Advanced Analysis and Redesign of Industrial Alarm Systems

  • Author / Creator
    Kondaveeti, Sandeep Reddy
  • In the process industry, the alarm system acts as a layer of protection between the Basic Process Control System (BPCS) and the Safety Instrumented System (SIS). The BPCS is designed for automatic regulation of day to day process operation and SIS comes into picture when emergency shutdown is required. There are specific standards worldwide that define how BPCS and SIS system are to be designed and expected to work. However, not many well defined standards are available for design and management of industrial alarm systemsmainly due to the heavy involvement of human factors. Alarm management has gained complexity mainly due to increasing size of process plants and also due to the Distributed Control System (DCS) that presents little motivation for limiting the number of variables on which alarms can be configured. Alarm management lifecycle for maintaining an efficient alarm system as suggested by the International Society of Automation standards (ISA SP18.02) is discussed in this work with emphasis on monitoring and assessment and design stages. In this work, novel tools for assessment of alarm system based on routinely collected alarm event data are proposed and demonstrated. The primary focus of these tools is to identify nuisance alarms such as chattering and redundant alarms. Alarm event data is represented mathematically and indices are proposed to calculate the extent of similarity between two alarms and also to estimate the extent of chattering in an alarm. Two of the most commonly used techniques for reducing alarm chatter, delay timers and latches are discussed in detail. Effect of varying the size of on-delay, off-delay timers and latches on the accuracy of detection is discussed in the Receiver Operating Characteristic (ROC) framework from a theoretical view point by modeling them using Markov chains. Use of Return to Normal (RTN) information in addition to alarm events information in designing delay timers is also discussed. Finally, advantages of multivariate techniques such as Principal Components Analysis (PCA) based T2 and Q statistic as opposed to univariate monitoring are discussed in the same framework using simulation examples and an industrial case study.

  • Subjects / Keywords
  • Graduation date
  • Type of Item
  • Degree
    Doctor of Philosophy
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
  • Institution
    University of Alberta
  • Degree level
  • Department
    • Department of Chemical and Materials Engineering
  • Specialization
    • Process Control
  • Supervisor / co-supervisor and their department(s)
    • Shah, Sirish (Department of Chemical and Materials Engineering)
  • Examining committee members and their departments
    • Prasad, Vinay (Department of Chemical and Materials Engineering)
    • Soroush, Masoud (Department of Chemical & Biological Engineering, Drexel University)
    • Chen, Tongwen (Department of Electrical & Computer Engineering)
    • Shah, Sirish (Department of Chemical and Materials Engineering)
    • Huang, Biao (Department of Chemical and Materials Engineering)