Tag: OEE .XLS files

Going DEEP with OEE

Does anyone actually look at their daily equipment availability? Instead of using TEEP that is typically based on calendarized availability, looking at the Daily Equipment Effectiveness Performance of your operation may provide some interesting insights.

Working overtime due to material or equipment availability occurs many times.  Unfortunately, we find that sometimes these very same machines are idle during the week.

A detailed explanation for calculating DEEP can be found in one of our earlier posts, “OEE, Downtime, and TEEP.”  Understanding machine utilization patterns may provide greater insight into the actual versus planned operating pattern of your process.

Just something to invoke some thoughts for your operation and to perhaps identify another opportunity to improve performance.

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!

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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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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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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