OEE Analysis

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Last update: October 3rd, 2008
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Facing growing competition companies must improve their performances: productivity, reactivity, costs cutting, shortening delivery time and improve quality.

In this context, OEE sure is a very Key Performance Indicator (KPI), which analysis gives the relative value of performance (as a result indicator) and action plans for improvement.

A focused OEE improvement program allows productivity improvements, capacity improvement with postponement of news investments in addtional equipments or remplacement of machines judged outdated. These investments may even be canceled if OEE improvement covers the search for capacity.


Understanding OEE losses

OEE value in itself shows actual performance level, yet what improvement teams look for is to understand of what is made the complement to 100, the part of waste.

OEE is made out of three components: availability, performance and quality.

In order to understand the causes of underperformance and wastes, one hint is to check the part of quality issues and treat the related problems with a problem solving methodology.

Next step is to exploit available data about downtime and their causes. Experience shows that most often the wastes are related to:

  • organisation problems:
    • lack of parts or material
    • late or absent personnel
    • sub-optimal planing
    • lengthy changeovers
    • ...
  • stoppages (planned or not):
    • overhaul
    • supply
    • changeovers
    • checkups
  • breakdowns or burnouts
TRS

OEE Analysis

The purpose of the OEE data analysis is to screen out main causes of losses and drive actions toward their root causes in order to eliminate them and achieve higher OEE. A Pareto diagram is perfectly fitting such an analysis and will help define countermeasures.

Author, Chris HOHMANN, is managing partner in an international consultancy.

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If not using an automated data collecting system, accumulating downtimes may show an important share of "unknown causes", the single data being aggregated in this convenient category.

If unknown causes accumulate an important share, they may be:

  • speed variations, difficult to see through human observation,
  • non fitting data collecting system,
  • personnel's lack of dedication and rigor.


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