Aizon Launches Predictive Maintenance Solution for Pharmaceutical Manufacturing

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SAN FRANCISCO– Aizon announced today the launch of its new asset monitoring application for pharmaceutical manufacturers and biotech companies. Built on Aizon’s GxP compliant AI SaaS Platform, Aizon Asset Health provides intelligent historical maintenance analysis, proactively monitors the condition of critical assets in real time, identifies potential problems and provides actionable maintenance recommendations that keep equipment up and running optimally. This data-driven maintenance approach reduces maintenance costs, eliminates unplanned downtime and optimizes product yield—unlocking the full potential of Smart Pharma Manufacturing.

Keeping manufacturing assets in effective working order can be costly and wasteful. A schedule-based approach to maintenance often results in the unnecessary repair or replacement of equipment in acceptable working conditions or conversely results in catastrophic failure of equipment due to undiagnosed issues. This can cause production disruptions, lead to product rejection, impact time to market and compromise First Time Right, that is ensuring that any procedure is performed in the right manner the first time and every time. Using advanced analytics and multivariate analysis, together with artificial intelligence, the Aizon Asset Health application further optimizes the reduction in unplanned downtime through condition-based maintenance beyond today’s industry standard – ultimately reducing maintenance expenses while improving asset reliability and performance.

“Pharmaceutical manufacturers and biotech companies are under tremendous pressure to maximize the return on investment and to reduce unplanned downtime; however, traditional schedule-based maintenance approach tends to fall short in terms of gaining control of downtime and the high costs associated with replacing equipment in an effort to achieve better performance,” said John Vitalie, CEO, Aizon. “Our Asset Health application enables our customers to harness the power of their equipment and environmental data to slash maintenance costs, optimize equipment performance, enhance product output and improve product quality.”