Tracking allows you to:
✔ Identify recurring failures
✔ Predict component life
✔ Plan spare inventory
✔ Reduce emergency downtime
✔ Monitor cost trends
✔ Improve machine resale value
Without data, every failure feels “random.”
At minimum, record:
Date
Machine ID
Component serviced
Type of service (inspection / repair / replacement)
Reason for service
Parts replaced
Downtime duration
Technician name
Observations
Optional but powerful:
Scrap percentage at time of service
Motor current reading
Hydraulic pressure reading
Bearing temperature
The more consistent the data, the more valuable it becomes.
Organize logs by system:
Forming section
Bearings
Roll tooling
Entry guides
Shear system
Punch system
Hydraulic system
Electrical/PLC
Motors
Sensors
Stacker
This allows trend analysis by system type.
Tag each entry as:
PM (Preventive Maintenance)
CM (Corrective Maintenance)
EM (Emergency Repair)
Goal for high-performing facilities:
✔ >70% preventive
✔ <20% corrective
✔ <10% emergency
If emergency repairs exceed 20%, the PM program is weak.
Maintenance data becomes powerful when linked to:
Production hours
Coil tonnage processed
Linear meters produced
Punch cycle count
Shear cycle count
Example:
If bearings fail every 1.2 million meters — that becomes predictable.
Usage-based tracking is superior to calendar-only tracking.
For critical components, track:
Installation date
Production meters since install
Failure date
Failure mode
Key components to track:
✔ Bearings
✔ Shear blades
✔ Punch tooling
✔ Hydraulic filters
✔ Hydraulic oil
✔ Motors
✔ Encoders
This creates predictive replacement scheduling.
Best options:
Spreadsheet system (basic but effective)
Shared cloud document
Maintenance software (CMMS)
ERP-integrated system
Minimum requirement:
Data must be searchable and sortable.
Paper logs are better than nothing — but hard to analyze.
Monthly review should show:
Downtime hours
Scrap rate
Most frequent failure types
Cost per machine
Parts consumption trend
Management should review maintenance data regularly.
Each inspection should use a consistent checklist.
Example:
Daily checklist
Weekly checklist
Monthly mechanical checklist
Quarterly structural audit
Checklists ensure consistency between technicians.
Define:
Who logs data
Who reviews logs
Who approves corrective actions
Who updates spare inventory
If logging responsibility is unclear, data becomes incomplete.
Maintain digital copies of:
PLC backups
Drive parameters
Hydraulic schematics
Wiring diagrams
Service manuals
FAT reports
Calibration reports
Maintenance history should include documentation changes.
Every quarter ask:
What failed repeatedly?
Which component causes most downtime?
Are we over-maintaining anything?
Can we extend any intervals?
Are scrap spikes linked to maintenance gaps?
Data review drives improvement.
❌ No structured logging
❌ Only recording major failures
❌ Not linking maintenance to production data
❌ No tracking of part life cycles
❌ No review process
❌ Not backing up PLC programs
Without review, logs become meaningless.
High-performing roll forming operations typically achieve:
✔ Predictable bearing replacement intervals
✔ Planned blade regrinds
✔ Minimal emergency downtime
✔ Spare parts stocked intelligently
✔ Scrap rate below 3%
Maintenance history supports reliability engineering.
To track machine maintenance history effectively:
✔ Log every service action
✔ Separate preventive and reactive work
✔ Link data to production usage
✔ Track component life cycles
✔ Use digital tracking when possible
✔ Review data quarterly
✔ Assign accountability
Maintenance tracking turns experience into measurable reliability.
Without tracking, you cannot improve.
Copyright 2026 © Machine Matcher.