In most manufacturing plants, machine failures rarely happen suddenly. They build up over time—through unnoticed contamination, improper lubrication, minor misalignments, and gradual wear. The challenge is not the lack of maintenance, but the delay in identifying early-stage abnormalities at the operator level.
Autonomous maintenance, one of the core pillars of TPM, addresses this gap by shifting basic maintenance ownership to machine operators. It is not just about cleaning or inspection—it is a structured capability-building process where operators learn to detect, prevent, and control equipment deterioration.
This article explains the autonomous maintenance steps in detail, along with how TPM autonomous maintenance implementation works in real plant environments.
What is autonomous maintenance in TPM, and how does it work at a system level
Autonomous maintenance (Jishu Hozen) is a structured methodology within TPM that enables operators to maintain their equipment through defined standards, inspection routines, and condition monitoring practices.
At a system level, it works across three layers:
- Basic condition control: cleaning, lubrication, tightening
- Condition monitoring: identifying early abnormalities through inspection
- Continuous improvement: eliminating root causes of forced deterioration
Instead of separating “operation” and “maintenance,” this approach creates a shared responsibility model where operators handle routine care, while maintenance teams focus on advanced diagnostics and reliability engineering.
Why autonomous maintenance is critical for modern manufacturing systems
High-speed production lines, automated equipment, and tight delivery timelines leave very little room for unexpected stoppages. Even small inefficiencies—like a 2% speed loss or minor vibration—can impact overall equipment effectiveness (OEE).
Autonomous maintenance reduces these losses by building a first-line defense at the operator level.
- Enables early detection of forced deterioration (dust, heat, friction, looseness)
- Reduces mean time to repair (MTTR) by identifying issues before failure
- Improves mean time between failures (MTBF) through preventive actions
- Supports stable OEE by minimizing minor stops and speed losses
- Creates a data-driven maintenance culture when integrated with CMMS
7 key steps of autonomous maintenance
Autonomous maintenance is not implemented as a one-time activity but as a phased capability-building process. Each step is designed to systematically move equipment from a deteriorated state to a controlled and stable condition. The focus gradually shifts from basic restoration to condition monitoring and finally to continuous improvement driven by operators. This structured progression ensures that both machine reliability and operator competence improve together. When executed correctly, these steps create a strong foundation for long-term TPM success.
1. Initial cleaning and forced deterioration exposure
This step goes beyond surface-level cleaning and focuses on restoring the equipment to its original condition. Operators interact closely with machine components, often dismantling accessible parts to remove accumulated dirt, grease, and contaminants. The objective is to expose hidden abnormalities that are usually masked during routine operation. It also helps in building operator familiarity with machine construction and weak points.
- Identification of forced deterioration, such as dust accumulation, oil leakage, and metal wear particles
- Detection of physical defects like loose bolts, cracks, misalignment, and damaged seals
- Use of tagging systems (red/white tags) to mark abnormalities for corrective action
- Establishment of baseline machine condition for future comparison
- Improved visibility of hard-to-detect areas such as internal panels and enclosed sections
2. Elimination of contamination sources and hard-to-access areas
After identifying issues, the next focus is on eliminating their root causes instead of repeatedly cleaning them. This step often requires small engineering modifications to the machine or the surrounding environment. The aim is to reduce contamination entry, simplify maintenance access, and minimize operator effort. It directly impacts the sustainability of autonomous maintenance practices.
- Sealing of leak points using gaskets, O-rings, or structural modifications
- Installation of protective covers and guards to prevent dust and coolant ingress
- Redesign of machine parts to improve accessibility for inspection and lubrication
- Reduction of cleaning frequency by eliminating recurring contamination sources
- Improvement in operator efficiency through better ergonomic access
3. Development of cleaning, lubrication, and tightening standards
Standardization transforms maintenance activities into structured and repeatable processes. Operators are provided with clearly defined guidelines that specify what needs to be done, how it should be done, and how frequently. This step ensures consistency across shifts and reduces dependency on individual experience. It also forms the backbone of the autonomous maintenance checklist.
- Creation of detailed cleaning standards with defined areas and methods
- Lubrication mapping, including the type of lubricant, quantity, and intervals
- Tightening standards with torque specifications for critical fasteners
- Development of visual SOPs and one-point lessons for easy reference
- Integration of standards into digital systems, like CMMS, for tracking
- Alignment of standards with OEM recommendations and plant conditions
4. General inspection training (component-level understanding)
At this stage, operators are trained to understand machine components and their functional behavior. The focus is on building technical knowledge so that operators can identify early warning signs of failure. Training includes both theoretical concepts and hands-on exposure to real equipment conditions. This step reduces the gap between operator and maintenance technician roles.
- Identification of abnormal vibration patterns in rotating components
- Recognition of overheating through touch, sensors, or visual indicators
- Understanding wear patterns in belts, gears, couplings, and chains
- Basic knowledge of electrical systems, such as wiring, connections, and insulation
- Awareness of pneumatic and hydraulic system behavior and leak detection
- Interpretation of machine sounds to identify internal issues
- Ability to differentiate between normal and abnormal operating conditions
5. Autonomous inspection (condition-based monitoring by operators)
Operators begin performing regular inspections independently using structured checklists and standards. This step shifts the approach from reactive observation to proactive monitoring. Operators are expected not only to identify issues but also to take immediate corrective actions within their scope. It significantly reduces unnoticed deterioration and improves response time.
- Execution of daily and periodic inspections using predefined checklists
- Monitoring of parameters such as noise, vibration, temperature, and leakage
- Recording of abnormalities in logs or digital systems for traceability
- Performing minor corrective actions like tightening, lubrication, and cleaning
- Escalation of complex issues with proper documentation and tagging
- Continuous comparison with baseline conditions established earlier
6. Standardization and visual control systems
To sustain autonomous maintenance, processes must be simplified and made visually intuitive. Visual controls reduce dependency on memory and ensure consistent execution across operators and shifts. This step focuses on creating a standardized work environment where deviations can be easily identified. It also improves training efficiency for new operators.
- Color coding of lubrication points, inspection zones, and safety areas
- Visual indicators for acceptable vs abnormal conditions (limits, gauges, markings)
- Display of standard operating procedures near equipment for quick reference
- Use of labels and tags for easy identification of components and checkpoints
- Implementation of one-point lessons (OPLs) for focused operator training
- Reduction of human error through clear visual guidance systems
7. Continuous improvement and equipment ownership culture
The final step focuses on sustaining and improving the system through operator involvement. Operators actively participate in identifying improvement opportunities and reducing recurring issues. This step strengthens the connection between people and machines, leading to higher accountability. It also integrates autonomous maintenance with other TPM pillars for long-term impact.
- Root cause analysis (RCA) for repeated failures and abnormalities
- Implementation of small improvements (Kaizen) to reduce effort and failure points
- Collaboration between operators and maintenance teams for problem-solving
- Continuous refinement of standards based on real-time observations
- Use of performance data (OEE, MTBF, MTTR) to drive improvements
- Development of an operator ownership mindset towards equipment reliability
- Contribution to the overall TPM autonomous maintenance implementation strategy
How to implement autonomous maintenance in a plant
Implementing autonomous maintenance in a plant requires a structured rollout that combines operator training, process standardization, and system-driven monitoring. It should begin with a clear assessment of current equipment conditions and gradually move towards building operator ownership through defined steps and measurable outcomes. Instead of applying it across the entire plant at once, a phased approach ensures better control, learning, and scalability. Integration with digital tools further strengthens tracking, accountability, and long-term sustainability of TPM practices.
- Start with pilot equipment selected based on criticality, breakdown frequency, and overall impact on production output
- Conduct baseline audits to evaluate current machine condition, identify deterioration points, and map existing maintenance gaps
- Train operators through hands-on sessions that focus on real machine behavior, failure patterns, and inspection techniques
- Develop standardized autonomous maintenance checklists with clearly defined tasks, frequencies, and responsibility ownership
- Clearly define responsibility boundaries between operators and maintenance teams to avoid overlap and confusion in execution
- Implement visual controls and SOPs directly at the machine level to ensure consistent execution across all shifts
- Use CMMS to track inspections, record abnormalities, assign actions, and maintain a complete maintenance history centrally
- Monitor KPIs like OEE, MTBF, MTTR, and minor stoppage trends to measure effectiveness and identify improvement areas
- Expand implementation gradually across production lines only after stabilizing the pilot phase and achieving consistent results
Autonomous maintenance checklist
1. Basic cleaning (Daily)
[ ] Clean machine surfaces, panels, and the surrounding working area
[ ] Remove chips, scrap, and foreign particles from moving parts
[ ] Wipe sensors, limit switches, and inspection windows
[ ] Clean air vents, cooling fans, and filters
[ ] Remove grease, oil sludge, and dirt buildup near components
2. Lubrication (Daily / Weekly)
[ ] Check lubrication levels at all designated points
[ ] Apply lubricant as per the specified type and quantity
[ ] Inspect bearings, chains, and slides for dry running signs
[ ] Check lubrication lines and nipples for blockage or leakage
[ ] Ensure no excess lubrication causing contamination
3. Tightening and mechanical condition (Weekly)
[ ] Tighten bolts, nuts, and fasteners on critical components
[ ] Check belt, chain, and coupling tension and alignment
[ ] Inspect guards and covers for proper fitment
[ ] Identify looseness, vibration, or mechanical play
[ ] Verify alignment of rotating and moving parts
4. Inspection (Daily / Weekly)
[ ] Listen for abnormal noise during operation
[ ] Check for unusual vibration or excessive heat
[ ] Inspect for oil, air, or coolant leakage
[ ] Verify pressure, temperature, and gauge readings
[ ] Look for wear, cracks, or corrosion on components
5. Electrical and control system (Weekly)
[ ] Inspect cables, wiring, and electrical connections
[ ] Check for loose terminals or exposed wires
[ ] Verify sensors, switches, and indicator functionality
[ ] Inspect control panels for dust, moisture, or overheating
[ ] Test emergency stop and interlock systems
6. Safety checks (Daily)
[ ] Ensure all safety guards and interlocks are in place
[ ] Verify emergency stop buttons are working properly
[ ] Check for oil spills or hazards around the machine
[ ] Confirm safety signs and warning labels are visible
[ ] Ensure operators are using required PPE
7. Minor maintenance actions (As required)
[ ] Perform minor tightening, adjustments, and corrections
[ ] Replace small consumables (filters, seals, fasteners)
[ ] Clean or reset sensors and remove obstructions
[ ] Adjust alignment or positioning where needed
[ ] Tag and report major issues to the maintenance team
8. Documentation and reporting (Daily)
[ ] Record completed tasks in logbook or CMMS
[ ] Tag abnormalities using the standard tagging system
[ ] Report recurring issues to the supervisor or maintenance
[ ] Track pending and completed checklist items
[ ] Maintain machine condition history for reference
9. Periodic condition check (Monthly)
[ ] Perform detailed inspection of critical components
[ ] Check calibration of gauges and instruments
[ ] Review lubrication effectiveness and intervals
[ ] Analyze breakdown trends and recurring issues
[ ] Update checklist based on observations and improvements
Conclusion
Autonomous maintenance is not a one-time activity—it is a structured journey from basic cleaning to full equipment ownership. Each of the autonomous maintenance steps builds operator capability while improving machine reliability in parallel.
Plants that treat it as a checklist activity often fail. Those that implement it as a system—supported by training, standards, and digital tools—see long-term improvements in performance and cost control.
If you are planning to implement autonomous maintenance at scale, TeroTAM can help you manage checklists, track inspections, monitor KPIs, and streamline TPM activities through a centralized platform.
For more details, reach out at contact@terotam.com
