A Practical Guide to Understanding and Measuring OEE

1. HELPING MANUFACTURERS
MAKE BETTER DECISIONS.
A Practical Guide to
Understanding and
Measuring OEE

2. Contents
Benefits of Measuring OEE
Three Components of OEE
AVA (Availability) Time Elements
Calculating (AVA) Availability
Calculating Pe (Performance)
Calculating Q (Quality)
OEE Formula Cheat Sheet
Analysing & Reporting on OEE
World-Class OEE
Automating Data Collection
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04
05
06
07
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3. Why Measure Your OEE?
A core metric in Total Productive Maintenance (TPM) and lean methodology, OEE
(Overall Equipment Effectiveness) is a measurement that indicates the degree to which a
manufacturing plant is truly productive. Using OEE to assign a numerical value to improvement
opportunities enables manufacturers to assess the effectiveness and viability of production
equipment and make informed CAPEX and OPEX decisions.
Justify CAPEXEngage Operators
Improve the performance of
your staff and machinery by
measuring where your capacity
constraints exist.
Benefits of Measuring OEE
Capture Inefficiencies
Develop a culture of continuous
improvement and engage
staff with accurate and visible
metrics.
Achieve ROI when maintaining
and replacing machinery with
historical data on machinery
performance.
• Reliable, accessible, and
accurate metrics ensure
that plant personnel
are aware of their
performance and their
contribution to business
goals.
• Straightforward metrics
increase cross-functional
communication.
• Justify capital
expenditure with
accurate data on asset
performance.
• Identify the true cost of
machine inefficiencies
and directly tie machinery
performance to business
and fiscal reporting.
• Identify lost time in
production, such as
unplanned downtimes,
micro stops, and more.
• Monitor changeovers,
planned downtimes, and
identify slow running lines
and machinery.
• Record waste and gain
accurate visibility over
production output and
quality.

4. Availability depicts the
uptime (or run time) as a
proportion of the time in
which a machine is available
for production. A decrease in
availability is often attributed
to setup times, changeovers
between SKUs, and planned
and unplanned downtimes.
Availability
Performance indicates all
losses that result due to
machinery not running at
optimal speed. A decrease
in performance is often
attributed to slow running
speeds.
Performance
Quality measures
manufactured units that do
not meet acceptable quality
standards. A decrease in
quality is generally attributed to
defective units.
Quality
Breaking it Down:
OEE Metrics
OEE is a product of the following three metrics: Availability,
Performance, and Quality. An OEE value of 100% indicates that your
production machinery is producing perfect products, with no waste
(100% Quality), as fast as possible (100% Performance), and without
any downtime (100% Availability). The most basic OEE calculation is:
OEE% = AVA% (Machine Availability) x PE% (Speed) x Q% (Yield)

5. Calculating Availability –
AVA Time Elements
Before measuring your AVA, it’s important to understand the different AVA variations and
machine states that are used to calculate them. The exact metric you choose will vary
based on the data that you are analysing.
Capital Time: Total potential hours that a
machine can operate. AKA 24x7.
Shift Time: The time the machine is
crewed by operators. Measured as the
duration from shift start to shift end.
Open Time: The total time a machine is
planned to be operational for, including
setup but excluding planned downtime.
Production Time: This is the time
a machine can produce products.
It excludes setup and any planned
downtimes.
Run Time: This is the time a machine
actually producing products (Run Normal
+ Run Slow time).
Run Normal
Run Slow
Unplanned
Downtime
Setup
Planned
Downtime
Idle Time
Run Time
Production
Time
Open Time
Shift Time
Capital
Time
3
6
9
12
15
18
21
21
Hours
Idle Time: Also known as “No Shift Time”,
e.g. weekends, holidays, time between
shifts.
Planned Downtime: Any planned lost
time, such as meal breaks, cleaning,
maintenance etc.
Setup: Time in changeover or initial
setup.
Unplanned Downtime: All unplanned lost
time, including short stops.
Run Slow: Your machine is running, but
at a slower than expected speed.
Run Normal: Your machine is running at
expected speed.
Machine States
AVA (Availability) Variations

6. Calcluating Availability
Calculating AVA (Availability)
Capital: AVA(c) = Run Time/ Total Time
Shift: AVA(s) = Run Time/ Shift Time (green + red + yellow + blue) No Shift
No Shift
No Shift
No Shift
Run Normal Run Slow Downtime Setup Time Planned
Open: AVA(o) = Run Time/Open Time (green + red + yellow)
Production: AVA(p) = Run Time/green + red
Planned
PlannedSetup
What AVA Variation Should I use?
When choosing which variation of AVA to use for your OEE formula, it’s important to consider what
information you’re looking to gain from the calculation.
To help you understand the purpose of each AVA variation, please consider the following example.
Example Shift: Crew arrive at 6:00 AM and leave at 4:00 PM. Machinery has 1 hour of planned downtime,
30 minutes of setup time and 30 minutes of unplanned downtime.
Capital AVA
AVA(c) measures the run time of your machinery relative to all available time in the day. With the above
example the AVA(c) calculation for that day would be: Run Time (10 Hours - 2 Hours)/ Total Time (24 Hours) =
AVA(c) 33.33%
Shift AVA
AVA(s) measures the run time of your machinery relative to time when the machine is staffed. With the above
example the AVA(s) calculation for that day would be: Run Time (10 Hours - 2 Hours)/ Shift Time (8 Hours + 1
Hour + 30 Min + 30 Min) = AVA(s) 80%
Open AVA
AVA(o) measures the run time of your machinery relative to all time your machine was scheduled to be
operational.It does not include planned downtime or idle time. With the above example the AVA(o) calculation
would be: Run Time (10 Hours - 2 Hours) / Open Time (8 Hours + 30 Min + 30 Min) = AVA(o) 89%
Production AVA
AVA(p) measures the run time of your machinery relative to all time your machinery was scheduled to
be producing products. This excludes downtimes and setup times. With the above example the AVA(p)
calculation would be: Run Time (10 Hours - 2 Hours) / (Run Time (8 Hours) + Unplanned Downtime (30 Min))
= AVA(p) 94%

7. Calculating PE (Performance)
Run Normal Run Slow Downtime Setup Time
Run Normal Run Slow Downtime
Run Normal Run Slow
Units In ÷
Units In ÷
Units In ÷ = Run Speed
= Production Speed
= Open Speed
Calcluating Performance
(Run Normal Run Slow x Rated Speed)Units In ÷ = PE
(Run Normal Run Slow x Nameplate Speed)Units In ÷ = PE(c) or Capital PE
Calcluating Speed
OEE Units & Speeds
The table below lists the unit and speed elements used to determine speed. Speed is a metric used when
calculating Performance (PE).
Unit Measure Description
Units In The number of units counted into the process.
Units Out The number of units counted out of the process.
Setup Units The number of units counted during Setup Time.
Run Speed The actual speed achieved during “Run Time”.
Open Speed Speed achieved during “Planned Production Time”
Rated Speed The theoretical potential speed for a given product.
Nameplate Speed The maximum potential speed of a machine.
Production Speed Speed achieved during “Production Time”.
Calculating Q (Quality)
(Units In - Defective Units) ÷ Units In

8. OEE Formula Cheat Sheet
Metric Description Calculation
AVA(c) Actual run time relative to capital time Run Time/Capital Time
PE(c) Actual speed relative to max machine speed Units In/(Run Time*Nameplate Speed)
Q Units out relative to units in Units Out/Units In
OEE(c) AVA(c)% x PE(c)% x Q%
Capital OEE
Metric Description Calculation
AVA(s) Actual run time relative to shift time Run Time/Shift Time
PE Actual speed relative to rated speed Units In/(Run Time*Rated Speed)
Q Units out relative to units in Units Out/Units In
OEE(s) AVA(s)% x PE% x Q%
Shift OEE
Metric Description Calculation
AVA(o) Actual run time relative to open time Run Time/Open Time
PE Actual speed relative to rated speed Units In/(Run Time*Rated Speed)
Q Units out relative to units in Units Out/Units In
OEE(o) AVA(o)% x PE% x Q%
Open OEE
Metric Description Calculation
AVA(p) Actual run time relative to open time Run Time/Production Time
PE Actual speed relative to rated speed Units In/(Run Time*Rated Speed)
Q Units out relative to units in Units Out/Units In
OEE(p) AVA(p)% x PE% x Q%
Production OEE

9. Analysing & Reporting on OEE
As you now know, OEE is a metric that is comprised of data on machinery availability, performance, and quality.
But to derive value from your OEE score, you need to drill down into each element to uncover where your
inefficiencies lie.
Below are some key insights you can derive by analyzing your OEE data:
• Understand how your machinery is performing over time with OEE trend reports and benchmark your
progress.
• Identify key problematic and repetitive downtimes and use this information to justify CAPEX decisions,
conduct root cause analysis (RCA) and improve performance.
• Monitor planned downtime and changeover times between products and analyse attainment to plan.
• Monitor quality performance and reduce defective units by uncovering reasons and areas of waste.
World-Class OEE
The idea of ‘World-Class OEE’ was originated by the pioneering founder of TPM, Seiichi Nakajima in 1984.
The figures have roots in the Japanese automotive industry and can be used as a reference to how the most
efficient plants in that industry and locale operate.
OEE WASTE
(Perfect) (World Class) (Typical) (Low)
100% 85% 60% 40%
While it’s interesting to see how you measure up to other leading manufacturers, it should be noted that
World-Class OEE is not a number that you should benchmark your performance against. This is because OEE,
as a metric, is relative to your production situation. As such, world-class OEE for a high-speed bottling line
will strongly differ from that of a metal extruder that produces small-batch units and has a high number of
changeovers.
As such, best practice would be to benchmark yourself against your own OEE and use that original OEE number
as a baseline from which to improve.

10. Automating Data Collection & Reporting
Manually capturing every production loss – particularly micro stops, changeovers, slow running times, and
downtimes – can be a tedious and near-impossible task for many manufacturers. Automating this data
collection with IIoT and software solutions like OFS assists manufacturers in getting accurate information
from production lines and making timely decisions.
Benefits of automating your OEE data collection and reporting:
• Data is collected with sensors on the production line. This ensures accurate recording of each and every
stop, wasted unit, and sub-optimal running event.
• Data is automatically fed into reporting modules. This saves time manually importing paper-based
information into spreadsheets – reducing data redundancy and preventing human error.
• Automated data collection allows you to review production performance in real-time. This allows you to
be proactive, alert relevant team members when needed and make smart CAPEX decisions.
• Automatically generated reports provide granular information on OEE. Analyse and review top downtime
reasons, asset utilization, OEE, and more.
Ready to automate your OEE data collection and reporting? Click here to request a free demonstration of
the OFS software suite and join 1,000s of leading manufacturers who are using real-time information to
drive manufacturing improvements.
OFS real-time dashboards and reports provide you with instant information on production performance.
Automate With OFS

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