The Use and Abuse of OEE

Overall Equipment Effectiveness (OEE )
is fast becoming a widely used measure for manufacturing industry, but
it is also one of the more misunderstood and misused measures and
causing much confusion.

What is OEE for?

The simple answer is “Improvement”. OEE
is an improvement measure and is used as part of the improvement cycle.
Unfortunately, much is made of the 85% ‘World Class Standard’ an
arbitrary target found in the original TPM literature. Not only is this target out of date (Nissan in Sunderland are running welding lines at 92-93% OEE ) it gives the wrong message. A customer has no interest in your OEE
– that is an internal measure which relates to your efficiency and
costs. The customer is far more interested in a measure such as On Time
In Full (OTIF) ie did I get my order? Running a manufacturing business
on an arbitrary efficiency measure rather than a customer satisfaction
measure is a recipe for disaster. The best use of an OEE
target such as 85% is to recognise that if you are reaching that level
and the customer is still not getting his orders on time, then you may
have a capacity constraint.

OEE does not tell us if we have a problem, the customer does. What OEE
does do is help us analyse the problem and make improvements. This is
why Toyota use it as a spot measure on a particular machine where there
is a capacity or quality problem. Calculating the OEE
of anything other than a discrete machine or automated line is
pointless; we have far better measures of the efficiency of a factory
or department as a whole.

OEE
developed out of the need for improvement groups to have a way of
measuring and analysing equipment problems as part of their Define,
Measure, Analyse, Improve, Control cycle. OEE
defines the expected performance of a machine, measures it and provides
a loss structure for analysis, which leads to improvement. It can then
be used as a tracking measure to see if improvement is being sustained
ie if control is sufficient.

What does OEE measure?

At its simplist, OEE measures the Availability, Performance and Output Quality of a machine.

A
machine is available if it is ready to produce, as opposed to being
broken down or having some changes or adjustments made. The definition
of availability allows for planned maintenance, when the machine is not
meant to be available to production, but makes no allowance for
changeovers etc. No machine with changeovers can ever be 100%
available. The reason for taking such a hard line is that changeovers
are a major loss to both efficiency and flexibility, so the OEE analysis focuses attention on it by making no changeover allowances.

Performance
efficiency measures the output during available time compared to a
standard. Here there can be debate about what the standard output
should be. A good rule of thumb is to make the performance calculation
based on best known performance. This may be greater or less than
design speed. My argument is that if a machine has never reached its
design performance it is not helpful to measure against that. On the
other hand, if it has consistently out performed the design spec you
can have (and I have seen) performance figures of 140%, which can hide
poor availability. This is always remembering that one purpose of OEE is to help tell you if you have the capacity to meet customer demand.

Output
Quality is a First Time Through measure – what percentage of the output
was right first time, without any rework. FTT measures are always the
best quality measures. The issue in OEE
is that sometimes the quality feedback is not immediate. In FMCG
businesses, a customer complaint can be received three months or more
after production. In these cases it is best not to include quality in
the OEE
calculation and use a more customer focused measure for quality –
number of complaints etc. If there is no way we can use the Quality
component of OEE in a real time improvement cycle, then it is pointless to measure it.

Loss Analysis

The next level of analysis are the seven (or six or eight or sixteen) losses. Within OEE we usually talk about seven losses, although TPM loss structures have been known to define 23 losses in all.

Availability
losses are primarily Breakdowns and Changeovers. Changeovers can be
separated into Tool changes, Material changes and Reduced Yield at
start up, but fundamentally these are the same issue. Further analysis
reveals breakdowns to have two fundamental types, those due to
deterioration because of inadequate maintenance and those due to
inherent machine characteristics.

This gives us three basic
responses to availability issues – improve changeovers through SMED,
improve basic maintenance and improve machine characteristics.
Depending on the Pareto analysis of losses we may need to act on one,
two or all three of these.

Performance losses are usually
separated into speed loss and minor stops – is the machine running
slow, or is it stop-starting? The definition of minor stop is also open
to debate – originally it was less than ten minutes, then five minutes,
then three minutes. The pragmatic approach is to say that if you can
measure the amount of time lost for a stop it is a breakdown, not a
minor stop. If you can only record the quantity of stops, then they are
minor stops.

There is some practical use for the speed/minor
stop distinction – if a machine is running slow we can always speed it
up, whereas if it is jamming we need to look at the physical mechanism
and try to remove the cause of the jams (my favourite example is where
we found the root cause was when metal washers were being loaded into a
hopper with a metal shovel, which damaged some, which then jammed the
feed – the solution was a plastic shovel!).

We can however also
make a useful distinction between performance losses due to
deterioration or contamination and those caused by inherent machine
characteristics. As with breakdowns this gives us two improvement
approaches – better maintenance or equipment re-design.

Improvement

The
only reason to measure and analyse anything is to improve it. If we are
not going to use the whole improvement cycle there is no point in
measuring OEE. It tells us nothing we do not already know. At a gross level all OEE
tells you is how much you made compared to what you wanted to make, and
any schedule adherence measure would tell you that already. Averaging OEE’s over whole plants or time periods just hides issues – OEE is a specific measure for use in specific improvement projects.

The biggest misuse of OEE is to use it to compare different processes, plants or machines. OEE
is not a useful executive KPI. It is not even a very useful operational
measure. It is an improvement measure, for people who want to improve
their equipment performance.

How to massage your OEE
1) When the machine breaks down, log it to planned maintenance
2) Do changeovers during planned maintenance or at weekends if not 24/7
3) Use an easy performance standard
4) Measure the best machine and quote that figure
5) Set arbitrary targets and achieve them through the above

Using the above strategy you should be able to report decent OEE’s and even make some money if pay is OEE performance related. What this will not do however is improve your ability to meet customer demand.

How to improve performance

1) Measure against customer demand (OTIF or similar)
2) Measure OEE on constraints or problem equipment
3) Set realistic performance standards
4) Analyse losses to identify issues for improvement
5) Use the whole improvement cycle