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Fuzzy-Based Failure Modes and Effects Analysis (FMEA) for Ring-Gantry Linac IGRT

J Chang*, S Jang , R Lalonde , D Heron , M Huq , UPMC Hillman Cancer Center and University of Pittsburgh School of Medicine, Pittsburgh, PA

Presentations

(Monday, 7/15/2019) 7:30 AM - 9:30 AM

Room: Stars at Night Ballroom 1

Purpose: Halcyon is a new ring-gantry linac and has unique challenges in handling IGRT compared to conventional linacs. In this study, we introduced fuzzy logic-based FMEA to provide better understanding of failure modes (FM) so that it can be used to establish a comprehensive quality management program for Halcyon IGRT.

Methods: The process map was generated and potential FMs and corresponding potential causes of failure and effects were identified for Halcyon IGRT. Experienced clinical evaluators used the linguistic variables (very low, low, medium, high and very high) to estimate the occurrence (O), severity (S) and detectability (D). The five levels of triangular membership functions and pairwise matrices produced fuzzy rules, which are used to determine the fuzzy risk priority number (RPN). The centroid defuzzification method is used to find the crisp value of output from the fuzzy O, S, and D. Based on the final ranking, risk mitigation strategies for each FM were made.

Results: A total of major five potential FMs and fifteen potential causes of failure and effects were identified from “load plan� to “beam delivery�. Normalized fuzzy RPN values for the FMs ranged from 0.158 to 0.242 having ranges of 0.054-0.403 for O, 0.049-0.491 for S and 0.069-0.37 for D. The highest ranked FM for the Halcyon IGRT was “Setup and immobilization� both due to its intrinsic importance and its high influence on other FMs. Corresponding mitigation plans included training on smooth operation of the couch, setup information in the in-room monitor, and regular inspection of immobilization devices.

Conclusion: The fuzzy FMEA model exhibits desirable properties that help overcome the drawbacks of the traditional FMEA and RPN, especially when dealing with a new type of machine and FMs are relative to each other. The results have been shared with team members, and mitigation plans are being implemented.

Keywords

Fuzzy Logic, Quality Control, Image-guided Therapy

Taxonomy

IM/TH- Formal quality management tools: Failure modes and effects analysis

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