Model-Based Safety Assessment of Industrial Automation Systems using IEC 61499
type: CreativeWork
description: Industrial automation systems are complex control systems that perform control and automation of hazardous plants. Safety of such systems is of paramount importance and may even be mandated by law. Safety-related systems may be required to demonstrate conformance to an applicable functional safety standards to assure safety and demonstrate the that these systems mitigate the risk to human lives, as much as reasonably possible. IEC 61508 is a standard of functional safety for generic electric, electronic, and programmable electronic (E/E/PE) systems and is used as the principal guide in this thesis. IEC 61508 adopts a two-pronged approach for addressing random failures in the hardware and systematic errors in the software. Random failures are addressed using quantitative techniques for reliability analysis e.g., reliability block diagrams and Markov analysis, and by computing the safe failure fraction to establish a confidence level. Systematic errors, on the other hand, are avoided by following quality assurance recommendations and qualitative validation techniques. However, this segregated application of quantitative and qualitative approaches is inadequate for addressing complexities introduced by software-intensive control systems. Furthermore, the manual application of traditional safety analysis techniques is tedious, error-prone, and largely dependent on practitioners’ skills. In order to ameliorate these problems, a model-driven approach towards safety analysis named, model-based safety assessment (MBSA) was proposed, which has gained significant interest in academia and industry in the recent years. MBSA approaches use system models for the purpose of safety analysis such as extracting fault trees, performing quantitative analysis, or discovering a critical sequence of errors that may cause system failures. MBSA can be performed on either by using dedicated safety models or by using system development models. The latter approach allows seamless integration w…
abstract: Industrial automation systems are complex control systems that perform control and automation of hazardous plants. Safety of such systems is of paramount importance and may even be mandated by law. Safety-related systems may be required to demonstrate conformance to an applicable functional safety standards to assure safety and demonstrate the that these systems mitigate the risk to human lives, as much as reasonably possible. IEC 61508 is a standard of functional safety for generic electric, electronic, and programmable electronic (E/E/PE) systems and is used as the principal guide in this thesis. IEC 61508 adopts a two-pronged approach for addressing random failures in the hardware and systematic errors in the software. Random failures are addressed using quantitative techniques for reliability analysis e.g., reliability block diagrams and Markov analysis, and by computing the safe failure fraction to establish a confidence level. Systematic errors, on the other hand, are avoided by following quality assurance recommendations and qualitative validation techniques. However, this segregated application of quantitative and qualitative approaches is inadequate for addressing complexities introduced by software-intensive control systems. Furthermore, the manual application of traditional safety analysis techniques is tedious, error-prone, and largely dependent on practitioners’ skills. In order to ameliorate these problems, a model-driven approach towards safety analysis named, model-based safety assessment (MBSA) was proposed, which has gained significant interest in academia and industry in the recent years. MBSA approaches use system models for the purpose of safety analysis such as extracting fault trees, performing quantitative analysis, or discovering a critical sequence of errors that may cause system failures. MBSA can be performed on either by using dedicated safety models or by using system development models. The latter approach allows seamless integration w…
author: Bhatti, Zeeshan
license: https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm
date published: 2017
date modified: 2026-07-24T01:07:07Z
provider: University of Auckland
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: ResearchSpace@Auckland

PropertyValue
property ID: Handle
value: https://hdl.handle.net/2292/31831