Transcript OEE Guide--Final

OEE: THE COMPLETE GUIDE
Everything you Need to Successfully Implement,
Analyze, and Improve Overall Equipment Effectiveness
Table of Contents 
: 
PART I: WHAT IS OEE?
PART III: HOW TO ANALYZE OEE
pg. 3
1. OEE Factors and Formulas
pg. 24
10.The Six Big Losses
a. Availability
a. Breakdowns and Changeovers
b. Performance
b. Minor Stops and Reduced Speed
c. Quality
c. Startup Defects and Scrap
2. OEE Calculation Example
3. OEE Comparisons
PART IV: HOW TO IMPROVE OEE
4. Calculating Production Line OEE
11. Improvement Methodologies
5. Calculating Long Term OEE
12. Reducing Changeover Time
PART II: HOW TO IMPLEMENT OEE
pg. 26
13. Eliminating Breakdowns
pg. 16
14. Eliminating Minor Stops
6. Selecting a Pilot Machine
15. Maximize Production Rate
7. Defining OEE for the Pilot Machine
16. Preventing Startup Defects
8. Data Collection
17. Eliminating Waste
9. Software Considerations
PART V: SUMMARY
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pg. 32
2
PART I
WHAT IS OEE?
PART I: WHAT IS OEE?
oee oVERVIEW
OEE OVERVIEW
Overall Equipment Effectiveness (OEE) is a
manufacturing performance metric that is used to
identify lost opportunities and measure improvement
efforts. OEE accounts for all lost production by
determining how much quality product is produced
compared to how much should have been produced in
the available time.
Essentially, OEE quantifies the effectiveness of a
process by measuring the percentage of time that is
actually productive.
Production losses occur when the machine is not
running (unplanned downtime), running at a reduced
speed (speed loss), or producing products that are out
of spec (quality loss).
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PART I: WHAT IS OEE?
OEE FACTORS AND FORMULAS
OEE FACTORS AND FORMULAS
Unplanned downtime, speed loss, and quality loss are quantified by
calculating three OEE factors:
Unplanned
Downtime
• Availability (unplanned downtime)
• Performance (speed loss)
• Quality (quality loss)
Speed Loss
Available
Time
(Max Units)
Then, OEE is calculated by multiplying these factors:
Quality Loss
OEE = (Availibility) x (Performance) x (Quality)
Effective
Time
(Good Units)
The OEE factors can be calculated on a production unit or time basis.
Each factor is a percentage, so the result is the same no matter what
values are used. Typically, availability is calculated based on time
because downtime is measured in time, not units. Performance and
quality are easiest to calculate with production units. The target
production rate is required to convert between time and production
units. For example, if the available time is 1,000 minutes and the
target production rate is 10 cases/min, then the maximum production is
10,000 cases.
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PART I: WHAT IS OEE?
Availability
AVAILABILITY
Availability accounts for the unplanned downtime losses by calculating
the percentage of time the process is actually operating during the time
it is available to operate. Availability can be calculated using the following
formulas:
Unscheduled
Time
Unplanned
Downtime
Availability =
Operating Time
Available TIme
Operating Time = Available Time - Unplanned Downtime
Available Time = Total Time - Unscheduled Time
Total Time
Available
Time
(Max Units)
Operating
Time
(Target Units)
Substituting for operating and available time simplifies the availability
formula to:
Availability = 1-
Unplanned Downtime
Total Time - Unscheduled Time
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PART I: WHAT IS OEE?
Availability
Unscheduled Time
Unplanned Downtime
Available time equals the total time of the evaluation period
minus the unscheduled time during that period. Unscheduled
time is the time that the process is not scheduled to run and is
subtracted from the total time to determine when the process is
actually available to run. Unscheduled time should only include
the following:
If a machine is not operating when it is available (scheduled
to run), then it is considered unplanned downtime. Typically
considered unplanned downtime, events such as preventative
maintenance, changeovers, cleaning, operator breaks, and
meetings can occur during unscheduled time without counting as
downtime.
Lack of Customer Orders. When a machine can produce
more than customer demand, the machine is not required
to run without customer orders, so curtailment is considered
unscheduled time. If the process continues to produce to add
inventory to the warehouse instead of curtailing, the time should
be counted as available time. Do not hide overproduction waste.
However, if they occur during scheduled time, the time needs to
be accounted for so the events should be considered unplanned
downtime. The goal is to improve the process, not to have a high
OEE, so all losses in control of the operations team should be
tracked.
Lack of Operating Personnel or Resources. These must be
caused by forces outside the company’s control (force majeure)
in order to be considered unscheduled time. A planning mistake
that causes a raw material supply shortage should be considered
unplanned downtime and should count in the OEE calculation.
You wouldn’t want to hide these problems.
Product Development/Trials. During research & development,
the equipment is unavailable to the production team, so this time
is considered unscheduled and is excluded from OEE calculations.
This isn’t always popular because people don’t like to see a
lower number, and some things may seem like they are not in
control of the operators. However, if you want to identify all
opportunities that are available for improvement, you must be
honest with yourself and not worry about the absolute OEE value.
The goal is to produce more quality product that your customers
will buy. Customers do not care if your OEE is 50% or 34%; they
only care that you have the ability to fill their order on time.
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PART I: WHAT IS OEE?
performance
PERFORMANCE
Just because the machine is operating, doesn’t mean that it is producing
products at the desired rate. The performance factor of OEE shows how
well a machine runs by measuring the speed loss that occurs during
operating time. The performance factor compares the actual units
produced to the target units and is calculated using the following:
Performance =
Unscheduled
Unscheduled
Time
Time
Unplanned
Unplanned
Downtime
Downtime
Speed Loss
Actual Units
Target Units
Total Time
Available
Available
Time
Time
(Max
(MaxUnits)
Units)
(or)
Operating
Operating
Time
Time
(Target
(TargetUnits)
Units)
Productive
Time
(Actual Units)
Actual Units
Target Production Rate x (Total Time - Unscheduled Time - Unplanned Downtime)
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PART I: WHAT IS OEE?
performance
Target Production Rate
Define the target production rate with the smallest feasible time
period for your process, like units/min or units/hr. The choice
of target production rate can vary depending on how a facility
wants to evaluate the performance. Some companies will use a
“budget” or “standard” production rate that is product specific.
However, using a budget speed that is lower than the maximum
speed raises the OEE and hides the true production capacity.
The best way to calculate the performance factor is to always
use the maximum theoretical production rate. This is sometimes
referred to as the nameplate capacity or design speed for the
equipment. To make all speed losses visible, the target speed
should be the same for all products even though some products
may be run at slower speeds.
For example, if the maximum production rate for a packaging
machine is 150 packages/min but the current product can only
be produced at a rate of 100 packages/min, you should still use
150 packages/min for the target production rate.
Knowing the speed loss caused by “difficult products” can
help compare and understand the total business impact of
running some products with reduced capacity. This information
can be used to optimize the product mix or identify process
improvements that will increase the speed.
The performance factor should never exceed 100%, so it is better
to have a target speed that is too high versus one that is too low.
If the performance factor is above 100%, it can hide deficiencies
in availability or quality. You want to make improvements, but
the speed target should only be changed if there is a major
process or equipment change.
Reaching the maximum speed should not be a regular
occurrence that requires frequently updating the target speed. If
a theoretical maximum is not known, it is a good idea to set the
target speed 10-25% above the current demonstrated maximum
to ensure the performance factor does not exceed 100%.
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PART I: WHAT IS OEE?
Quality
QUALITY
Not all of the units that are produced meet quality specifications.
The quality factor accounts for quality losses by comparing the
number of good units to the total number of units produced,
and is calculated using the following:
Quality =
Unscheduled
Time
Unplanned
Downtime
Total Time
Good Units
Actual Units
Good Units
A good unit is a unit that meets quality specifications the first
time through the process. If a part doesn’t initially meet quality
specifications, then the time spent reworking that part should be
counted as an OEE loss because resources are used to rework
the part instead of producing a new, quality part.
Also, the unit must be compared to the quality specifications
that apply to the intended product. For example, some units
might not meet their quality specifications, but they could be
downgraded and sold as a different grade, brand, etc. Although
Speed Loss
Available
Time
(Max Units)
Operating
Time
(Target Units)
Quality Loss
Productive
Time
(Actual Units)
Effective Time
(Good Units)
they can still be sold, the product did not meet its intended
purpose as produced, so it was not correct the first time through
the process and it should be considered waste.
The good unit count can be one of the more difficult aspects of
OEE to track. Some processes can be sending rework through
at the same time as new products so it can be difficult to
isolate. Some consideration should be given to how this can
be accomplished in your particular process. As far as OEE is
concerned, waste (scrap), rework, or downgraded products are
all considered quality losses.
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PART I: WHAT IS OEE?
oee calculation example
OEE CALCULATION
EXAMPLE
Availability = 1 -
Using the above equations, there are only
5 variables you need to track in order to
calculate OEE. These variables, including
example values for a 24 hour period, are:
Performance = Unplanned Downtime
Actual Units - Unscheduled Time
(or)
1-
331
1440 - 60
= 0.76 or 76%
Actual Units
Target production rate x (Total Time - Unscheduled Time - Unplanned Downtime)
(or)
Unscheduled Time = 60 minutes
9,020
10.5 x (1,440 - 60 - 331)
= 0.82 or 82%
Unplanned downtime = 331 minutes
Actual units produced = 9,020 units
Target production rate = 10.5 units/min
Good units produced = 8,749 units
Quality =
Good Units
Actual Units
Once each of the factors (Availability, Performance, and Quality)
have been calculated, they can be multiplied to determine the
OEE. Using the values from the following examples:
(or)
8,749
9,020
= 0.97 or 97%
OEE = (Availibility) x (Performance) x (Quality)
(or)
0.76 x 0.82 x 0.97 = 0.60 or 60%
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PART I: WHAT IS OEE?
oee calculation example
Alternative OEE Formula
There is an alternative way to calculate OEE by simplifying the
formula. Using the formulas for the three OEE factors, you can
see that actual units cancels out.
Although this is not the standard OEE formula, the result will
be equivalent to multiplying the three factors. This formula
has been included because it can greatly simplify automated
OEE calculations because the formula uses the basic variables
mentioned above. However, it is important to remember that
the purpose and power of OEE is in evaluating the losses.
Therefore, you should still calculate and track availability,
performance, and quality separately. This topic will be discussed
further in the data collection and OEE analysis sections.
OEE =
Operating Time
Available TIme
x
Actual Units
Target Units
x
Good Units
Actual Units
(or)
OEE =
Good Units
(Total Time - Unscheduled Time) x Target Production Rate
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PART I: WHAT IS OEE?
oee comparisons
OEE COMPARISONS
Although each OEE factor in the example above may seem
acceptable on its own, the process is only producing quality
product 60% of the time. This seems rather low doesn’t it?
Actually, 60% is a typical OEE value for manufacturing operations
and values under 50% are quite common.
Both Process A and Process B have an OEE of 66%, but which
one would you rather have? Process A has a lot of changeover
time from product changes, but when it is running, it runs well.
They could benefit from setup reduction or improved production
scheduling. On the other hand, Process B has a much higher
availability because there is much less changeover time, but
would you like to have 91% quality instead of 99% like Process A?
You may have seen references stating that an OEE greater
than 85% is considered world class, but OEE is not meant for
comparing different processes, or even similar processes with
different circumstances. The following example illustrates the
problem with OEE comparisons:
You can see that there are many ways to get the same OEE, so
care must be taken when making OEE comparisons. The power
of OEE comes from analyzing the losses, not the resulting OEE
score. OEE is best used as a way to identify losses and increase
the output on a specific machine.
Variable
Process A
Process B
Available Time (minutes)
1440
1300
Breakdowns (minutes)
105
204
Changeover Time (minutes)
300
30
Availability (%)
72
91
Performance (%)
92
80
Quality (%)
99
91
.64*.92*.99=66%
.83*.80*.91=66%
OEE (%)
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PART I: WHAT IS OEE?
calculating production line oee
CALCULATING PRODUCTION
LINE OEE
When calculating OEE for a production line, you should collect
availability data on the bottleneck (slowest machine) of the
process because the bottleneck determines the production for
the line. Downtime events should be tracked for all pieces of
equipment in the line.
When tracking downtime for the bottleneck, also keep track of
the amount of time the bottleneck is starved and blocked. The
bottleneck is starved when waiting for input from upstream
equipment and it is blocked when downstream equipment
cannot receive output.
Step 1
(120 units/min)
Step 2
(115 units/min)
The actual speed for the line is equal to the bottleneck speed,
but the speed target for the performance factor should be
based on the fastest equipment in the line. This will highlight
the impact of having an unbalanced line and will help justify
improvement activities on the bottleneck.
In the process above the slowest step is 90 units/minute and the
fastest is 120 units/minute. If step 4 consistently runs at 90 units/
min, the performance rate would be 90/120, or 75%. So, why
not use 90 as the target speed and then have a performance
rate of 100% because the line cannot run faster than its slowest
component. Looking at the performance rate this way hides the
fact that this line is handicapped by a step that can run only 75%
of the rest of the line. Effort should be focused on the slowest
step to have the biggest impact on effectiveness.
Step 3
(120 units/min)
Step 4
Bottleneck
(90 units/min)
Step 5
(120 units/min)
Focus on the Bottleneck
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PART I: WHAT IS OEE?
Calculating long term oee
CALCULATING LONG TERM OEE
OEE is a weighted calculation. Usually, OEE is calculated for small
time periods, such as an hour or shift, and then simply averaged
to calculate an OEE for a longer time period, but this is a bad
practice. OEE should be calculated from its base data for each
time period. The following example illustrates why averaging
OEE values does not work.
Shift
OEE
Available Time
1
61%
480
2
53%
480
3
72%
120
If you just take the average by adding the OEE values together
and dividing by three, you will get a daily OEE of 62%. However,
the third shift only had 120 minutes of available time, so when
weighted by available time, the daily OEE is actually 59%. The
difference may seem small, but it is important, especially when
you are trying to track progress.
The best way to setup OEE is to get everything in units of time,
including performance and quality. The calculations can still be
based on units for understanding, but an additional calculation
should be made to convert units into effective minutes.
If you stay with units for performance, you’ll end up with a value
that is more heavily weighted to products that have a higher
target production rate. This is another reason to have one
standard production rate for your line, regardless of individual
product capabilities because then the calculation can be left with
units.
OEE is weighted by time.
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PART II
HOW TO IMPLEMENT OEE
PART II: HOW TO IMPLEMENT OEE
sELECTING A PILOT MACHINE
SELECTING A PILOT MACHINE
When starting with OEE, it’s best to choose a pilot machine.
This choice is important because the first machine is a learning
experience to test OEE and highlight the process for the rest of
the facility.
It is important to pick a machine that has a high likelihood of
success. Consider choosing a single machine with a relatively
limited product mix instead of a complicated production line or a
machine that has an extensive product mix.
Make sure you have a “team” that will help make OEE
implementation successful, with both operators and mechanics
part of the process. Finally, make sure that you can measure all
of the variables you need to calculate OEE.
DEFINING OEE FOR THE PILOT
MACHINE
The OEE formula is standard, but it is important to get everyone
on the same page with regards to what, when, where, how,
and why the data is collected. A standard definition of OEE and
its factors must be identified and communicated throughout
the organization. Involving operators when defining the OEE
calculation is beneficial because it will help them understand and
trust the measurement system. It is important to define what is
considered unscheduled or unplanned downtime, and you must
decide on the target rate for calculating the performance factor.
Downtime and speed should be measured on the process
bottleneck (slowest machine) because the bottleneck determines
the production for the line. For production lines where all
machines run at identical speeds, the best practice is to calculate
OEE on the equipment that performs the primary function.
Once you start identifying opportunities, make sure there is
enough support in the organization to make the desired changes
so identified problems don’t linger too long. Try finding some
quick wins that will help generate momentum and make your
program successful.
Once you start identifying opportunities, make sure there is
enough support in the organization to make the desired changes
so identified problems don’t linger too long. Try finding some
quick wins that will help generate momentum and make your
program successful.
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PART II: HOW TO IMPLEMENT OEE
DATA COLLECTION
DATA COLLECTION
Automation
Now that you have seen how OEE is calculated, you need to
figure out how to collect the required data and calculate OEE.
OEE can be tracked manually on paper or in a spreadsheet, or
there are several software options. Manual calculations and
tracking can be a good way to get started and verify the data
collection process, but automatic systems will help save time and
effort and will provide more reliable results.
Also, the goal of tracking OEE is to get the right information to
the right people at the right time so they can solve problems that
reduce waste and improve productivity. Automatic event tracking
with real-time displays can help operators log information and
make corrective actions in a timely manner.
In addition to the 5 required variables, you should also consider
what information you need to problem solve the OEE losses.
For example, it is a good idea to capture detailed downtime
data, such as the machine fault, downtime reason, duration, and
operator comments or corrective actions. You might also want
to collect the quality measurements used to determine if the
product is within specifications and any off-quality reasons.
It is possible to track downtime manually, but manual data is
usually not accurate and it is difficult to use in a timely manner.
For example, operators aren’t good time keepers. They are busy
trying to resolve the problem and get the machine running, so
the downtime duration is a guess that is often inaccurate. It is
easy to think you were down for an hour when maybe it was
only half an hour. How many times have you been at work and
thought it must be almost lunch time, and when you look at the
clock it was only 10 a.m.?
Additionally, manual data can get incorrectly transcribed or lost
and it can be difficult to compile accurately. When events go
unassigned it is difficult to know what to work on, but inaccurate
data can be even worse. An operator might also document an
inaccurate time on purpose to hide excessive downtime.
There are some areas where operator involvement is critical. An
operator can explain what really happened, but an automated
data collection system should be relied on to collect the data and
then operators can help turn that data into useful information.
Automation also frees up the operator so they can spend more
time operating and less time documenting.
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PART II: HOW TO IMPLEMENT OEE
DATA COLLECTION
Capture Availability Data
Ultimately, you want to know if your machine is running or not,
but it is helpful to subdivide downtime and capture five machine
states. The key states are:
• Running – the machine is producing product
• Down – the machine is not producing product because of
an unplanned event related to the machine (breakdown,
changeover etc.)
• Unscheduled – the machine is not producing product
because it is not scheduled to run (no customer demand/
orders)
• Starved – the machine is not producing product because
the machine is not receiving product from upstream (an
upstream machine is down)
Ideally, the state would be determined by the machine control
system, but it can also be done with calculations in downtime
tracking software. Downtime events can then be triggered by the
machine state, and a start time and end time are recorded.
It is also a good idea to divide downtime into major and minor
stops. Most people consider minor stops to be downtime events
that are less than five minutes that don’t require maintenance.
Minor stops could include events such as jams, blocked sensors,
or minor adjustments. Downtime events that are greater than 5
minutes are considered major stops and should be identified as
either breakdowns or changeovers. Minor stops are considered
part of the performance factor.
• Blocked – the machine is not producing product because
the machine cannot discharge products (a downstream
machine is down)
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PART II: HOW TO IMPLEMENT OEE
DATA COLLECTION
Assign Downtime Reasons
After a downtime event is created, a reason needs to be identified and
assigned because knowing why the machine went down is essential for
problem solving. Some systems can automatically assign a reason based
on the error code from the machine. Operators can verify automatically
generated reasons or select the appropriate downtime reason from a
pre-determined list of common causes. Some companies even build
the reason picking functionality directly into the machine controls and
require the operator to select a reason prior to starting the equipment
back up. This is a way to guarantee all downtime events get a reason
assigned to them, but be careful because it could cause inaccurate
data or frustration because the operator just wants to get the machine
started again.
Try to create a manageable and focused list of downtime reasons.
You need to have an appropriate list of reasons to be successful. The
reason list should be small and standardized for each equipment type.
You cannot work on everything at the same time. Most likely you will
prioritize and work on the top 3-5 downtime categories. So what benefit
is there to having 30 reasons? You want the list large enough so events
can be assigned a reason and not be categorized as “Other.” A list with
10-12 reasons is usually sufficient. Also, don’t make the operator drill
down too many levels into the reason tree to find the right reason. Just
because the system has 4 levels, doesn’t mean you have to use them all.
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Assign reasons to facilitate problem solving.
20
PART II: HOW TO IMPLEMENT OEE
DATA COLLECTION
Create a Reason Tree
Capture Downtime Event Attributes
When creating downtime reason trees, you should keep the
following points in mind:
There is additional data that you should consider collecting to
help make the downtime data useful, including the following:
Reasons should be distinct. It should be obvious to operators
which reason applies, so you don’t end up with some people
selecting one reason and other people selecting a different
reason for the same direct cause.
• Process area or production line
Reasons should be symptoms. The reason should describe
a direct cause, not a root cause. You should not be asking
operators to determine root cause without some problem
solving activity. For example, the direct cause of the machine
downtime might be a bearing failure. The root cause of the
bearing failure might be lack of lubrication, which could
ultimately mean a deficiency with the lubrication program in the
facility.
• Machine fault/error code
Only include frequent reasons. Do not include reasons that
do not occur often because that only makes it harder to find
the right reason. If you use an “Other” reason, it should not be a
top cause. New reasons should be added to the list so the true
causes are captured.
• Machine name or number
• Product name or code
• Event duration
• Shift number
• Production date and time
• Operator comments (including any corrective actions)
Basically, you want to collect anything that can help identify
who, what, when, where, why for every downtime event. It is
valuable to get operator comments describing the event and any
corrective actions performed in their own words. You will get the
most accurate comments at the time of the event and this also
provides immediate communication.
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PART II: HOW TO IMPLEMENT OEE
DATA COLLECTION
Reason categories can be used to identify top problems, but the
operator comments can be invaluable when trying to identify
the root cause. With practice and coaching you can start to get
comments loaded with information.
Note: Similar data collection and reporting should be set up for
speed and quality losses.
Provide Real-Time information for Real-Time
Problem Solving
The best time to collect information and solve a problem is when
it is actually happening. After-the-fact reporting and problem
solving is not as effective. How downtime data is viewed and by
whom it is viewed is important for driving improvement.
The data should be available continuously and not require
complicated reports to be manually compiled after a long time
has elapsed.
There are several ways to identify and react to the causes of
downtime. Pareto charts are a common tool to visually show the
top downtime reasons either in terms of time or event count in a
given time period.
It is a good practice to develop a process for systematically
addressing the chronic problems near the top of the Pareto
chart. Trends and Gantt charts are also good visual tools that can
be used to show a timeline of downtime events. For downtime
information to be effective, data must be easy to collect, easy
to understand, and must provide enough information for good
problem solving.
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PART II: HOW TO IMPLEMENT OEE
Software Considerations
SOFTWARE CONSIDERATIONS
The OEE calculation is standard, but collecting the right data is
anything but standard. Every facility is different and has different
data collection needs. With that in mind, here are some things to
consider when choosing OEE software:
• How will you track downtime?
• How will you measure the production rate?
• How will you determine and measure the product quality?
• Do the variables currently exist or do you need to create
them?
• Will you need to upgrade equipment with sensors to allow
automatic tracking of OEE?
There may be different data sources with different communication protocols, so an OEE system should be able to acquire data
from all sources and perform calculations with the data.
For example, quality data may be in an MES system like SAP,
production rate data might be in a historian, and downtime data
could be tracked in an Excel spreadsheet. Combining all of the
data to calculate OEE can be a challenge, so you need to have a
flexible tool for OEE.
Another consideration is how to reference the target speeds and
quality specifications, which could be product and equipment
dependent. A good software package will provide a way to store
multiple variable attributes (targets, limits etc.).
Data analysis is an important aspect of OEE improvement.
Some OEE systems are stand-alone calculation and dashboard
programs. A key feature of a good software is the ability to
combine the OEE data with other data, such as continuous
process data or lab test values. Calculating OEE on the fly so
real-time information can be viewed by the people running the
process is invaluable.
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PART III
HOW TO ANALYZE OEE
Overall Equipment Effectiveness, or
If equipment is operating at a high OEE
Once you have cleared the important
OEE, has several benefits over simple
but not meeting customer demand, you
hurdle of configuring and collecting OEE
one-dimensional metrics like machine
know you have a capacity problem. OEE
data, how do you use it to improve OEE?
efficiency. If you are not meeting demand
can also identify spare capacity to keep
The entire purpose of OEE is to highlight
and have a low OEE (equipment is
up with changes in demand.
losses, so all losses must be analyzed,
underperforming) then you know you have
an equipment effectiveness problem.
prioritized, and minimized.
PART III: HOW TO ANALYZE OEE
THE SIX BIG LOSES
THE SIX BIG LOSES
First of all, each OEE factor (Availability, Performance, and
Quality) should be broken down further to provide more
granular data. This approach leads to what are known as the Six
Big Losses.
OEE Factor
Six Big Losses
Description
1. Breakdowns
Downtime events greater than 5 min from unplanned
equipment failures
2. Changeovers (set-up/adjustments)
Downtime from changing products
3. Minor Stops
Downtime events less than 5 min that usually don’t require
maintenance
4. Reduced Speed
Production loss caused by running slower than target speed
5. Startup Defects
Off-quality product produced during startups
6. Scrap/rework (in-process defects)
Off-quality product produced during normal operation
Availability
Performance
Quality
The reason for splitting each factor into two categories is that the
potential causes are usually different. The Six Big Losses provide
an effective way to compare and prioritize production losses,
which leads to more successful identification and elimination
of the root causes. A popular way to view these losses in the
context of OEE, is with the use of a stacked bar or waterfall chart.
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PART III: HOW TO ANALYZE OEE
THE SIX BIG LOSES
OEE WATERFALL
Breakdowns & Changeovers (Availability)
Minor Stops & Reduced Speed (Performance)
The availability factor can be divided into the first two of the
six big losses, changeovers and breakdowns. Both of these
are critical becavuse when the machine isn’t running, there
is no performance or quality to worry about. When collecting
data for a production line with multiple discrete processes,
the availability analysis should be from the perspective of the
bottleneck process. The downtime can be further broken down
into breakdowns on the bottleneck process itself, downstream
breakdowns that block the bottleneck from running, and
upstream breakdowns that starve the bottleneck process. This
extra information will help focus reliability improvements. In the
example above, there is a high percentage of breakdowns on the
bottleneck itself, so the initial effort should be to improve the
availability of the bottleneck asset.
Minor stops are actually short duration downtime events,
such as jams and operator adjustments that do not require
maintenance. The definition is flexible, but typically, downtime
events are considered minor stops when the duration is less
than five minutes, and breakdowns when they are longer than
five minutes. Minor stops disrupt the flow of a production line.
The reduced speed category captures the losses of running
below the target (maximum) speed.
Startup Defects & Scrap (Quality)
Just like the other factors, the quality factor is divided into
startup defects and scrap because there are different causes for
these two categories.
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PART IV
HOW TO IMPROVE OEE
PART IV: HOW TO IMPROVE OEE
IMPROVEMENT METHODOLOGIES
IMPROVEMENT METHODOLOGIES
There are many different continuous improvement
methodologies that can be applied to OEE. There is no right
or wrong way to go about it, but the following discussion will
provide some guidelines for overall improvement and tools
which can be used to minimize each of the Six Big Losses.
After you have developed the plan, it is time to execute that plan
and monitor the outcome. The final step is to close the cycle by
integrating the knowledge you have gained to adjust the goal, or
to formulate a new theory.
The Deming Cycle, or PDSA Cycle (also known as the PDCA
Cycle), is one proven, continuous-improvement model that can
be easily applied to reduce losses. The PDSA Cycle is a sequence
of four logical steps: Plan, Do, Study/Check, Act. This sequence
can be repeated indefinitely to achieve incremental OEE gains.
No matter what method you use to improve OEE, focus on the
process/system and not on the person. Even if the root cause is
people doing something wrong, focus on why a problem occurs
and figure out how to change the system to prevent people
from making that mistake. You may have heard the Japanese
term Poka-yoke, which means mistake proofing. Poka-Yoke is a
technique used to make equipment or processes safer and more
reliable by preventing inadvertent errors.
The first step toward solving a problem is actually identifying the
problem you are going to work on. The Six Big Losses and the
waterfall chart break out the data into smaller buckets to help
identify and then prioritize losses in order to focus improvement
activities. Once you have identified the top losses it’s time to
develop an improvement plan. Based on either historical data
you have collected or expert/user knowledge, you need to
formulate a theory for possible causes and develop a plan to
eliminate them.
There are many examples of mistake proofing that you see
and use every day. For example, new cars are equipped with
many monitoring and alert systems to warn of obstacles in your
blind spots. In a manufacturing facility, interlocks are in place to
prevent machines from running when guards are open. This can
be an effective tool to improve changeover time and eliminate
startup defects. Making machine settings simple or even
automatic so that changes are repeatable helps eliminate the
opportunity for operator error.
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PART IV: HOW TO IMPROVE OEE
Reduce Changeover Time
REDUCE CHANGEOVER TIME
Changeovers are a necessary evil of producing different
products, but the time it takes can be minimized. SMED
(single-minute exchange of dies) is a methodology that breaks
down changeover improvement into 3 basic steps.
• Step 1: Identify and seperate changeover tasks to
internal or external. Internal tasks are done after the
machine has been shut down for a changeover. External
tasks can be done while the machine is still running. For
example, retrieving machine parts and tools is external, but
installing the parts is internal.
Changeover time reduction should also include optimizing the
production schedule to sequence products so the least number
of changes are required. For example, run similar products backto-back and you might be able to use similar machine settings or
have shared parts that don’t need to be changed out.
ELIMINATE BREAKDOWNS
The breakdown category can be further subdivided. All of the
breakdown categories (breakdowns, starved, and blocked)
should be separated into planned and unplanned. The goal
is to minimize planned downtime and eliminate unplanned
downtime.
• Step 2: Evaluate and convert internal tasks to external.
Find ways to convert as many internal tasks as possible to
external tasks. One possibility is to combine several parts
into a pre-assembled module that can be quickly removed
and installed.
Planned breakdowns can include preventative maintenance
and cleaning. Attack the planned downtime like changeovers.
Unplanned production losses can be either chronic or sporadic,
so the frequency and duration/severity should be used for
evaluation.
• Step 3: Simplify remaining internal tasks. Including
standardizing fasteners so fewer tools are needed, or even
replacing them with quick release mechanisms that don’t
require the use of tools.
Chronic downtime events occur frequently. Sporadic events
occur infrequently, maybe just once, but they last a long time or
have a big impact on the business.
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PART IV: HOW TO IMPROVE OEE
Eliminate Minor Stops
Identifying the root cause of sporadic events is usually much
easier. For the chronic downtime, some more structured
problem solving may be required. You can follow the PDSA Cycle
or whatever methods your organization might use.
ELIMINATE MINOR STOPS
Minor stops are essentially breakdowns of short duration,
but that doesn’t mean these events don’t have a significant
impact on the business. Automated data collection is critical for
accurately capturing minor stops, but don’t overwhelm operators
by requiring them to log reasons for every 30 second downtime
event. A lot of minor stops are chronic issues, so if you have a
lot of minor stops, operators can usually tell you what problems
they deal with every day. You can go out to the line and observe
while its running and you will probably see the main causes of
chronic minor stops.
Some minor stops may be harder to identify. Integration
problems between machines in a production line are common.
Machine and conveyor speeds need to be correctly programmed
to balance the flow of product between processes. The starved
and blocked data can help with minor stops as well. Look for
instances when the bottleneck is starved or blocked when there
are no minor stops upstream or downstream.
MAXIMIZE PRODUCTION RATE
There are many possible causes for speed loss. Your equipment
might be worn so performance has deteriorated. You may
have poor quality raw materials that require running at slower
speeds. Some operators might have less experience so they are
not comfortable running the machine any faster. The training
and operating procedures may be inadequate. To combat
this, develop standards to make the process more robust so it
doesn’t matter who is running the machine. Operators usually
set the machine speed where it gives them the least amount of
problems. Go see what problems they are trying to compensate
for and eliminate them. Sometimes just making speed loss
visible will lead to improved performance because people are
aware it is being observed. Whatever the potential causes, focus
on the bottleneck because it determines the speed of your line.
PREVENT STARTUP DEFECTS
Startup defects should be evaluated as part of your changeover
improvement efforts. What can be done to make changeovers
repeatable so that the time it takes to consistently produce
good products is minimized? Automation and recipes that can
automatically download machine settings can reduce a lot of
variation during startups.
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PART IV: HOW TO IMPROVE OEE
Eliminate Waste
ELIMINATE WASTE
Defects are all about variation in the process. Six Sigma is common methodology
that consists of tools for reducing variation and eliminating defects. However,
you don’t have to be practicing Six Sigma to reduce defects. The goal should be to
achieve zero defects, even though this might not be possible.
Defects are directly related to variability, so reducing process variability is key to
improving quality. Identify why parts are scrapped and identify process control
parameters that impact the quality variable. Try to identify continuous variables
that can be monitored to predict the outcome of quality parameters that are
measured less frequently.
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PART V
SUMMARY
PART V: SUMMARY
OEE Summary
OEE SUMMARY
Availability accounts for unplanned downtime, performance
accounts for speed losses, and quality accounts for losses from
producing off-quality product. Multiply the factors together
to calculate OEE. Focus on the Six Big Losses to prioritize
improvement efforts. The topics covered in this guide are
summarized in the following graphics:
Overall Equipment Effectiveness (OEE) is a manufacturing
performance metric that is used to identify lost opportunities
and measure improvement efforts. The lost opportunities are
quantified by the three OEE Factors: Availability, Performance,
and Quality.
Lack of customer orders
Lack of operating personnel
Lack of resources
Product development and trials
Unscheduled
Time
Unplanned
Downtime
Available Time
(Max Units)
Availability =
Six Big Losses
Operating Time
Available TIme
OEE = (Availibility) x (Performance) x (Quality)
Breakdowns
Changeovers
Reduced Speed
Minor Stops
Speed Loss
Operating Time
(Target Units)
Performance =
or
Productive Time
(Actual Units)
Quality Loss
Effective Time
(Good Units)
Actual Units
Startup Defects
Scrap/Rework
Quality =
Target Units
Good Units
Actual Units
Good Units
(Total Time - Unscheduled Time) x Target Production Rate
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PART V: SUMMARY
OEE Summary
OEE
OEE Factors
Definitions
Improving
the Six
Availability
Performance
Quality
Include All Downtime
Exclude Unscheduled Time
Use DESIGN SPEED for Target
A Good unit is CORRECT the 1st Time
- Breakdowns
- Changeovers
- Preventative
- Maintenance
- Cleaning
- Operator Breaks
- Lack of Customer Orders
- Lack of Operating Personnel
- Lack of Resources
- Product Development (Trials)
Production Rate for ALL products
through the process
Performance should NEVER exceed
Exclude Rework & Downgraded
100%
products from Good Units
Breakdowns
Changeovers
Reduced Speed
Minor Stops
Startup Defects
Scrap/Rework
- Minimize Planned
- Eliminate Unplanned
- Separate Internal & External Tasks
- Change Internal to External
- Simplify remaining Internal tasks
- Equipment condition
- Raw material quality
- Training
- Breakdowns
< 5 min
- Automate Changeovers
- Reduce Variation
- Create Standards
- Eliminate defects
Big Losses
- Involve Operators
- Automate and collect accurate loss data
- Focus on the bottleneck
- Create real-time displays
Keys for
Success
- Assign loss reasons
- Capture event attributes (process area, machine name, product code, machine fault, shift, date, operator comments, etc.)
- Use the Six Big Losses to categorize data and prioritize improvement efforts
- Develop an Improvement Plan
- Execute the plan using tools appropriate for each loss type
- Evaluate the results and adjust the plan to continuously improve
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