Automated life cycle processing for complex medical imaging devices
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.
