This systematic review investigates how smart maintenance, aligned with Industry 4.0 principles, can improve performance and compliance in medical-imaging manufacturing by integrating sensing, connectivity, information management, analytics, and execution into a single, governed system. Using a PRISMA 2020 protocol, we searched Scopus, Web of Science, IEEE Xplore, ACM Digital Library, and PubMed for English-language studies published from 2011 to 2020. Eligibility focused on data-driven maintenance practices in discrete and imaging-proximate manufacturing with reportable operational outcomes. Two independent reviewers screened records, extracted data on technologies, integration touchpoints, governance controls, and key performance indicators, and appraised methodological quality. In total, 105 peer-reviewed studies were synthesized. Findings show consistent improvements when analytics are embedded in routine workflows: median gains included overall equipment effectiveness +6.4 percentage points, mean time to repair −19 percent, mean time between failures +28 percent, and scrap or rework −14 percent. Effects were larger and more durable where bi-directional integration with CMMS and MES automated work orders and close-out, where prognostics with remaining useful life estimates informed schedules, and where prescriptive planning aligned interventions with calibration windows. Compliance practices change control, audit trails, authenticated telemetry, and documented threshold or model validation reduced nuisance alerts and helped sustain benefits beyond 12 months. Imaging-specific high-leverage indicators included vacuum integrity and particle counts that directly link equipment health to calibration yield. Overall, the evidence supports a compliance-aware blueprint that treats smart maintenance as a configured enterprise capability rather than a point solution, delivering measurable and auditable performance improvements across regulated imaging manufacturing.
Md Shamim (Sat,) studied this question.