The method wedfor the selection ofa Safety Integrity Level (SIL) for a Sa ety Instrumented System (SIS) o a hazardous consequences and likelihood, as well as the effectiveness of process safeguard. Process Sajty Management, under OSHA 29 CFR Part 191 0, requires an assurance of mechanical integrity for all emergency shutdown systems andsajty critical controls. The International Society for Measurement and romulgated an industy standard S84.01, to States, and the International Electrochemical Commission (IEC) created a similar standard for Europe. These standard specifi that all electrical electronic, and rogrammable electhat thg, achieve a spec$ed SIL. These standard arepe@rmance baed givingguidunce on how to select and achieve an appropriate SIL for a given SIS, but are not prescriptive to any particular method or equipment. The SIL selection is critical since in many cases the SIS is the h t hyer ofprotection for the prevention of hazardous events. The probability offailure on demand of a SIS are quantitatively categorized into discrete integrity h e h (i.e. SIL) by both indwty standard. Since neither standard spec$es re uirements for intep;ty level selection, ing the risk ofa process to a levelacceptable or tolerable to each individual company. In this pa er, current indw practicesfor the selection of estimation of risk reduction that the SIS willprovide for a given process. The level of effort, required expertise, and accuracy of the methods are also compared to assist the reader in choosing the appropriate SIL selection methodology. process shou d we a risk based approach to eva Ir uate potential assist Contra in l(ISA)f comp iance with the PSM regulation in the United tronic system, used in SISs, are require a! to be desiped such the determination of a s4 IL for a SIS is based solely on reduc-SILs are eva P uated to illustrate x ow each methodprovides an _ _ ~ * The authou, Edward M. Marszal, I? E., can be reached via

In the nitrogen fertilizer industry, potentially severe impacts can stem from toxic, fire, and explosion hazards from accidental releases and hazards associated with failures in high pressure equipment. While consequence analysis can be used to calculate the severity (as measured by the personnel or buildings in the hazard zone), the very large zones associated with some of the most severe scenarios essentially place the entire facility within the hazard zone, leaving few practical options to mitigate the consequence. Using a quantitative risk analysis approach, which evaluates both the consequence and likelihood of potential events at fertilizer sites, provides additional insight to help make informed decisions about the best way to minimize the risk exposure. © 2012 American Institute of Chemical Engineers Process Saf Prog, 2012

Facility siting methods to optimize the layout of industrial facilities for risk reduction have been evolving for decades from subjective views, standards, and guidelines to quantitative numerical analysis. The authors of this paper have tossed out the past, moved beyond the present, and taken out their crystal balls to provide a discussion around the future of facility siting by focusing on technology driven enhancements associated with three main themes: mainstreaming of current advanced analysis techniques into the base case methodology, incorporating company and/or site specific data trending and analytics to operationalize the studies, and the potential transformational change to machine learning‐based predictive risk management. With technological advancements touching nearly every area of business, it is no surprise that it is also changing the landscape of consequence and risk‐based facility siting approaches. As with all markets, the customer will be a key driver for the advancements of technical safety studies to suit their adapting needs. However, as this article will show, personnel conducting facility siting studies are also using technological advancements to challenge the status quo by improving data fidelity, increasing the robustness and depth of analysis, and providing improved insights to aid decision making.

There are several factors that make the establishment of risk criteria a daunting task that few want to undertake. Nonetheless, for large global corporations, it is likely that one or more facilities have to meet governmental requirements. For US facilities, there is an incentive to having risk criteria in that it allows greater flexibility in complying with the updated API Recommended Practice 752 on siting of occupied permanent buildings. Having corporate risk criteria is imperative to ensure that facilities and operations that are not in “regulated jurisdictions” have a consistent framework to make risk‐related decisions. Risk criteria range from the use of the traditional risk matrix (consequence vs. likelihood) to the more quantitative risk criteria that include geographic risk (individual risk) and/or societal risk criteria. This article discusses the steps necessary to help companies develop robust defendable risk criteria that facilitate decision making. Potential pitfalls are also presented and discussed including: (a) the potential to develop criteria that are unachievable or too lax, (b) developing criteria that are inconsistent with other established programs in the company, and (c) reconciling the needs between unit level criteria and business or group level criteria. Typical risk‐tolerance criteria, and examples of issues and pitfalls that are commonly faced by companies developing such criteria, are also presented. © 2012 American Institute of Chemical Engineers Process Saf Prog, 2012

An expert system known as the Automated Project Design System (APDS TM) has been developed to assist process and facilities engineers in performing preliminary feasibility studies, optimization studies, and provide the basic information required for the initiation of the detailed design for offshore oil and gas production facilities.Given the feedstock and product specifications, the expert system produces a preliminary process flow diagram showing all major pieces of equipment and determines all utility system requirements. Rigorous material and energy balance calculations are done via an interface to a conventional process simulator. All of the required equipment is sized and an estimated cost for each item is produced. An overall cost estimate for the production facility is also produced. Various reports, drawings, and equipment datasheets are generated to summarize the final results. The system is extremely flexible and allows the user to easily change input parameters, to customize equipment sizes and costs and to produce customized reports containing whatever information is desired.