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Pharma and healthcare industries operate in a highly regulated ecosystem where product quality and safety are of paramount importance.
Plants that are operational 24×7 can’t afford to have limited asset visibility, sudden machine failures, and unplanned downtimes. Poor machine health not only affects net productivity, it can also lead to hazardous leakages, and catastrophic accidents.
Unless a more pragmatic and analytical approach towards maintenance is adopted, pharma manufacturing plants can’t realistically retain a sustainable competitive advantage. With a Predictive Maintenance model, overall plant reliability objectives can be achieved.
Predictive Maintenance and Digital Reliability for Pharma and Healthcare Plants
Preventative maintenance models in Pharma and healthcare manufacturers can no longer enable plant reliability. A decided shift to predictive maintenance with AI-enabled monitoring and reliability solutions is necessary. A leading Pharma manufacturer saved 12 hours of production downtime with focused application of plant reliability solutions.
Achieve digital reliability with predictive analytics. Deploy responsive maintenance strategies with real-time insights on asset performance and machine health.
Optimize Machine Health and Performance
Monitor machine conditions in real time and diagnose potential equipment faults before they can halt production. Facilitate maintenance planning and machine upkeep with real-time data and solution-based insights.
Reduce Unplanned Production Downtime
Proactively resolve machine malfunctions and process inconsistencies to reduce unplanned production downtime. Organize informed and need based maintenance events to sustainably maintain plant productivity.
Enhance Safety and Efficiency
Increase visibility of mission critical equipment and deploy digital twin technology to enhance asset reliability. Achieve more from engaged assets while ensuring a safer and quality-centric production environment.
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