The Risk Analysis Screening Tool: Part I, overview. Issue 2 (3rd March 2020)

• Record Type: Journal Article
• Authors: Vaughen, Bruce K.; Hurban, David A.; First, Kenneth; Ness, Al
• Is Part Of: Process safety progress. Volume 39:Issue 2(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-03-03
• Subjects: barrier -- hazard identification -- incident scenario -- layer of protection -- layer of protection analysis -- process hazards analysis -- risk analysis; Chemical plants -- Management -- Periodicals; 660
• DOI: 10.1002/prs.12142
• Languages: English
• ISSNs: 1066-8527

Abstract

Abstract: The Dow Chemical Company has provided for international use a set of tools to help other companies effectively understand and manage their process safety hazards and risks, helping the global process safety community improve their process safety performance. The tools described in this paper were generously donated to the Center for Chemical Process Safety (CCPS) and the European Process Safety Centre (EPSC). What makes this donation special is that small and large companies can use the Risk Analysis Screening Tool (RAST) and the Chemical Hazards Engineering Fundamentals (CHEF) tools to help validate, screen, and prioritize between their process risks. Each company can download and configure RAST to assess for and ensure compliance with their company‐specific risk matrix: their risk tolerance criteria. RAST can be applied to existing and proposed installations. In addition, RAST is versatile: helping reduce process safety risk when used during Management of Change (MOC) reviews for comparing different inherently safer design options. As is detailed in the paper, RAST follows the basic steps in performing a Hazard Identification and Risk Analysis (HIRA) study. The tool allows Process Hazards Analysis (PHA) Teams to validate process‐specific scenarios, and provides guidance on potential causes of incident scenarios. The scenario‐specific risks—a function of the consequence and the frequency—can be determined in RAST through a quantified consequence impact through leak rate and dispersion modeling and estimated scenario frequencies through equipment integrity and reliability information.