<p> Critical infrastructure (CI) risk management frameworks require identification of single point of failure risks but existing reliability assessment methods are not practical for identifying single points of failure in CI systems. The purpose of this study was development and assessment of a system reliability assessment tool specific to the task of identifying single points of failure in CI systems. Using a series of action research nested cycles the author developed, applied, and improved a single point of failure analysis (SPFA) tool consisting of a six step method and novel single point of failure analysis algorithm which was utilized in analyzing several CI systems at a participating data center organization for single points of failure. The author explored which components of existing reliability analysis methods can be used for SPFA, how SPFA aligns with CI change and risk management, and the benefits and drawbacks of using the six step method to perform SPFA. System decomposition, network tree, stated assumptions, and visual aids were utilized in the six step method to perform SPFA. Utilizing the method the author was able to provide the participating organization with knowledge of single point of failure risks in 2N and N+X redundant systems for use in risk and change management. The author and two other individuals independently performed SPFA on a system and consistently identified two components as single points of failure. The method was beneficial in that analysts were able to analyze different types of systems of varying familiarity and consider common cause failure and system interdependencies as single points of failure. Drawbacks of the method are reliance on the ability of the analyst and assumptions stated by the analyst. The author recommends CI organizations utilize the method for identification of single points of failure in risk management and calls future researchers to further investigate the method quantitatively.</p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10975757 |
| Date | 29 November 2018 |
| Creators | Moore, Michael Ronald |
| Publisher | Northcentral University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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