Predicting parts wear to reduce waste and downtime


Parts wear at different rates on production lines. As an additional complication, the measurements by which they wear (e.g. time, usage) vary as well. It’s a tricky problem to manage, but left untended, the issues can be considerable.


Our Consumer Product Goods customer was experiencing unplanned downtimes, too much waste, and quality issues, due to variation in parts wear.


Our 3-part solution not only addressed the issues with waste, quality and downtime; it provided additional benefits in traceability and work planning:

  1. Tracked parts usage on 3 separate parameters – see below.
  2. Maintained a real-time inventory of parts usage and lifespan since last restored, plus complete traceability on where used.
  3. Built the ability to automatically create work orders based upon operating conditions, to improve uptime reliability.

Usage: Number of cycles

  • Each Work Order was associated with the serial number for each part used (through analysis, we’d learned quality issues were starting at around 1.5 million cycles).
  • Each cycle counted.
  • Reporting created for each part: how many cycles; which components made up the part assembly and when; which work order was associated to any of those parts.

Usage: Runtime

Some parts, e.g. belts, were tracked by runtime, because analysis had revealed that breakage occurred at around 4500 hours. These parts were tracked on runtime, post-installation, but only while equipment was running.

Usage: Absolute time

Running or not, oil in a gearbox alters over time, causing premature wear of other equipment. Post-change oil use was calculated in real time to track effective life.


  • Step 1: Build inventory data – the list of parts and where they were installed
  • Step 2: Data acquisition and analysis, allowing the maintenance team to decide the limits of each of the three measurement types
    • Example: Deciding which part should be tracked by which model, and the maximum number of cuts / running time / absolute time


Significant benefits were quickly reached:

  • Number of unplanned downtimes due to part wear or breakdown dropped significantly,
  • Work planning was easier; the team had visibility through a specific report to the complete list of parts, based on the next time they needed to be rebuilt.
  • Inventory management improved because new or re-built parts were made available in time for next preventive replacement.
  • Part retirement became pro-active, as we knew some parts could only be rebuilt X number of times.
  • Rejects due to quality failure were reduced.
  • Quality failure due to parts wear was detected considerably sooner.
  • Traceability rose, as we knew which product was manufactured with which equipment.