Operational Data Framework for Safety Instrumented Systems : A Case Study in Functional Safety and Reliability
Nyman, Joel (2024-02-14)
Nyman, Joel
14.02.2024
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe202402157437
https://urn.fi/URN:NBN:fi-fe202402157437
Tiivistelmä
In various industries, companies are adopting functional safety measures to address safety concerns, adhere to standards, and manage complex systems. This research is focused on ensuring the reliable operation of Safety Instrumented Systems (SISs) by emphasizing the reliability data. The study examines methodologies for collecting data, classifying failures, mitigating risks, and complying with international safety standards. Through a case study in the energy and marine power industry, a theoretical framework is developed to utilize operational data for assessing SIS performance in the form of a new Engine Safety System (ESS). By complying with IEC standards 61508 and 61511 and incorporating the framework into the ESS's Functional Safety Management Plan, the research addresses key challenges such as data collection, failure analysis, and performance verification. The primary research questions involve determining the type of data to be collected and establishing guidelines for analysing and evaluating that data. A mixed method approach is chosen, with a greater emphasis on qualitative aspects due to the nature of interpreting standards and establishing procedures.
The developed framework is presented using tables that outline the required data inputs for reporting actual demands, spurious trips, failures of other barriers, and SIS element failures. Failure report templates are provided, emphasizing the importance of identifying root causes and categorizing failures into Safe or Dangerous failures, as well as Undetected or Detected. The reliability assessment involves comparing actual performance data against the criteria defined in the Safety Integrity Requirements that have been established for the SIS, based on the outcome of the risk assessment. Different risk assessment techniques, such as Layer of Protection Analysis, Fault tree analysis, and risk matrices, are presented in this context, while key performance indicators like demand rates and failure rates are explored to highlight their role in verifying SIS performance.
The established framework, designed for the ESS to execute safety functions at Safety Integrity Level 2, is versatile and can serve as a robust foundation for the development of future Functional Safety projects within the organisation and can be applied to other SISs with different Safety Integrity level targets. The study concludes by addressing challenges associated with reliability and various data sources, such as human error and lack of functional safety training, emphasizing the significance of comprehending functional safety when operating with data of SISs.
The developed framework is presented using tables that outline the required data inputs for reporting actual demands, spurious trips, failures of other barriers, and SIS element failures. Failure report templates are provided, emphasizing the importance of identifying root causes and categorizing failures into Safe or Dangerous failures, as well as Undetected or Detected. The reliability assessment involves comparing actual performance data against the criteria defined in the Safety Integrity Requirements that have been established for the SIS, based on the outcome of the risk assessment. Different risk assessment techniques, such as Layer of Protection Analysis, Fault tree analysis, and risk matrices, are presented in this context, while key performance indicators like demand rates and failure rates are explored to highlight their role in verifying SIS performance.
The established framework, designed for the ESS to execute safety functions at Safety Integrity Level 2, is versatile and can serve as a robust foundation for the development of future Functional Safety projects within the organisation and can be applied to other SISs with different Safety Integrity level targets. The study concludes by addressing challenges associated with reliability and various data sources, such as human error and lack of functional safety training, emphasizing the significance of comprehending functional safety when operating with data of SISs.