomes very visible when two or more experts give different answers or even conflicting ones. This is not a new problem, and very bright minds have thought how to tackle it. But so far, however, the topic has not been given much attention in process safety and risk assessment. The paper has a review character and will present various approaches with detailed explanation and examples

Can we verify and intrinsically validate risk assessment results? What progress is being made to increase QRA trustworthiness?

PresentationThe purpose of a risk assessment is to make a decision whether the risk of a given situation is acceptable, and, if not, how we can reduce it to a tolerable level. For many cases, this can be done in a semi-quantitative fashion. For more complex or problematic cases a quantitative approach is required. Anybody who has been involved in such a study is aware of the difficulties and pitfalls. Despite proven software many choices of parameters must be made and many uncertainties remain. The thoroughness of the study can make quite a difference in the result. Independently, analysts can arrive at results that differ orders of magnitude, especially if uncertainties are not included. Because for important decisions on capital projects there are always proponents and opponents, there is often a tense situation in which conflict is looming. The paper will first briefly review a standard procedure introduced for safety cases on products that must provide more or less a guarantee that the risk of use is below a certain value. Next will be the various approaches how to deal with uncertainties in a quantitative risk assessment and the follow-on decision process. Over the last few years several new developments have been made to achieve, to a certain extent, a hold on so-called deep uncertainty. Expert elicitation and its limitations is another aspect. The paper will be concluded with some practical recommendations

HAZOP: Our Primary Guide in the Land of Process Risks: How can we improve it and do more with its results?

PresentationAll risk management starts in determining what can happen. Reliable predictive analysis is key. So, we perform process hazard analysis, which should result in scenario identification and definition. Apart from material/substance properties, thereby, process conditions and possible deviations and mishaps form inputs. Over the years HAZOP has been the most important tool to identify potential process risks by systematically considering deviations in observables, by determining possible causes and consequences, and, if necessary, suggesting improvements. Drawbacks of HAZOP are known; it is effort-intensive while the results are used only once. The exercise must be repeated at several stages of process build-up, and when the process is operational, it must be re-conducted periodically. There have been many past attempts to semi- automate the HazOp procedure to ease the effort of conducting it, but lately new promising developments have been realized enabling also the use of the results for facilitating operational fault diagnosis. This paper will review the directions in which improved automation of HazOp is progressing and how the results, besides for risk analysis and design of preventive and protective measures, also can be used during operations for early warning of upcoming abnormal process situations

Study of FSRU-LNGC System Based on a Quantitative Multi-cluster Risk Informed Model

PresentationThe offshore LNG terminal, referred to as LNG floating storage unit or floating storage and re- gasification unit (FSRU), performs well on both building process and operation process. The LNG FSRU is a cost-effective and time efficient solution for LNG transferring in the offshore area, and it brings minimal impacts to the surrounding environment as well. This paper proposed a systematic method to integrate chemical process safety with maritime safety analysis. The evaluation network was adopted to process a comparison study between two possible locations for LNG offshore FSRU. This research divided the whole process into three parts, beginning with the LNG Carrier navigating in the inbound channel, the berthing operation and ending with the completion of LNG transferring operation. The preferred location is determined by simultaneously evaluating navigation safety, berthing safety and LNG transferring safety objectives based on the quantitative multi-cluster network multi-attribute decision analysis (QMNMDA) method. The maritime safety analysis, including navigational process and berthing process, was simulated by LNG ship simulator and analyzed by statistical tools; evaluation scale for maritime safety analysis were determined by analyzing data from ninety experts. The chemical process safety simulation was employed to LNG transferring events such as connection hose rupture, flange failure by the consequence simulation tool. Two scenarios, i.e., worst case scenario and maximum credible scenario, were taken into consideration by inputting different data of evaluating parameters. The QMNMDA method transformed the evaluation criteria to one comparable unit, safety utility value, to evaluate the different alternatives. Based on the final value of the simulation, the preferred location can be determined, and the mitigation measures were presented accordingly

A Refreshing Take: Analysing Accident Scenarios through Causal Network Topology Metrics

PresentationAccident causation investigation and even more hazard scenario identification are troubled by the complexity of interactions between three elements in a process facility: People, Plant and Procedures. Interactions are of various nature, such as physical change and information transfer, all influencing the process. To facilitate investigation the digraph network was applied as the most flexible visual aid to describe a causal structure. Such structure consists of nodes and edges representing an event or condition in the accident scenario and a causal link respectively. Attributing the nodes and edges to the type of interaction, numbers of the same type can be counted, and so two metrics are developed: The P3 Interaction Contribution (PIC). This is the proportion of nodes and edges associated with an interaction between People, Plant and Procedures. The Average Edge Weight. This relates to the proportion of events in the scenario that are associated with the logical AND gate conjunction from its causes (incident nodes), where the event requires more than one simultaneous cause. The technique was tried on four CSB accident descriptions. Interesting differences are seen. Also, in view of a paper accepted to be published in Safety Science the approach seems quite helpful in process hazard analysis