Assessment of catastrophe risk and potential losses in industry

Prioritizing the indicators influencing permit to work system efficiency based on an analytic network process

A permit to work (PTW) system is a formal procedure designed to control non-routine and hazardous works. However, this system by itself does not prevent incidents, and various factors contribute to its efficiency. This study aims to prioritize the indicators influencing system efficiency. To do this, indicators of the system were identified and scored by 15 safety experts. Next, priority weights of the indicators were analyzed by an analytic network process and Super Decisions version windows 2.10. Accordingly, the nine main indicators and 43 sub-indicators influencing the PTW system were ranked. The main indicators from high to low were preventive actions, training, safe procedures, emergency system, control and corrective measures, coordination, monitoring, details of the permit form and documentation, respectively. The present work helps identify the involved indicators in PTW system efficiency. Thereby, the experts can prioritize and perform measures to prevent failures in the system and decrease accidents.

A near-miss management system architecture for the forensic investigation of software failures

Digital forensics has been proposed as a methodology for doing root-cause analysis of major software failures for quite a while. Despite this, similar software failures still occur repeatedly. A reason for this is the difficulty of obtaining detailed evidence of software failures. Acquiring such evidence can be challenging, as the relevant data may be lost or corrupt following a software system's crash. This paper proposes the use of near-miss analysis to improve on the collection of evidence for software failures. Near-miss analysis is an incident investigation technique that detects and subsequently analyses indicators of failures. The results of a near-miss analysis investigation are then used to detect an upcoming failure before the failure unfolds. The detection of these indicators - known as near misses - therefore provides an opportunity to proactively collect relevant data that can be used as digital evidence, pertaining to software failures. A Near Miss Management System (NMS) architecture for the forensic investigation of software failures is proposed. The viability of the proposed architecture is demonstrated through a prototype.