The Preventive Maintenance Program (PMP) is a structured maintenance approach designed to optimize the performance and longevity of pharmaceutical equipment. By implementing PMP within EPCs, companies can proactively manage maintenance schedules, minimize equipment failures, and ensure compliance with industry regulations.
Schedule maintenance tasks periodically based on equipment type and usage.
Send notifications to responsible personnel in advance.
Review the schedule by the Group Leader/Head of Department.
Assign tasks to the related service engineer.
Conduct preliminary inspections to assess equipment condition.
Identify potential issues before they escalate.
Perform cleaning, lubrication, calibration, and functional testing.
Complete necessary adjustments and minor repairs.
Review and approve results by the department head.
Create change control or deviation if applicable for major adjustments.
Conduct final verification to ensure maintenance effectiveness.
Document user acceptance.
Take appropriate actions based on inspection results:
Keep equipment in use.
Schedule for additional maintenance.
Identify for replacement if necessary.
Lack of automated reminders can lead to missed maintenance.
Manual tracking increases administrative workload.
Inconsistent maintenance can result in unexpected failures.
Automated alerts and notifications for scheduled maintenance ensure timely execution.
Categorization of maintenance activities improves priority management.
Standardized workflows streamline maintenance tracking.
Automatic CAPA generation ensures proactive issue resolution.
Equipment logs are updated automatically, improving compliance.
Preventive maintenance calendar helps in proactive maintenance planning.
Regular training and awareness improve staff competency in maintenance procedures.
Reduction in unexpected equipment failures through proactive maintenance.Minimized human errors with automation.
Improved compliance with regulatory requirements.
Enhanced operational efficiency with structured workflows.
Better decision-making with real-time maintenance data analytics.
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