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Preventive Maintenance

Introduction: Preventive Maintenance

Preventive Maintenance is planned work that keeps equipment in good condition. The aim is to prevent failures before they happen. It reduces unplanned downtime, stabilises output, and extends asset life. It is a core practice in Lean and Total Productive Maintenance.

Background

Traditional maintenance was often reactive. Teams fixed machines only after breakdowns. This caused lost production and variable quality. Preventive Maintenance grew as factories pursued reliability and flow. By servicing assets on a schedule and by condition, teams improve availability, speed, and quality at the same time.

Key Elements/Features

  • Asset register. A complete list of assets with criticality, history, and parts.
  • Maintenance plan. Calendar based tasks and condition based tasks for each asset.
  • Standards. Clear instructions for inspection, cleaning, lubrication, and minor fixes.
  • Spare parts. Right parts in the right place with minimum and maximum levels.
  • Condition monitoring. Simple checks such as vibration, temperature, and noise.
  • Work management. Planning, scheduling, permits, and close out with feedback.
  • Metrics. Availability, Mean Time Between Failures, Mean Time To Repair, and maintenance cost.
  • Roles. Operators handle basic care. Technicians handle complex work. Leaders remove barriers.

Applications/Examples

  • Daily operator care. Clean, Inspect, and Lubricate at shift start.
  • Weekly checks. Belts, chains, fasteners, guards, and sensors.
  • Monthly tasks. Alignment, filters, lubrication change, and safety systems.
  • Condition triggers. Replace a bearing when vibration exceeds the set limit.
  • Seasonal tasks. HVAC service before peak load.

Relevance/Impact

Preventive Maintenance improves reliability and safety. It reduces total cost by cutting failures and wasted time. It supports stable flow, higher OEE, and better quality. Start with critical assets. Define simple standards. Build a living plan that uses history and condition data. Link findings to root cause fixes and design changes.

See also

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