Tag: Calculate OEE

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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OEE: Frequently Asked Questions

We added a new page to our site to address some of the more frequently asked questions (FAQ’s) we receive regarding OEE.  We trust you will find this information to be of interest as you move forward on your lean journey.  We always appreciate your feedback, so feel free to leave us a comment or send an e-mail directly to LeanExecution@gmail.com or Vergence.Consulting@gmail.com

We have had an incredibly busy summer as more companies are pursuing lean manufacturing practices to improve their performance.  OEE has certainly been one of the core topics of discussion.  We have found that more companies are placing a significant emphasis on Actual versus Planned performance.  It would seem that we are finally starting to realize that we can introduce a system of accountability that leads to improvements rather than reprimands.

Keep Your Data CLEAN

One of the debates we recently encountered was quantity versus time driven performance data when looking at OEE data.  The argument was made that employees can relate more readily to quantities than time.  We would challenge this as a matter of training and the terminology used by operations personnel when discussing performance.  We recommend using and maintaining a time based calculation for all OEE calculations.  Employees are more than aware of the value of their time and will make every effort to make sure that they get paid for their time served.

Why are we so sure of this?  Most direct labour personnel are paid an hourly rate.  Make one error on their pay or forget to pay their overtime and they will be standing in line at your office wondering why they didn’t get paid for the TIME they worked.  They will tell you – to the penny – what their pay should have been.  If you are paying a piece rate per part, you can be sure that the employees have already established how many parts per hour they need to produce to achieve their target hourly earnings.

As another point of interest and to maintain consistency throughout the company, be reminded that finance departments establish hourly Labour and Overhead rates to the job functions and machines respectively.  Quite frankly, the quantity of parts produced versus plan doesn’t really translate into money earned or lost.  However, one hour of lost labour and everyone can do the math – to the penny.

When your discussing performance – remember, time is the key.  We have worked in some shops where a machine is scheduled to run 25,000 parts per day while another runs a low volume product or sits idle 2 of the 5 days of the the week.  When it comes right down to the crunch for operations – how many hours did you earn and how many hours did you actually work.

Even after all this discussion we decided it may be an interesting exercise to demonstrate the differences between a model based on time versus one based (seemingly) only on Quantitative data.  We’ll create the spreadsheet and make it available to you when its done!

Remember to take advantage of our free spreadsheet templates.  Simply click on the free files in the sidebar or visit our free downloads page.

We trust you’re enjoying your summer.

Until Next Time – STAY Lean!

Vergence Business Associates

OEE Topics for 2009

We changed our theme!

Today was another day to do a little maintenance. We spent a little time revamping our look and feel. We hope you enjoy the changes and find our site a little easier to navigate.  We updated our Free Downloads page to present another easier and more direct venue to get your files instantly using Box.Net. If you’re already familiar with WordPress, you know how great this widget is. Downloads could never be faster or easier.

We also took some time to update some of our pages. We would suggest, however, that the best detailed content appears in the individual articles that we have posted.

Upcoming Topics for 2009

  1. Tracking OEE Improvements:  We have noticed an increase in the number of requests to discuss tracking OEE improvements.  We have been working on a few different approaches even for our own consulting practice and look forward to sharing some thoughts and ideas here.
  2. How OEE can improve your Cost of Non-Quality.  It’s more than yield.
  3. What OEE can do for your Inventory.  Improvements should be cascading to other areas of your operation – including the warehouse.
  4. Innovation – Defining your future with OEE
  5. OEE and Agile – Going beyond lean with OEE.
  6. Best Practices – OEE in real life, in real time

If you would like to suggest a topic for a future post, ask a question, or make a suggestion, please leave a comment or simply send an e-mail to LeanExecution@gmail.com or vergence.consulting@gmail.com.  We do appreciate your feedback.

Until Next Time – STAY lean!

Vergence Business Associates

We respect your privacy, your information will not be shared, sold, or distributed to any third parties.  We will only use your e-mail to communicate with you at your request.  You will not be subject to any advertising or marketing campaigns.

Cost Weighted OEE and other free OEE Spreadsheet Templates

OEE Spreadsheet Templates – One Click Closer:

As the days of summer are upon us, we thought it would be good idea to make it easier for you to access our free downloads so you can spend more time doing the things you want to do.  We have updated our site and we are pleased to offer you four ways to download our OEE spreadsheet templates:

  1. We added a new page titled “Downloads
  2. We also added a new Link List to the sidebar titled “Download Files”
  3. We made the FREE DOWNLOADS orange Box file a little larger and easier to read.
  4. We will include direct access links in the content of our posts.

Your OEE templates are literally a click away – saving you time and effort.

Cost Weighted OEE – Advanced OEE Template

We have received numerous requests for our “Cost Weighted OEE” template.  Many people are starting to realize that the OEE factors for availability, performance, and quality are not directly correlated.  Of course, we have also discussed our concerns in this regard on several occasions and will state again that OEE is not a stand alone metric.  As a vantage point metric, it can provide a valuable perspective on operations in real time, however, it is only one part of the overall equation.

Rex Gallaher wrote an excellent article titled “OEE Oxymoron; Are all factors truly equal?” that was published by ReliablePlant.com on February 18, 2009.  This article also conveys the premise that the OEE factors are not equal.  Understanding the financial impact of each of the OEE factors will assure that efforts and energy are focused on activities that will provide the greatest return on investment for your company.

To celebrate our site updates, we thought we would give you at least one more reason to see how our download venues work.  A copy of the Cost Weighted OEE Template is now available through all three of our download venues or you can Click HERE to get immediate access to the file.

For a detailed discussion of OEE and how it can (and should not) be used to identify opportunities to eliminate waste and reduce costs, click on one of the links below:

  1. OEE and Cost Control – Published in December, 2008
  2. 6 Things OEE is NOT! – Published in April, 2009
  3. Make or Break with OEE – Published in May, 2009

In light of the current economy, many companies have been forced to look inward to find “new” money.  OEE is one of the few lean metrics available that can help your organization to focus on the greatest opportunities with measurable returns.  We trust the templates and spreadsheet solutions that we offer here will help you in your quest.

For more information, click on the Categories section of the sidebar to search for other articles on our Blog that may be of interest to you.  They can provide significant insight into the many aspects of operations and OEE and may serve as part of your ongoing training efforts.

We appreciate your feedback.  Please feel free to leave a comment or send an e-mail with your suggestions for a future topic, comments, questions, or concerns to leanexecution@gmail.com or versalytics@gmail.com

Until next time – STAY lean!

OEE Training – Online

Getting Started

Online Training is more rampant now than ever.  If you want to learn about OEE and how to calculate it correctly then we have all the information you need right here.  Simply click on the categories of interest to you and research your specific topic or Click Here to get started.  This is the first article that got us started in November of 2008.  All of our online content is presently available at no charge.

Free Spreadsheet Templates

We offer several OEE Spreadhseet Templates that are available at no cost to our visitors and clients. Feel free to click on the “Free Downloads” template on the sidebar.  This is a new feature and trust that you will find this a much easier solution that provides immediate access to our documents.  If you can’t find what you are looking for, contact us by e-mail (leanexecution@gmail.com) or leave a comment with your suggestions for other templates that you would like to see available on our site.

Advanced Visitors

We trust that the content presented here is of interest to you as well.  We have provided many articles of interest related to OEE and Lean.  Simply review the categories and posts available or visit our pages for more information.  Our articles present detailed discussions and best practices applicable to the featured topic.

If you have any questions, comments, or suggestions for a future topic, simply leave a comment or send an e-mail to leanexecution@gmail.com or vergence.consulting@gmail.com.  We respect your privacy.  We will not share, disclose, sell, or distribute your e-mail or personal information with any third parties.  Your e-mail will only be used to contact you at your request.  You will not be subject to any advertising or marketing campaigns.  See our privacy policy for more details.

Until Next Time – STAY lean!

Vergence Business Associates

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!

Feel free to send us your feedback – We appreciate your questions, comments, and suggestions.

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How to Reduce Costs with OEE: Cost Control

OEE is a great metric to help identify where you may be incurring losses in your processes or operation.  As one of the goals of implementing a Lean strategy is to reduce costs, it only seems natural that we should be able to determine what processes to focus on that are driving the greatest losses.

From the example developed in our previous posts we determined that the OEE and related factors for our three processes were as follows:

Machine Availability Performance Quality OEE
A 92.97% 88.26% 97.77%  80.22%
B 96.04% 77.23% 94.44% 70.05%
C 95.16% 61.70% 95.20% 55.90%

Based on the OEE results, one would be inclined to take a look at Machine C as it has the lowest OEE.  Is this really the greatest opportunity?  The only way to answer the question is to understand what factors are driving costs and ultimately affecting profitability.

The performance factor for machine C is definitely pulling down the OEE for this process.  What would you think if the machine is 100% automated (no labour) and the cycle time, although it may be less than standard, is still meeting the takt time to meet customer demand?  Is there really a cost?  Of course there is, but the impact to your business may be minimal in terms of cost when compared to the other machines.

It is clear that we need to develop a model to understand what losses and ultimately costs are associated with each of the factors.  In turn, we will be able to better understand the overall OEE.

What costs do we consider?  We recommend keeping the model simple.  There are typically three cost components associated with any given process or product:  Material, Labour, and Overhead.  Burden is another term used for Overhead and we will use these terms interchangeably.

Our goal over the next few posts will be to develop a simple cost model for each process and, in turn, determine which one may be the process of choice for improvement.  For now, we will provide a general discussion of some of the potential cost considerations.

Improving quality typically yields the greatest return on investment because all of the cost elements stated above are impacted by the Quality factor.  Raw material, Labour, and Burden are all expended to produce a part scrap part.

The costs associated with Quality losses are further challenged when considering the number of parts that would have to be produced in order to recover these lost costs.  If you are lucky enough to enjoy a 10% profit margin (clear), then, at a minimum, 10 parts would have to be produced for every part scrapped.  Of course, more parts would have to be produced to recover other infrastructure costs incurred including documentation, record keeping, and scrapping of the actual parts.

Performance losses typically affect labour and overhead.  Labour losses are easy enough to understand.  If a machine is operator dependent, then we will have to pay a person to stand at the machine to run it.  If it is running slowly, more costs are incurred to cover the additional labour time.

In many cases, direct losses related to overhead are sometimes difficult to assess unless a truly activity based costing system is in place.  The reason for the complexity arises because some of the costs are “fixed”.  Because the equipment exists, expenses such as depreciation or property taxes are incurred whether or not the equipment or, for that matter, the plant is running.  The performance of the machine or any of the other factors for that matter won’t change this fact.

Availability then becomes somewhat more obscure when it comes to calculating hard costs.  If the labour can be redeployed to another process when a machine goes down, perhaps some of the labour losses can be avoided.  If not, then waiting for a machine to be repaired or material to be delivered is a real loss that should be addressed.

Intangible costs are also difficult to quantify but we should be aware of their existence.  The costs associated or related to poor OEE may include overtime, expedited freight, and infrastructure costs related to extra handling of material or management of non-conforming material (containment, extra inspection, rework, and scrap).  Although this is a relatively short list, it addresses the most obvious potential losses.  With a little more thought, the list could easily grow longer.

Other key metrics in your facility such as customer delivery or quality performance indicators may also point to problems that can be traced directly to poor OEE performance.  Although difficult to measure, a company’s competitive position is compromised when efficiencies are low and eventually the costs of poor performance make their way into the “burden” costs required to manage the operation.

While OEE is an effective metric for operations, on its own, it does not provide a direct indicator of real financial losses.  As Lean Practitioners we are challenged to provide an analysis that not only improves the metrics of the business but also translate into real financial improvements on the balance sheet and ultimately – the bottom line.  We would suggest that OEE is a time driven metric (asset time management strategy) versus our proposed COEE which is Finance or “Value” driven (cost management strategy).   We are presently developing a model that will allow your OEE data to be sensitized with cost data as demonstrated by the table below.

We have coined the term COEE or Cost of Overall Equipment Effectiveness.  Consider the following OEE results converted to Cost based drivers using standard costs as our baseline.  The sample data and spreadsheet used to calculate this data will be available as a download soon.  The overall spreadsheet is quite large and based on a fully detailed three shift operation.

Cost driven OEE model - Summary
Cost driven OEE model - Summary

Our OEE cost model clearly presents the real costs or “losses” incurred per part.  Our Weighted OEE Cost Model will change the way you view OEE data, enabling you to set priorities and identify real, quantifiable, opportunities for improvement.  The above snapshot represents the goal of our COEE project – a clean, clear, summary of the losses incurred correlated directly to your OEE index.  Another advantage is that the Availability, Performance, and Quality factors are recalculated based on cost and presents a realistic breakdown of losses for each of these factors from a financial perspective.  Our spreadsheet presents an advanced OEE example that will bring real value to your OEE implementation strategy.

NOTE:  The fully developed spreadsheet is available from our FREE Downloads page or from the FREE Downloads box on the sidebar.

A well implemented OEE strategy should become evident on the balance sheet through improved material utilization, reduced labour variance (straight and overtime reductions), reduced scrap costs, reduced rework costs, and other burden account reductions.

Take quick, effective, and efficient action to solve the problems having the greatest financial impact to your business.  Last but not least, don’t confuse activity with action.  Decisions are not actions and talking about a problem or even writing about it could be construed as activity.  Real actions produce real, measurable, results.

Change requires Change.  Profit is to business as oxygen is to humans – you need it to survive. 

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.  There are no hidden files, formulas, or macros and no obligations for the services provided here.

If you have any questions or comments, feel free to send an email to LeanExecution@gmail.com

Until Next Time – STAY Lean!

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