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Published on: April 19, 2024
Proactive Replacement in Aseptic Manufacturing: A Health Index + Weibull/Kaplan--Meier Framework
SaiVijay Thattukolla1, SaiVinay Thattukolla2
1Independent Researcher saivijay.t1998@gmail.com.
Abstract:
Aseptic manufacturing depends on reliable equipment to maintain throughput and protect patients. This study presents a practical, reproducible maintenance engineering method for proactively replacing aging parts before failure; regulatory references are included only as bounded implementation context for execution inside governed (site validated) systems. This study presents a practical, reproducible method for proactively replacing aging parts before failure. The method combines a simple weighted Health Index (HI) that summarizes condition signals such as vibration, temperature, flow, pressure decay, and motor torque with established survival methods (Weibull and Kaplan-Meier) to estimate remaining useful life (RUL). These estimates are converted into clear Green-Yellow-Red maintenance actions and illustrated with a conceptual SAP Plant Maintenance execution workflow for work orders, spare reservation, and traceable recordkeeping under site governance. The workflow is demonstrated on a vial washer, an upstream step that influences vial cleanliness and particulate control prior to depyrogenation, focusing on components including conveyors, pumps, bearings, seals, spray nozzles, and heaters. Using a simulation dataset to illustrate the full end-to-end analytics and decision workflow, Weibull fits with shape factor β in the range of about 1.8 to 2 captured wears out behavior, and Kaplan-Meier pump survival at 24 months was 0.58 (95% CI 0.50 to 0.66). Applying HI together with RUL shifted interventions from unplanned breakdowns to planned stops. Relative to a reactive baseline under the stated assumptions, the scenario results showed 62.5% lower downtime, 84% lower combined maintenance and rejection costs, and 50% fewer batch rejects, with robustness demonstrated through sensitivity tests and 1000 Monte Carlo runs. Overall, the contribution is a reproducible maintenance engineering workflow (HI + survival-based RUL + decision matrix) with a conceptual Computerized Maintenance Management Systems (CMMS)/SAP Plant Maintenance execution mapping for traceable work order initiation when implemented under site governance. The approach is adaptable to existing supervisory control and data acquisition (SCADA) and SAP Plant Maintenance infrastructures following validation within the site quality system, with early benefit expected when prioritizing product quality critical components such as seals and spray nozzles.
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