This article highlights both the pros and cons of implementing OEE in a manufacturing environment. I have tried to include both the positive and negative elements to give a balanced view, and have also included some of the best practices that I have seen over the last 29 years that I have been working in the industry. Although my background is as a software developer and in particular using the PlantRun and Prodigy software platforms, the concepts described here are universally applicable.

1. April 2020
Outline
Overall Equipment Effectiveness or OEE is a method of looking at a
manufacturing process to determine how well it is operating. It
combines three metrics to provide a single measure that encompasses
the utilisation of an asset, if it is being run at its optimum speed, and
what proportion of scrap to good products are being produced.
OEE (%) = Availability (%) x Performance (%) x Quality (%)
10000
Savings
Unless you have a site that is already extremely efficient, in virtually all
cases that I have come across it is possible to get a payback for a
system in just a few weeks. After that you are saving money and
improving your bottom line.
Generally there are also benefits realised that were not apparent
initially. For example, with one timber mill, it was presumed that the
operator on one of their stackers was stood waiting for about 1½ hours
in an 8 hour shift. After an automatic OEE system was installed it
became clear that it was actually 4½ hours. As a result their process
was adjusted to build up a buffer and the operator redeployed on
other tasks during their ‘newly available’ time.
When not to implement
Implementing an OEE system will not inherently make you more
efficient or save you money. The only way to make it work is if you
actively use the data it generates.
Ideally more than one member of staff should champion the process.
Otherwise if that person is busy or if they leave, you are left without
appropriate knowledge and the system is unlikely to be successful.
You also need buy-in from the top management all the way down to
the shop floor. Fundamentally you need to be committed to it, or you
will just be wasting your time and money.
Why OEE?
by Ashley Tizard
Summary
This article highlights both
the pros and cons of
implementing OEE in a
manufacturing
environment.
I have tried to include
both the positive and
negative elements to give
a balanced view, and have
also included some of the
best practices that I have
seen over the last 29
years that I have been
working in the industry.
Although my background
is as a software developer
and in particular using the
PlantRun and Prodigy
software platforms, the
concepts described here
are universally applicable.
OEE  Machine Downtime  Manufacturing Information Systems
The pros and cons of implementing an OEE system
April 2020
1

2. April 2020
OEE  Machine Downtime  Manufacturing Information Systems
2 Available or not…
The availability metric immediately brings up some interesting
differences in possible approach. From the production plan point of
view, operators are expected to be running their assets according to a
defined shift pattern with allowances for breaks, clean up times etc.
This gives an amount of available time for running on each asset. It
can, however, make it complicated when, for example, operators are
off sick, the production plan needs to change on the fly, or an
impromptu meeting is held. Ultimately this leads to an increased
administration requirement which, in my experience can result in the
system falling out of favour as the overhead is too onerous.
I think in most cases it is better to handle the planned not to run
periods by using simple concepts such as identifying when an operator
is not logged on to an asset. Then there is no additional administration
and logging on can be enforced through the use of machine interlocks.
What is the target speed?
Takt or cycle times for machines can be well defined but that is only
the start of the story. Production planning systems will calculate how
many products of a particular type can be manufactured in a given
amount of time. They take into account changeover and clean down
times, and include timings for bringing raw materials to an asset and
taking finished goods away. This gives most sites their performance
targets. However, I have seen many cases where the data in the
ERP/MES is based on historic hearsay and is not particularly accurate.
A little while ago, I was stood with a production manager at a site
looking at a machine with a speed measurement above it of about 200
m/hr. I questioned how they knew if it was running at the correct
speed and what the target speed was. The discussion progressed to
the fact that when the machine was installed the manufacturer said it
could run at 800 m/hr, as the machine was now quite old they had
recently said that they thought that it would probably be capable of
400 m/hr. “Ok” I said, “but why is it running at 200?”. “That’s a good
question” was the response…
The target speed for each product should be reviewed and if there is
uncertainty about them then data needs to be collected initially to
allow an accurate figure to be determined and then fixed.
Availability
is an indication of the
time that an asset is
running.
It is calculated as the
operating time as a
percentage of the planned
production time
(otherwise known as
available time).
Performance
is an indication of how
close the asset is running
to its target production
rate for the product being
made.
It is calculated as the
number of products
produced as a proportion
of the possible number of
products that could have
been made in the running
time.

3. April 2020
OEE  Machine Downtime  Manufacturing Information Systems
3 Quality products
OEE accounts for the quality metric with exactly the same weight as
availability and performance, however, in most instances the early wins
at a site do not initially come from targeting quality issues. That is not
to say that it should be ignored though. If you speed up production to
improve performance, you may inadvertently reduce the quality.
Ideally if the quality metric is not going to be targeted initially, I would
suggest using a nominal value, for example, defining a percentage of all
products manufactured to be scrap.
World class performance?
World class performance is often quoted at 85% but the reality is that
it is wholly dependent on the manufacturing process for a particular
type of product. In some cases a 50% OEE may be exceptional.
Ultimately, OEE is a benchmark that should be used to determine
whether a site is making improvements or not. It doesn’t matter if the
actual value is 85% or 25%.
Paper based data collection
Manual, paper based systems allow users to become familiar with the
concepts of OEE and are, therefore, a good starting point. However,
they have two key issues:
1. It can require a significant amount of time to interpret handwriting
and transcribe it into a tool that can be used to analyse the data.
2. Human nature would inherently mean that the data is not accurate.
If I was running an asset, my focus would be manufacturing
products, not filling in a form. If I reached the end of an 8 hour
shift and realised that I had made 500 products instead of 1000, I
would assume that it would be because I had 4 hours of
breakdown. I would be unlikely to remember how long any period
of stoppage was for and every reason that the asset stopped.
An automatic system will accurately timestamp each stoppage event
and can be used to force reasons to be entered at the time they occur.
This leads to better data that can be automatically analysed.
Quality
is an indication of how
well the products are
being made.
It is calculated as the
number of good products
as a proportion of the
total number that were
started.
OEE
OEE is a widely used
analysis and
benchmarking metric.
World class sites are
regarded as an 85% or
above OEE, and the
average OEE is around
65%.

4. April 2020
OEE  Machine Downtime  Manufacturing Information Systems
4 What about manual assembly?
Although tracking OEE for a manual assembly process is inherently
dependent on an operator entering accurate information, there is no
reason why it cannot be monitored so that data is collated
electronically and automatically processed, meaning that there is only
minimal administration required.
If you also look at minimising operator interactions using barcode
scanners, RFID readers, and the integration of the OEE system with
production planning to get works orders / jobs automatically, then
there are some significant additional benefits to be realised.
Response times
In order to improve, one of the key areas to address is response times.
This may be simply highlighting to management when an asset has
been stopped for an extended period of time, or improving the
notification / call out mechanisms available for maintenance staff.
For longer stoppages there is often a disagreement between
production and maintenance about how long a breakdown took to
repair. Recording call out and response times allows these period to be
analysed in more detail to determine, for example, if there are
sufficient maintenance staff on a night shift.
In addition, allowing operators to request raw materials or their team
leader, direct from their asset can also result in shorter stoppages.
What about the detail?
In order to make improvements you will need to go from the 3 key
metrics into the data that they are made up of. For example,
• If the availability measure is low then you need to understand what
stoppages have occurred and why?
• If the performance metric is low, you need to be able to review the
data to determine what is happening and potentially see the
reasons for slow speed running.
• If the quality measure is low, what are the reasons for scrap?

5. April 2020
OEE  Machine Downtime  Manufacturing Information Systems
5 Why OEE?
OEE is not a panacea but it is a great tool for identifying where issues
are and providing a means of seeing that improvements have been
made.
Implementing an OEE system that can be easily expanded over time to
cover more assets and include additional functional areas is a way of
instilling continuous improvement throughout the workforce.
After all, your competitors are improving and unless you continue to
become more efficient, you will get left behind.
About the
Author
Ashley Tizard is the
Managing Director of
Tascomp Ltd. He has
implemented machine
downtime systems for
almost 30 years, looking
at the reasons for
stoppages, OEE, and
improving response times
to issues.
He has worked in virtually
all manufacturing industry
sectors, including:
• Food & Drink
• Chemicals and
Pharmaceuticals
• Metals
• Forestry Products
• Automotive
• Aerospace
• Print
• Textiles