Automated life cycle processing for complex medical imaging devices

• Published in: 2017 Annual Reliability and Maintainability Symposium (RAMS) pp. 1 - 6
• Main Authors: Fricks, Rafael B., Trivedi, Kishor S.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 2017
• Subjects: Biomedical imaging; Companies; Computed tomography; History; life data analysis; Maintenance engineering; mean cumulative function; non-parametric methods; R&M applications in health care; X-ray imaging
• DOI: 10.1109/RAM.2017.7889693

Medical imaging systems from major modalities such as Magnetic Resonance Imaging or X-Ray Computed Tomography are complex devices subject to various types of maintenance. Medical device companies that develop these systems often monitor and maintain systems sold throughout their potentially decades-long design lives, recording a variety of maintenance operations that occur in practice. In order to interpret such massive repair record volumes collected over hundreds of distinct product lines, we present a data processing method developed for compiling maintenance histories of MRI and CT scanners. We then use the outputs of this program to compute a common non-parametric estimate, the mean cumulative function. Results are presented from active in vivo imaging product lines with identifying information omitted. Finally, key insights from the produced MCFs preface a discussion on the methods as well as future directions.