Overall Equipment Effectiveness (OEE) is a well-known KPI in many industries for nearly forty years in western countries. It reflects overall performance in a single number, and is built upon or integrating three other metrics: Availability, Performance and Quality.
- Availability is the readiness of the machine / equipment to operate when required
- Performance is the actual run rate compared to the nominal run rate
- Quality is the number of good parts or quantity right first time compared to the global quantity (good and no good)
Everyone of these metrics is expressed in %, OEE = availability x performance x quality
As OEE is multiplying fractions, the result cannot be greater than the smallest value of Availability, Performance or Quality. That is why OEE is a severe KPI: if one of the intermediate KPI decreases, the OEE decreases faster.
If someone is in charge of improving OEE, he or she will “speak” a Goal Tree, and it goes like this: in order to achieve the highest value of OEE, we must have:
- the machine / equipment steadily ready to operate
- running continuously at nominal speed
- producing only good parts
Now with this said, what to do next? Where are the leverage points?
OEE is great to give a snapshot of performance taking into account the three high-level must haves, but when it comes to action OEE must be broken down to find where and what to act on.
Critical Success Factors are very useful because they provide top management the minimal but sufficient dashboard to monitor progress towards the Goal.
These Critical Success Factors are dependent on underlying Necessary Conditions.
Availability for example depends on machine’s technical condition as well as on setup and material availability. It depends also on availability of trained and entitled workforce, work orders and possibly other documents.
Performance will probably depend on the machine’s condition, itself depending on the maintenance policy, maintenance frequency, and so on. Performance is also depend on the proper use of the machine by workers, the type and quality of raw material, the type and condition of its tools.
The breakdown goes on this way, from each Critical Success Factor down to the least Necessary Condition, building the whole Goal Tree. In order to list all Necessary Conditions, the same phrase applies: “In order to achieve… We must…”
The list may go on, both horizontally and vertically, according to the business.
The more regulatory constrained the business, the more likely to have a horizontally-wide Tree, as those regulatory constraints will add many mandatory Necessary Conditions.
What I really like with Goal Trees is the provided guidance by the necessity-based logic, insuring a complete and robust Tree is built. On top of it, it helps discriminating the must-haves from nice-to-haves.
Therefore it’s easy to respond logically to the claim “the machine is too old to achieve good performance, get us a new one!”. When considering what can be done to improve OEE, the age of the machine does not appear as being the biggest influencer.
In fact, many examples show that properly tended old machines can still be performant assets.