Category: Quality Factor

OEE For Manufacturing

We are often asked what companies (or types of companies) are using OEE as part of their daily operations.  While our focus has been primarily in the automotive industry, we are highly encouraged by the level of integration deployed in the Semiconductor Industry.  We have found an excellent article that describes how OEE among other metrics is being used to sustain and improve performance in the semiconductor industry.

Somehow it is not surprising to learn the semiconductor industry has established a high level of OEE integration in their operations.  Perhaps this is the reason why electronics continue to improve at such a rapid pace in both technology and price.

To get a better understanding of how the semiconductor industry has integrated OEE and other related metrics into their operational strategy, click here.

The article clearly presents a concise hierarchy of metrics (including OEE) typically used in operations and includes their interactions and dependencies.  The semiconductor industry serves as a great benchmark for OEE integration and how it is used as powerful tool to improve operations.

While we have reviewed some articles that describe OEE as an over rated metric, we believe that the proof of wisdom is in the result.  The semiconductor industry is exemplary in this regard.  It is clear that electronics industry “gets it”.

As we have mentioned in many of our previous posts, OEE should not be an isolated metric.  While it can be assessed and reviewed independently, it is important to understand the effect on the system and organization as a whole.

We appreciate your feedback.  Please feel free to leave us a comment or send us an e-mail with your suggestions to leanexecution@gmail.com

Until Next Time – STAY lean!

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How to Calculate the Quality Factor for OEE

How to correctly calculate the Quality Factor for OEE

Most people assume that the quality factor for Overall Equipment Effectiveness (OEE) is determined by simply calculating the yield of good parts from the total parts produced.  Unfortunately, this logic does not hold true when calculating the quality factor beyond the individual part or process.

We will show you how to correctly calculate the Quality factor and determine a truly weighted result that is consistent with the definition of Overall Equipment Effectiveness.  Although OEE itself does not have a unit of measure, it is based on the effective use of time.

The Quality Factor Defined

Although OEE itself is expressed as a percentage, all of the individual OEE factors are based on time.  Yes, even the quality factor:

The quality factor measures the percentage of time that was used to make or manufacture an acceptable quality product at rate or standard.

We have witnessed too many organizations that attempt to immediately convert the Quality Factor into a Cost of Non-Quality, Parts / Million (PPM), or other type of metric.  This is not the intent of the quality factor from an overall equipment effectiveness perspective.  Again, OEE measures effective use of time.

While it is not our intent to delve into a cost of non-quality discussion, we agree that understanding the cost drivers is in the best interests of the company to minimize losses.  This includes any investment that must be made to improve OEE.

We would also encourage you to download a copy of our Excel spreadsheets (see the BOX file on the sidebar).  There are no charges or fees for downloading these files and we request that these products remain available as such.  Now, let’s move on to the Quality Factor.

Free Download ->>> Click here to download a copy of the example developed in this post! <<<-Free Download

Where did the time go?

By definition, OEE is used to determine how effectively the time for a given machine, process, or resource is used: 

  • Availability:  Planned (Scheduled) versus Unplanned downtime
  • Performance:  Standard versus Actual cycle time
  • Quality:  Value Added versus Non-Value Added time

All of the OEE factors pertain to time.  From our definition above, the factors are independent of people (labour) required, parts produced, defective product, or the value of these items.  However, when we review many OEE templates, and more specifically the quality factor calculation, the time element is lost.

The true Quality Factor formula

The simple yield calculation works for a single process or part number but not for multiple machines or part numbers.  A simple example will demonstrate the correct way to calculate the Quality factor for a single part.  We will expand on this simple example as we go along.  Click here to download your free copy of the spreadsheet used in this post.

Note:  We are using the standard rate for the Quality time calculations as the Availability and Performance factors already account for downtime and cycle time losses respectively.  Quality is based on the pure standard rate or cycle time only.

EXAMPLE:  Machine A – Production Summary

Part Number

Rate / Minute

Total Produced

Defective

Quantity

Yield %
Quantity

1

2

800

10

98.75%

Totals

——-

800

10

98.75%

Averages

2

800

10

98.75%

As we can see from the table above, machine A produces part number 1 at a standard rate of 2 parts / minute.  A total of 800 parts are produced of which 10 are defective and scrapped.  The simple yield formula will correctly calculate the Quality factor as:

Quality Yield = (800 – 10) / 800 = 790 / 800 = 98.75%

From an OEE perspective, however, our interest is not how many parts were scrapped, but rather, how much machine or process time did we lose by making them.  From our example, 10 defective parts results in a loss of 5 minutes: 

Lost Time = 10 parts / (2 parts / minute) = 5 minutes

The quality factor actually tells us how effectively the time was used to make good or acceptable parts.  From our example, the time required to make ALL parts at the standard rate is 400 minutes (800 parts / 2 parts / minute = 400).  Our Quality factor can easily be calculated as follows: 

  • Value Added Time = Total Time – Non-Value Added Time
  • = 400 – 5
  • = 395 minutes

Total Time (All Parts) = 400 minutes

Quality Factor = Value Added Time / Total Time
                               = 395 / 400
                               = 98.75%

Although the results in this case are the same, the method is uniquely different.  Since this is based on a single machine, the cycle times are cancelled in the formula as shown below:

= (800 – 10) / 2 parts per minute / (800 / 2 parts per minute)

The YIELD pitfall revealed:

Our calculation method becomes relevant when we start looking at the production of different parts running through the same machine or process.  The easiest way to demonstrate this is by extending our first example.

Let’s assume we are also using machine A to produce two additional part numbers.  The production data is summarized in the table below as follows:

EXAMPLE:  Machine A – Production Summary

Part Number

Rate / Minute

Total Produced

Defective

Quantity

Yield %
Quantity

1

2

800

10

98.75%

2

8

1600

160

90.00%

3

1

800

20

97.50%

Totals

——-

3200

190

94.06%

Averages

4

1067

63

95.42%

If we calculate the Quality factor for machine A, the simple yield formula will provide a misleading result.  Note that we’ve provided the process yield factor for each line item part number as we have already determined that the ime factors cancel for individual parts.

The average Yield % from the table above is 95.42%.  We will demonstrate that this result is also incorrect.  Remember, we’re interested in the percent of total time used to make a quality product (also known as Value Added Time).

The real question is, “What is the overall Quality factor for machine A?”  The simple yield formula would suggest the following:

Simple Yield Quality Factor = (3200 – 190) / 3200 = 3010/ 3200 = 94.06%

This percentage is misleading and – as we will demonstrate – the WRONG result.

Calculating the True Weighted Quality Factor

Let’s take the table from above and expand on it to reflect our TIME based calculations.  We will calculate the time required to produce all parts (Total Time) and the time lost to produce defective parts (Lost Time).  Remember, these times are calculated at the standard cycle time or rate.  The resulting table appears below:

EXAMPLE:  Machine A – Production Summary

Part Number

Rate / Minute

Total Produced

Total Time

Defective

Quantity

Lost Time

Yield %
Time

1

2

800

400

10

5

98.75%

2

8

1600

200

160

20

90.00%

3

1

800

800

20

20

97.50%

Totals

——-

3200

1400

190

45

96.79%

Averages

4

1067

467

63

15

95.42%

 From this table, we can quickly calculate the true weighted quality factor as follows:

           Quality Factor = Value Added Time / Total Time
                               = (1400 – 45) / 1400
                               = 1355 / 1400
                               = 96.79 %

Putting it ALL together

From the discussion above, we have combined the results into the table below:

EXAMPLE:  Machine A – Production Summary

Part Number

Rate / Minute

Total Produced

Total

Time

Defective

Quantity

Lost Time

Yield %
Quantity

Yield %
Time

Delta

1

2

800

400

10

5

98.75%

98.75%

0.00%

2

8

1600

200

160

20

90.00%

90.00%

0.00%

3

1

800

800

20

20

97.50%

97.50%

0.00%

Totals

——-

3200

1400

190

45

94.06%

96.79%

2.72%

Averages

4

1067

467

63

15

95.42%

95.42%

0.00%

The true weighted quality factor can be found in the Yield % Time column (96.79%).  This result fits the true definition of Overall Equipment Effectiveness. 

The table also shows that the differences between the methods can lead to a significant variance between the results (96.79% – 94.06% = 2.72%): 

  • = 94.06% (Simple)
  • = 95.42% (Average)
  • = 96.79 % (Weighted)

We can quickly prove which answer is correct quite easily.  Referring to the table below, the only factor that resulted in the correct time calculations is the Yield Time % factor (96.79%).  The table shows that the true Value Added Time or Earned Time is 1355 minutes and the total time lost due to defective parts is 45 minutes.  Exactly what we expected to find based on our earlier calculations.

Quality Factor – Validation Table – All Times are in minutes

Method

“Yield %”

Total Time

Earned

Lost Time

Delta Time

Yield Quantity %

94.06%

1400

1316.9

83.1

38.1

Average Yield %

95.42%

1400

1335.8

64.2

19.2

Yield Time %

96.79%

1400

1355.0

45.0

0.0

What does all this mean in terms of time?  The results shown in this table clearly demonstrate that a seemingly small delta of 2.72% between the different methods of calculating the Quality Factor can be significant in terms of time.  The Delta time indicated in the table is the difference between the calculated lost time for Method and the actually calculated lost time of 45 minutes.

If this machine was actually scheduled to run 450 minutes per shift on 2 shifts the results would be even more dramatic over the course of a year.  Assuming the machine is loaded with the same part mix and there are 240 working days per year:

Annual Working Time = 240 * 450 * 2 = 216,000 minutes

The following table summarizes the results on an annualized basis: 

Quality Factor – Annualized Results – All Times are in minutes

Method

“Yield %”

Total Time

Earned

Lost Time

Delta Time

Yield Quantity %

94.06%

216,000

203,169.6

12,830.4

5896.8

Average Yield %

95.42%

216,000

206,107.2

9892.8

2959.2

Yield Time %

96.79%

216,000

209,066.4

6933.6

0.0

The “Yield Quantity %” method indicates the actual lost time that could be incurred annually is 12830.4 minutes (28.51 shifts).  Relative to our “Yield Time %” method, this is overstated by 5896.8 minutes, the equivalent of just over 13 shifts.  Similarly, the “Average Yield %” method indicates a total lost time of 9892.8 minutes (21.98 shifts).  Relative to our “Yield Time %” method, this is overstated by 2959.2 minutes or approximately 6.6 shifts.  This further exemplifies the need to understand the correct way to calculate the Quality Factor.

Let’s continue to re-affirm the validity of our calculation method.

Individually Weighted Quality Factors

We will now show you how to calculate the individually weighted quality factors for each part number or line item.  The weighted “time based” quality factor is calculated using the following formula for each line item part number: 

Weighted Line Item = (Value Added Time)
Total Time for All Parts

Where, Value Added Time = Total Time – Lost Time

 We have simplified the table from our example to show the time related factors only.  The table showing the time weighted quality factors from our example is as follows:

Part Number

Rate / Minute

Total Produced

Total Time

Defective

Quantity

Lost Time

Yield %
Time

Weighted % Yield Time

1

2

800

400

10

5

98.75%

28.21%

2

8

1600

200

160

20

90.00%

12.86%

3

1

800

800

20

20

97.50%

55.71%

Totals

 

3200

1400

190

45

96.79%

96.79%

Averages

4

1067

467

63

15

95.42%

 

As we can see from the table, the sum of the “Weighted % Yield Time” percentages is the same as the “Yield % Time”.  The time based formula is once again validated.  We will now take this table one step further to reveal where the real opportunities are to improve the Quality Factor and Overall Equipment Effectiveness.

Improving the Quality Factor

The Yield % or the Weighted Time % do not provide any real indication of the contribution of each part number to the overall weighted quality factor.  We can see from the table that part numbers 2 and 3 both resulted in 20 minutes of lost time compared to part number 1 where only 5 minutes were lost.

Since part numbers 2 and 3 resulted in an equivalent loss of time, we would expect that they would also result in an equal contribution to improve the Quality Factor.  To demonstrate this and to appreciate the real improvement opportunity, we added two more columns to our table as shown below – “Weighted % Process Time” and “Yield % Opportunity”:

Machine A – Weighted Quality Factor – EXAMPLE  

Part Number

Total Time

Weighted

% Process Time

Lost Time

Value Added Time

Yield %
Time

Weighted % Yield Time

Yield % Opportunity

1

400

28.57%

5

395

98.75%

28.21%

0.36%

2

200

14.29%

20

180

90.00%

12.86%

1.43%

3

800

57.14%

20

780

97.50%

55.71%

1.43%

Totals

1400

100.00%

45

1355

96.79%

96.79%

3.21%

Averages

467

33.33%

15

452

95.42%

32.26%

1.07%

The weighted process time was calculated by dividing the process time for each part number by the Total Time.  Once again, we can validate our weighted Quality Time by multiplying the “Weighted % Process Time” by the “Yield %” for each line item. 

To make sure we understand the calculations involved, let’s work out one of the line items in the table.  For Part Number 1, 

  • Weighted % Process Time = 400 / 1400 = 28.57%
  • (1)  Weighted % Yield Time = 28.57% * 98.75% = 28.21%
  • (2)  Weighted % Yield Time = (400 – 5) / 1400 = 28.21 %

Note that we showed two ways to demonstrate the Weighted % Yield Time to once again validate the quality factor calculation method.

The opportunity to improve the OEE for the three part numbers is the difference between the Weighted Process Time and the Weighted Yield Time.  For Part Number 1,

            Improvement = 28.57% – 28.21% = 0.36%

Similarly, the improvements for part numbers 2 and 3 are as follows: 

  • Improvement Part Number 2 = 14.29% – 12.86% = 1.43%
  • Improvement Part Number 3 = 57.14% – 55.71% = 1.43%

Three Key Observations

  1. First, the results of the calculations are consistent the actual observed down time.
  2. Second, although the yields for part numbers 2 and 3 are significantly different, each has the same NET impact to the final OEE result.
  3. Third, when add the total “Yield % Opportunity” (3.21%) for all three part numbers to the total “Weighted % Yield Time” (96.79%), the result is 100%.

This last calculation once again demonstrates that the Quality Factor calculation presented here is consistent with the true definition of OEE.

The formula for the Quality Factor is:

Total Time to Produce Good Parts @ Rate / Total Time to Produce ALL Parts @ Rate

One Final Proof

Our method will produce a result that is consistent with the formula OEE = A * P * Q.  Using our example, it is clear that if Availability and Performance are both 100% and the Quality Factor is 96.79%, the final OEE for all parts will also be 96.79%.

Consistent with the definition of OEE, using our example, 96.79% of 1400 minutes is 1355 minutes.  This is the time that was used to make good or acceptable quality parts.  Similarly then, the time lost making all defective parts is 45 minutes (1400 – 1355 = 45).

The Impact to Operations

OEE is typically used by the Operations team for capacity planning, labour planning, and to determine how much time to schedule for a given resource to produce parts.  The above examples clearly demonstrate that even a small delta can have significant capacity, labour, and scheduling implications.  From this perspective it also becomes a relatively simple task to determine the direct labour costs associated with the production of defective parts.

Purchasing, Materials, Scheduling (Lead Times), Inventory (Stock), Finance, and Quality are all affected by inaccurate data and, in this case, OEE calculation errors.  Of course these errors are not just limited to the Quality Factor itself.

There are other significant losses and costs related to quality as well.  It is not our intent to pursue a discussion on the cost of non-quality as we recognize there are many other factors (internal and external) that must be considered to truly understand the real cost of non-quality for activities such as sorting, inspection, scrap (material losses), rework, re-order, machine time, and administration.

In the real world, someone may just be preparing a plan to improve the Quality of parts running on Machine A to reduce excessive labour and material costs.  We can only wonder what method they used to calculate the “savings”.  Inevitably, many companies approve the project and the funding only to realize the savings fell well short of expectations or will never materialize at all.

In Closing

We would contend that the differences in the calculation method presented here and those found elsewhere are significant.  In our example case, the difference is 2.72%.  We demonstrated that this can be significant when annualized over time.  Similarly, the opportunity for improvements using our method is clear and concise.

Now when someone asks you how to calculate the Quality Factor, you can confidently show them how and tell them why.

The example used in this post can also be downloaded from our BOX File on the sidebar or CLICK HERE.  This is offered at no charge and of course will make it easier for you to use for your own applications.

Thank you for visiting – Until Next Time – STAY lean!

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Problem Solving with OEE – Measuring Success

OEE in Perspective

As mentioned in our previous posts, OEE is a terrific metric for measuring and monitoring ongoing performance in your operation.  However, like many metrics, it can become the focus rather than the gage of performance it is intended to be.

The objective of measuring OEE is to identify opportunities where improvements can be made or to determine whether the changes to your process provided the results you were seeking to achieve.  Lean organizations predict performance expectations and document the reasons to support the anticipated results .  The measurement system used to monitor performance serves as a gauge to determine whether the reasons for the actual outcomes were valid.  A “miss” to target indicates that something is wrong with the reasoning – whether the result is positive or negative.

Lean organizations are learning continually and recognize the need to understand why and how processes work.  Predicting results with supported documentation verifies the level of understanding of the process itself.  Failing to predict the result is an indicator that the process is not yet fully understood.

Problem Solving with OEE

Improvement strategies that are driven by OEE should cause the focus to shift to specific elements or areas in your operation such as reduction in tool change-over or setup time, improved material handling strategies, or quality improvement initiatives.  Focusing on the basic tenets of Lean will ultimately lead to improvements in OEE.  See the process in operation (first-hand), identify opportunities for improvement, immediately resolve,  implement and document corrective actions, then share the knowledge with the team and the company.

Understanding and Managing Variance:

OEE data is subject to variation like any other process in your operation.  What are the sources of variation?  If there is a constant effort to improve performance, then you would expect to see positive performance trends.  However, monitoring OEE and attempting to maintain positive performance trends can be a real challenge if the variances are left unchecked.

Availability

What if change-over times or setup times have been dramatically reduced?  Rather than setting a job to run once a week, it has now been decided to run it daily (five times per week).  What if the total downtime was the same to make the same number of parts over the same period of time?  Did we make an improvement?

The availability factor may very well be the same.  We would suggest that, yes, a signficant improvement was made.  While the OEE may remain the same, the inventory turns may increase substantially and certainly the inventory on hand could be converted into sales much more readily.  So, the improvement will ultimately be measured by a different metric.

Performance

Cycle time reductions are typically used to demonstrate improvements in the reported OEE.  In some cases, methods have been changed to improve the throughput of the process, in other cases the process was never optimized from the start.  In other instances, parts are run on a different and faster machine resulting in higher rates of production.  The latter case does not necessarily mean the OEE has improved since the base line used to measure it has changed.

Quality

Another example pertains to manual operations ultimately controlled through human effort.  The standard cycle time for calculating OEE is based on one operator running the machine.  In an effort to improve productivity, a second operator is added.  The performance factor of the operation may improve, however, the conditions have changed.  The perceived OEE improvement may not be an improvement at all.  Another metric such as Labour Variance or Efficiency may actually show a decline.

Another perceived improvement pertains to Quality.  Hopefully there aren’t to many examples like this one – changing the acceptance criteria to allow more parts to pass as acceptable, fit for function, or saleable product (although it is possible that the original standards were too high).

Standards

Changing standards is not the same as changing the process.  Consider another more obvious example pertaining to availability.  Assume the change over time for a process is 3o minutes and the total planned production time is 1 hour (including change over time).  For simplicity of the calculation no other downtime is assumed.  The availability in this case is 50% ((60 – 30) / 60).

To “improve” the availability we could have run for another hour and the resulting availability would be 75% (120 – 30) / 120.  The availability will show an improvement but the change-over process itself has not changed.  This is clearly an example of time management, perhaps even inventory control, not process change.

This last example also demonstrates why comparing shifts may be compromised when using OEE as a stand-alone metric.  What if one shift completed the setup in 20 minutes and could only run for 30 minutes before the shift was over (Availability = 60%).  The next shift comes in and runs for 8 hours without incident or down time (Availability = 100%).  Which shift really did a better job all other factors being equal?

Caution

When working with OEE, be careful how the results are used and certainly consider how the results could be compromised if the culture has not adopted the real meaning of Lean Thinking.  The metric is there to help you improve your operation – not figure out ways to beat the system!

FREE Downloads

We are currently offering our Excel OEE Spreadsheet Templates and example files at no charge.  You can download our files from the ORANGE BOX on the sidebar titled “FREE DOWNLOADS” or click on the FREE Downloads Page.  These files can be used as is and can be easily modified to suit many different manufacturing processes.  There are no hidden files, formulas, or macros and no obligations for the services provided here.

Please forward your questions, comments, or suggestions to LeanExecution@gmail.com.  To request our services for a specific project, please send your inquiries to Vergence.Consulting@gmail.com.

We welcome your feedback and thank you for visiting.

Until Next Time – STAY Lean!

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OEE for Multiple Parts – Single Machine (Multipart Processes)

How to Calculate OEE for Single Machine and Multiple Parts.

Flexible manufacturing provides the advantage of producing many different parts on the same piece of equipment.  The same is true for processes such as stamping presses, molding machines, or machining operations.

The first question most often asked is, “How do we calculate OEE for a piece of equipment that is capable of manufacturing multiple parts?”  The overall OEE for a stamping press, molding machine, machining process, or other “multipart” process is easily calculated using the same formulas presented in our previous posts “How to Calculate OEE” and “Practical OEE“.

We presented three machines running at various rates and producing unique products.  We demonstrated how to calculate the OEE for each part individually and for all parts collectively.  The machines A, B, and C could very easily be parts A, B, and C running on one machine.  The application of the OEE formulas presented for these three machines is the same for multiple parts running on the same machine.

We have prepared two Excel spreadsheets that demonstrate how to calculate OEE for a single machine that produces multiple parts.  We have also created a separate Excel spreadsheet that will show you how to calculate OEE for Multiple Departments and Multiple Machines running Multiple Parts.

Calculating OEE for any period of time, department, or group of equipment is a simple task.  With the understanding that OEE measures how effectively Net Available Time is used to produce good parts at the ideal rate, the formula for any OEE calculation follows:

OEE (Any Category) = Total SUM of IDEAL Time / Total SUM of NET Available Time

Once this basic premise for OEE calculations is clearly understood, any combination of OEE summaries can be prepared including OEE summaries by Shift, Operator, Manager, Division, Process, and Process Type.

FREE Downloads 

We are currently offering our Excel OEE Spreadsheet Templates and example files at no charge.  You can download our files from the ORANGE BOX on the sidebar titled “FREE DOWNLOADS” or click on the FREE Downloads Page.  These files can be used as is and can be easily modified to suit many different manufacturing processes.  There are no hidden files, formulas, or macros and no obligations for the services provided here.

Multipart OEE – Confronting the Challenges

Most manufacturing environments are challenged with the task of minimizing inventories requiring more frequent change-overs or setups.  By far, the greatest challenge of multipart equipment is managing the change-over process and is usually reflected in the OEE Availability factor.

We recommend including setup or change-over time as part of the unplanned downtime calculation.  Then, by definition, one method to improve Availability is to reduce change-over or setup time.  Reductions in change-over time will also be reflected by improved Availability.  The Availability factor is now a useful metric for tracking improvements.

According to our definition, change-over time or setup time is measured from the end of the current production run (“the last good part made”) to the start of the next production run (“first good part produced”).  We have worked with some manufacturers that decided to do change-overs on the off shift so that they could avoid the down time penalty.  They clearly didn’t get the point – deferring the time when the change-over is performed doesn’t change the time required to perform it.

Several programs such as SMED (single minute exchange of dies) are available and, when coupled with best practices for quick die change (QDC) or quick tool change techniques, can greatly reduce the time lost during your tool change events.

We will consider posting best practices for SMED or QDC and would welcome any reader comments in this area.

We always welcome your feedback and comments.  Feel free to send us your questions or comments to leanexecution@gmail.com

Until Next Time – STAY Lean!

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Practical OEE – How To Calculate and Use Weighted OEE

We have presented the methods of calculating OEE for a process and also demonstrated how weighted OEE is calculated for multiple processes.  Our next challenge is to determine how this data can be used to make sure we are targeting the right processes for improvement.

Over the next few posts, we will show you how to calculate weighted OEE factors for each process.  This weighting will include calculations for each of the factors as well as the overall OEE.  The results of the individual weighted factors may well serve to point us in the right direction.

Calculating the weighted OEE and it’s factors is not just a simple calculation of averages as you can see from our previously calculated data.  It is easy to fall into this trap and it is also for this very reason that we have put forth the effort to show you how it should be done.

We highly recommend reviewing the posts presented over the past few days to refresh yourself with the ongoing development of our key Lean metric:  OEE.

Free Excel Downloads:

We have created a number of Excel spreadsheets that are immediately available for download from our FREE Downloads page or from the Free Downloads widget on the side bar.  These spreadsheets can be modified as required for your application.

Calculating Weighted OEE

We will continue to use the examples presented in our previous posts to develop our OEE metric.  We will start with the overall OEE percentage to help you understand the weighting concept applied here.

The basic formula to determine the weighted OEE for each individual process follows:

Weighted OEE = Process OEE * (Net Available Time / Total Net Available Time)

The OEE data taken from our previous examples is summarized in the table below:

  1. Machine A:  OEE = 80.22%, Net Available Time = 455 minutes
  2. Machine B:  OEE = 70.05%, Net Available Time = 455 minutes
  3. Machine C:  OEE = 55.90%, Net Available Time = 455 minutes

The total Net Available Time for all machines = 455 * 3 = 1365 minutes.  Now we can calculate our “weighted OEE” for each machine as shown:

  1. Machine A:  Weighted OEE = 80.22% * (455 / 1365) = 26.74%
  2. Machine B:  Weighted OEE = 70.05% * (455 / 1365) = 23.35%
  3. Machine C:  Weighted OEE = 55.90% * (455 / 1365) = 18.63%

Adding the individual weighted OEE together for each machine, we find the total is 68.72%.  Note that this matches the total OEE calculation from our previous post.

Warning:  Don’t fall into the trap of assuming that the same result could have been achieved by simply averaging the three OEE numbers.  The results in the calculation appear to be a simple average, however, this is misleading because you will also note that the Net Available Time and Total Net Available Time ratio is the same for each machine.  This is not always the case.  Many times, a machine may run for only half a shift or a few hours at a time.  This may significantly change the weighted OEE for a given machine and the result is not a simple arithmetic average.

Our next step will be to calculate the individual weighted factors for Availability, Performance, and Quality for each machine.  These calculations will readily demonstrate that it’s not a simple averaging process.

Weighted Availability Factor:

The basic formula to determine the weighted Availability Factor for each individual process follows:

Weighted Availability = Availability % * (Net Available Time / Total Net Available Time)

You will note that the weighting factor for availability is the same as the weighting factor for the overall OEE weight.  The Availability data taken from our previous examples is summarized in the table below:

  1. Machine A:  Availability = 92.97%, Net Available Time = 455 minutes
  2. Machine B:  Availability = 96.04%, Net Available Time = 455 minutes
  3. Machine C:  Availability = 95.16%, Net Available Time = 455 minutes

The total Net Available Time for all machines = 455 * 3 = 1365 minutes.  Now we can calculate our “weighted availability” for each machine as shown:

  1. Machine A:  Weighted Availability = 92.97% * (455 / 1365) = 30.99%
  2. Machine B:  Weighted Availability = 96.04% * (455 / 1365) = 32.01%
  3. Machine C:  Weighted Availability = 95.16% * (455 / 1365) = 31.72%

Adding the individual weighted Availability factors together for each machine, we find the total is 94.72%.  Note that this matches the total weighted Availability calculation from our previous post.

 Warning:  because all process have the same Net Available Time you may be thinking that this seems like a lot of work to simply get an average of the numbers.  More on this later when we take a look at Performance and Quality.

Weighted Performance Factor:

The basic formula to determine the weighted Performance Factor for each individual process follows:

Weighted Performance = Performance % * (Net Operating Time / Total Net Operating Time)

You will note that the weighting factor for performance is different.  This is because performance is a measure of how well the operating time was used to make parts.  The Performance data taken from our previous examples is summarized in the table below:

  1. Machine A:  performance = 88.26%, Net Operating Time = 423 minutes
  2. Machine B:  Performance = 77.23%, Net Operating Time = 437 minutes
  3. Machine C:  Performance = 61.70%, Net Operating Time = 433 minutes

The total Net Operating Time for all machines = 1293 minutes.  Now we can calculate our “weighted performance” for each machine as shown:

  1. Machine A:  Weighted Performance = 88.26% * (423 / 1293) = 28.87%
  2. Machine B:  Weighted Performance = 77.23% * (437 / 1293) = 26.10%
  3. Machine C:  Weighted Performance = 61.70% * (433 / 1293) = 20.66%

Adding the individual weighted Performance factors together for each machine, we find the total is 75.63%.  Note that this matches the total weighted Performance calculation from our previous post.

 Finally:  You will note that the Weighted Performance is NOT the same as the Arithmetic Average!  The arithmetic average in this case is 75.73%.  Although it doesn’t appear to be a significant difference, you wil see that it can be.

Weighted Quality Factor:

The basic formula to determine the weighted Quality Factor for each individual process follows:

Weighted Quality = Quality % * (Ideal Operating Time / Total Ideal Operating Time)

You will note that the weighting factor for quality is different.  This is because quality is a measure of how well the ideal operating time was used to make good (saleable) parts.  The Quality data taken from our previous examples is summarized in the table below:

  1. Machine A:  Quality = 97.77%, Ideal Operating Time = 373.33 minutes
  2. Machine B:  Quality = 94.44%, Ideal Operating Time = 337.50 minutes
  3. Machine C:  Quality = 95.20%, Ideal Operating Time = 267.17 minutes

The total Ideal Operating Time (to make all parts) for all machines = 978 minutes.  Now we can calculate our “weighted quality” for each machine as shown:

  1. Machine A:  Weighted Quality = 97.77% * (373.33 / 978) = 37.32%
  2. Machine B:  Weighted Quality = 94.44% * (337.50 / 978) = 32.59%
  3. Machine C:  Weighted Quality = 95.20% * (267.17 / 978) = 26.01%

Adding the individual weighted Quality factors together for each machine, we find the total is 95.92% as expected.  Note that this matches the total weighted Quality calculation from our previous post.

 Finally:  You will note that the Weighted Quality is NOT the same as the Arithmetic Average! 

Remember to get your free downloads.  We have created a number of Excel spreadsheets that are immediately available for download from our FREE Downloads page or from the Free Downloads widget on the side bar.  These spreadsheets can be modified as required for your application.

Until Next Time – STAY Lean!

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Weighted OEE: How To Calculate Total Plant OEE

In this post we will present a simple method to calculate a truly weighted OEE, including weighted factors Availability, Performance, and Quality.

The QUICK weighted OEE method:

Recalling our original definition of OEE, we are measuring how effectively our planned production time (net available time) is used to make a quality (saleable) product.  The weighted OEE then is the total time required to make a quality product divided by the total net available time.

From our examples in the “Calculating OEE” post, the following table summarizes the time required to produce quality products ONLY for machines A, B, and C:

  1. Machine A:  365 minutes
  2. Machine B:  318.75 minutes
  3. Machine C:  254.34 minutes

The total time to produce good quality (saleable) products is 938.09 minutes.

The total net available time for the three machines is 1365 minutes (3 * 455 minutes). 

The total weighted OEE for the 3 machines = 938.09 / 1365 = 68.72%

Calculating the Weighted Factors:

A similar process to the one described above can be applied to the individual factors.  It stands to reason that when the individual factors are multiplied together that we should get the same result.  We will use this to check our answer.

Weighted Availability:

Availability measures machine uptime efficiency.  The definition applied to an individual process also applies to the total of all the machines.  Availability is calculated using the formula:

Availability:  Net Operating Time / Net Available Time

From our examples in the “Calculating OEE” post, the following table summarizes the Net Operating Times for machines A, B, and C:

  1. Machine A:  423 minutes
  2. Machine B:  437 minutes
  3. Machine C:  433 minutes

The total Net Operating Time = 1293 minutes.

The total Net Available Time for the three machines is 1365 minutes (3 * 455 minutes). 

The weighted AVAILABILITY for the 3 machines = 1293 / 1365 = 94.73%

Weighted Performance:

Performance measures machine operating time efficiency when compared to the “ideal” cycle or operating time.  The definition applied to an individual process also applies to the total of all the machines.  Performance is calculated using the formula:

Performance:  Ideal Operating Time / Net Operating Time

From our examples in the “Calculating OEE” post, the following table summarizes the Ideal Operating Times for machines A, B, and C:

  1. Machine A:  373.33 minutes
  2. Machine B:  337.50 minutes
  3. Machine C:  267.17 minutes

The total Ideal Operating Time to produce ALL parts = 978 minutes.

The total Net Operating Time for the three machines is 1293 minutes (See Availability Calculations Above). 

The weighted PERFORMANCE for the 3 machines = 978 / 1293 = 75.64%

Weighted Quality:

Quality measures how efficiently the “ideal” operating time is used to produce quality (saleable) products.  Again, the definition applied to an individual process also applies to the total of all the machines.  Quality is calculated using the formula:

Quality:  Ideal Operating Time to Make Quality Parts / Ideal Operating Time

From our examples in the “Calculating OEE” post, the following table summarizes the Ideal Operating Time to produce Quality Parts ONLY for machines A, B, and C:

  1. Machine A:  365.00 minutes
  2. Machine B:  318.75 minutes
  3. Machine C:  254.34 minutes

The total Ideal Operating Time for Good Parts = 938.09 minutes.

The total Ideal Operating Time to produce ALL parts for the three machines is 978 minutes (See Performance Calculations Above). 

The weighted Quality for the 3 machines = 938.09 / 978.0 = 95.92%

Weighted OEE cross check:

Let’s compare the results.  From the calculations above, the results are summarized as follows:

  1. Weighted Availability:  94.73%
  2. Weighted Performance:  75.64%
  3. Weighted Quality:  95.92%

Now, we multiply the individual weighted OEE factors together:

OEE = 94.73% * 75.64% * 95.92% = 68.73%

You will see the result is the same as the Quick check introduced at the start of this post.

In our next post we will show you how to calculate the weighted factors for each individual process and introduce yet another way to confirm the weighted OEE calculation.

We have created a number of Excel spreadsheets that are immediately available for download from our FREE Downloads page or from the Free Downloads widget on the side bar.  These spreadsheets can be modified as required for your application.

If you have any questions, comments, concerns, or suggestions for a future topic, please forward them by e-mail to leanexecution@gmail.com  We look forward to hearing from you and trust this information will get you going.

Until Next Time, STAY Lean!

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