Tag: Integrating OEE

OEE, Labour, and Inventory

Almost every manufacturing facility has a method or means to measure labour efficiency.  Some of these methods may include Earned versus Actual hours or perhaps they are financially driven metrics such as “Labour as a Percent of Sales” or as “Labour Variance to Plan”.  As we have learned all too well through the latest economic downturn, organizations are quite adept at using these metrics to flex direct labour levels based on current demand.  This suggests that almost every company has access to at least a  financial model of some form that can be used to represent “ideal” work force requirements based on sales.

It is not our intent to discuss how these models are created, however, I can only trust that the financial model is based on a realistic assessment of current process capabilities and resources required to support the product mix represented by the sales forecast.  At a minimum, the assessment should include the following standards and known variances for each process:  Material, Labour, and Rate.  You may recognize these standards as they form the basis of our OEE cost model that we have discussed in detail and offer in our Free downloads page.

Analyzing the Data

Many companies use both Labour Efficiency and Overall Equipment Effectiveness to measure the performance of their manufacturing operations.  We would also expect a strong correlation to exist between these two metrics as the basis for their measurement is fundamentally common.  As you may have already observed in your own operations, this is not always the case in the real world.  The disconnect between these two metrics is a strong indicator that yet another opportunity for improvement may exist.

For example, it is not uncommon to see operations where OEE is 60% – 70% while labour efficiencies are reported to be 95% or better.  How is this possible?  The simple answer is that labour is redirected to perform other work while a machine is down or, in extreme cases, the work force is sent home.  In both cases, OEE continues to suffer while labour is managed to minimize the immediate financial impact of the downtime.

Set up and / or change over may be one of the reasons for down time and another reason why there is a perceived discrepancy between labour efficiency and overall equipment effectiveness.  Some companies employee personnnel specifically trained to perform these tasks and are classified as indirect labour.

Redirecting labour to operate other machines presents its own unique set of problems and is typically frowned upon in lean organizations.  Companies that follow this practice must ensure that adequate controls are in place to prevent excess inventories from building over time.  I reluctantly concede to the practice of “redeployment during downtime” if it is indeed being managed.

Some would argue that the alternate work is being managed because the schedule actually includes a backup job if a given machine goes down.  If we probe deep enough, we may be surprised to learn that some of these backup jobs are actually “never” scheduled because the primary scheduled machines “always” provide ample downtime to finish orders of “unscheduled” backup work.  As such, we must be fully aware of the potential to create the “hidden factory” that runs when the real one isn’t.

Pitfalls of Redirected Labour

This practice easily becomes a learned behavior and tends to place more emphasis on preserving labour efficiency than actually increasing the sense of urgency required to solve the real problem.  In all too many cases the real problem is never solved.

Too many opportunities to improve operations are missed because many planners have learned to compensate for processes that continually fail to perform.  Experience shows that production schedules evolve over time to include backup jobs and alternate machines that ultimately serve as a mask to keep real problems from surfacing.  From a labour and OEE perspective, everything appears to be normal.

Redirecting labour to compensate for Process deficiencies may give rise to excess inventory.  “Increased inventory” is an extremely high price to pay for the sake of perceived efficiency in the short-term.  Higher inventory has an immediate negative impact to cash flow in the short-term as real money is now represented by parts in inventory until consumed or sold.  Additional penalties of inventory include carrying and handling costs that are also worthy of consideration.

Three Metrics – Working Together

You will note that we deliberately used the term labour efficiency throughout our discussion and presents an opportunity to demonstrate that efficiency and effectiveness are not synonymous.  Efficiency measures our ability to produce parts at rate while effectiveness measures our ability to produce the right quantity of quality parts at the right time.

Overall Equipment Effectiveness, Labour Efficiency, and Inventory are truly complementary metrics that can be used to determine how effectively we are managing our resources:  Human, Equipment, Material, and Time.  Our mission is to safely produce a quality part at rate, delivered on time and in full, at the lowest possible cost.  Analyzing the data derived through our metrics is the key to understanding where opportunities persist.  Once identified, we can effectively solve the problems and implement corrective actions accordingly.

Until Next Time – STAY lean!

Vergence Analytics

Advertisements

OEE: Planned Downtime and Availability

Injection Molding Press
Image via Wikipedia

As a core metric, Overall Equipment Effectiveness or OEE has been adopted by many companies to improve operations and optimize the capacity of existing equipment.  Having completed several on site assessments over the past few months we have learned that almost all organizations are measuring performance and quality in real-time, however, the availability component of OEE is still a mystery and often misunderstood – specifically with regard to Set Up or Tool Changes.

We encourage you to review the detailed discussion of down time in our original posts “Calculating OEE – The Real OEE Formula With Examples” and “OEE, Down time, and TEEP” where we also present methods to calculate both OEE and TEEP.  The formula for Overall Equipment Effectiveness is simply stated as the product of three (3) elements:  Availability, Performance, and Quality.  Of these elements, availability presents the greatest opportunity for improvement.  This is certainly true for processes such as metal stamping, tube forming, and injection molding, to name a few, where tool changes are required to switch from one product or process to another.

Switch Time

Set up or change over time is defined as the amount of time required to change over the process from the last part produced to the first good part off the next process.  We have learned that confusion exists as to whether this is actually planned down time as it is an event that is known to occur and is absolutely required if we are going to make more than one product in a given machine.

Planned down time is not included in the Availability calculation.  As such, if change over time is considered as a planned event, the perceived availability would inherently improve as it would be excluded from the calculation.  Of course, the higher availability is just an illusion as the lost time was still incurred and the machine was not available to run production.

If we could change a process at the flip of a switch, set up time would be a non-issue and we could spend our time focusing on other improvement initiatives.  While some processes do require extensive change over time, there is always room for improvements.  This is best exemplified by the metal stamping industry where die changes literally went from Hours to Minutes.

To remain competitive and to increase the available capacity, many companies quickly adopted SMED (Single Minute Exchange of Dies) initiatives after recognizing that significant production capacity is being lost due to extensive change over times.  Overtime through extended shifts and capital for new equipment is also reduced as capacity utilization improves.

Significantly reduced inventories can also be realized as product change overs become less of a concern and also provide greater flexibility to accommodate changes in customer demand in real-time.  Significantly increased Inventory Turns will also be realized in conjunction with net available cash from operations.

Redefining Down Time

The return on investment for Quick Tool Change technologies is relatively short and the benefits are real and tangible as demonstrated through the metrics mentioned above.  Rather than attempt to categorize down time as either planned or unplanned, consider whether the activity being performed is impeding the normal production process or can be considered as an activity required for continuing production.

We prefer to classify down time as either direct or indirect.  Any down time such as Set Up, Material Changes, Equipment Breakdowns, Tooling Adjustments, or other activity that impedes production is considered DIRECT down time.  Indirect down time applies to events such as Preventive Maintenance, Company Meetings, or Scheduled IDLE Time.  These events are indeed PLANNED events where the machine or process is NOT scheduled to run.

Redefine the Objective

Set up or change over time is often the subject of much heated debate and tends to create more discussion than is necessary.  The reason for this is simple.  Corporate objectives are driven by metrics that measure performance to achieve a specific goal.

Unfortunately, in the latter case, the objectives are translated into personal performance concerns for those involved in the improvement process.  Rather than making real improvements, the tendency is to rationalize the current performance levels and to look for ways to revise the definition that creates the perception of poor performance. Since availability does not include planned down time, many attempts are made to exclude certain down time events, such as set up time, to create a better OEE result than was actually achieved.

Attempts to rationalize poor performance inhibits our ability to identify opportunities for improvement.  From a similar perspective, we should also be prudent with. and cognizant of, the time allotted for “planned” events.

It is for this reason that some companies have resorted to measuring TEEP based on a 24 hour day.  In many respects, TEEP eliminates all uncertainty with regard to availability since you are measured on the ability to produce a quality part at rate.  As such, our mission is simple – “To Safely Produce a Quality Part At Rate, Delivered On Time and In Full”.  Any activity that detracts from achieving or exceeding this mission is waste.

Remember to get your OEE spreadsheets at no charge from our Free Downloads Page or Free Downloads Box in the sidebar.  They can be easily and readily customized for your specific process or application.

Please feel free to send your comments, suggestions, or questions to Support@VergenceAnalytics.com

Until Next Time – STAY lean!

Vergence AnalyticsVergence Analytics

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!

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!

OEE for Batch Processes

Coke being pushed into a quenching car, Hanna ...
Image via Wikipedia

We recently received an e-mail regarding OEE calculations for batch processes and more specifically the effect on down stream equipment that is directly dependent (perhaps integrated) on the batch process.  While the inquiry was specifically related to the printing industry, batch processing is found throughout manufacturing. Our more recent experiences pertain to heat treating operations where parts are loaded into a stationary fixed-load oven as opposed to a continuous belt process.

Batch processing will inherently cause directly integrated downstream equipment (such as cooling, quenching, or coating processes) to be idle. In many cases it doesn’t make sense to measure the OEE of each co-dependent piece of equipment that are part of the same line or process. Unless there is a strong case otherwise, it may be better to de-integrate or de-couple subsequent downstream processes.

Batch processing presents a myriad of challenges for line balancing, batch sizes, and capacity management in general.  We presented two articles in April 2009 that addressed the topic of  where OEE should be measured.  Click here for Part I or Click  here for Part II.

Scheduling Concerns – Theory of Constraints

Ideally, we want to measure OEE at the bottleneck operation.  When we apply the Theory of Constraints to our production process, we can assure that the flow of material is optimized through the whole system.  The key of course is to make sure that we have correctly identified the bottleneck operation.  In many cases this is the batch process.

While we are often challenged to balance our production operations, the real goal is to create a schedule that can be driven by demand.  Rather than build excess inventories of parts that aren’t required, we want to be able to synchronize our operations to produce on demand and as required to keep the bottleneck operation running.  Build only what is necessary:  the right part, the right quantity, at the right time.

Through my own experience, I have realized the greatest successes using the Theory of Constraints to establish our material flows and production scheduling strategy for batch processes.  Although an in-depth discussion is beyond the scope of this article, I highly recommend reading the following books that convey the concepts and application through a well written and uniquely entertaining style:

  1. In his book “The Goal“, Dr. Eliyahu A. Goldratt presents a unique story of a troubled plant and the steps they took to turn the operation around.
  2. Another book titled “Velocity“, from the AGI-Goldratt Institute and Jeff Cox also demonstrates how the Theory of Constraints and Lean Six Sigma can work together to bring operations to all new level of performance, efficiency, and effectiveness.

I am fond of the “fable” based story line presented by these books as it is allows you to create an image of the operation in your own mind while maintaining an objective view.  The analogies and references used in these books also serve as excellent instruction aids that can be used when teaching your own teams how the Theory of Constraints work.  We can quickly realize that the companies presented in either of the above books are not much different from our own.  As such, we are quickly pulled into the story to see what happens and how the journey unfolds as the story unfolds.

Please leave your comments regarding this or other topics.  We appreciate your feedback.  Also, remember to get your free OEE spreadsheets.  See our free downloads page or click on the file you want from the “Orange” box file on the sidebar.

Until Next Time – STAY lean!

Vergence AnalyticsVergence Analytics

Benchmarking OEE

Benchmarking Systems:

We have learned that an industry standard or definition for Overall Equipment Effectiveness (OEE) has been adopted by the Semi Conductor Industry and also confirms our approach to calculating and using OEE and other related metrics.

The SEMI standards of interest are as follows:

  • SEMI E10:  Definition and Measurement of Equipment Reliability, Availability, and Maintainability.
  • SEMI E35:  Guide to Calculate Cost of Ownership Metrics.
  • SEMI E58:  Reliability, Availability, and Maintainability Data Collection.
  • SEMI E79:  Definition and Measurement of Equipment Productivity – OEE Metrics.
  • SEMI E116:  Equipment Performance Tracking.
  • SEMI E124:  Definition and Calculation of Overall Factory Efficiency and other Factory-Level Productivity Metrics.

It is important to continually learn and improve our understanding regarding the development and application of metrics used in industry.  It is often said that you can’t believe everything you read (especially – on the internet).  As such, we recommend researching these standards to determine their applicability for your business as well.

Benchmarking Processes:

Best practices and methods used within and outside of your specific industry may bring a fresh perspective into the definition and policies that are already be in place in your organization.  Just as processes are subject to continual improvement, so are the systems that control them.  Although many companies use benchmarking data to establish their own performance metrics, we strongly encourage benchmarking of best practices or methods – this is where the real learning begins.

World Class OEE is typically defined as 85% or better.  Additionally, to achieve this level of “World Class Peformance” the factors for Availability, Performance, and Quality must be at least 90%, 95%, and 99.5% respectively.  While this data may present your team with a challenge, it does little to inspire real action.

Understanding the policies and methods used to measure performance coupled with an awareness of current best practices to achieve the desired levels of  performance will certainly provide a foundation for innovation and improvement.  It is significant to note that today’s most efficient and successful companies have all achieved levels of performance above and beyond their competition by understanding and benchmarking their competitors best practices.  With this data, the same companies went on to develop innovative best practices to outperform them.

A Practical Example

Availablity is typically presented as the greatest opportunity for improvement.  This is even suggested by the “World Class” levels stated above.  Further investigation usually points us to setup / adjustment or change over as one of the primary improvement opportunities.  Many articles and books have been written on Single Minute Exchange of Dies and other Quick Tool Change strategy, so it is not our intent to present them here.  The point here is that industry has identified this specific topic as a significant opportunity and in turn has provided significant documentation and varied approaches to improve setup time.

In the case of improving die changes a variety of techniques are used including:

  • Quick Locator Pins
  • Pre-Staged Tools
  • Rolling Bolsters
  • Sub-Plates
  • Programmable Controllers
  • Standard Pass Heights
  • Standard Shut Heights
  • Quarter Turn Clamps
  • Hydraulic Clamps
  • Magnetic Bolsters
  • Pre-Staged Material
  • Dual Coil De-Reelers
  • Scheduling Sequences
  • Change Over Teams versus Individual Effort
  • Standardized Changeover Procedures

As change over time becomes less of a factor for determining what parts to run and for how long, we can strive reduced inventories and improved preventive maintenance activities.

Today’s Challenge

The manufacturing community has been devastated by the recent economic downturn.  We are challenged to bring out the best of what we have while continuing to strive for process excellence in all facets of our business.

Remember to get your free Excel Templates by visiting our FREE Downloads page.  We appreciate your feedback.  Please leave a comment an email to leanexecution@gmail.com or vergence.consultin@gmail.com

Until Next Time – STAY Lean!

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

Welcome to LeanExecution!

Welcome! If you are a first time visitor interested in getting started with Overall Equipment Effectiveness (OEE), click here to access our very first post “OEE – Overall Equipment Effectiveness“.

We have presented many articles featuring OEE (Overall Equipment Effectiveness), Lean Thinking, and related topics.  Our latest posts appear immediately following this welcome message.  You can also use the sidebar widgets to select from our top posts or posts by category.

Free Downloads

All downloads mentioned in our articles and feature posts are available from the FREE Downloads page and from the orange “FREE Downloads” box on the sidebar.  You are free to use and modify these files as required for your application.  We trust that our free templates will serve their intended purpose and be of value to your operation.

Visit our EXCEL Page for immediate access to websites offering answers and solutions for a wide variety of questions and problems.  Click here to access the top ranking Excel Dashboards.  Convert your raw data into intelligent data to drive intelligent metrics that will help you to analyze and manage your business effectively.

Questions, Comments, Future Topics

Your comments and suggestions are appreciated.  Feel free to leave a comment or send us your feedback by e-mail to LeanExecution@gmail.com or VergenceAnalytics@gmail.com.  We respect your privacy and will not distribute, sell, or share your contact information to any third parties.  What you send to us stays with us.

Subscribe to our blog and receive notifications of our latest posts and updates.  Simply complete the e-mail subscription in the sidebar.  Thank you for visiting.

Until Next Time – STAY lean!

Vergence Analytics

SPC for OEE

Some of our readers have expressed an interest in the application of Statistical Analysis Tools for OEE.  We have also reviewed various texts and articles that have expressed opposing views on the application of Statistical Tools with OEE data.

Our simple answer is this:

  •  At best, statistical tools should only be used on unique or individual processes.   Comparisons may be made (with caution) between “like” processes, however, even these types of comparisons require a thorough, in-depth, understanding of product mix, customer demand, and potentially unique process considerations.
  • At worst, it may be worthwhile to use statistical analysis tools for the individual OEE factors:  Availability, Performance, and Quality.

Negative trends may have Positive returns

While certain top level improvements can be implemented across the company, such as quick die change or other tool change strategies, their very integration may (and should) result in changes to the existing or current operating strategy.  A quick tool change strategy may provide for substantially reduced set up times and, as a result, operations may schedule shorter and more frequent runs.  In turn, the net change to OEE may be negligible or even lower than before the new change strategy was implemented.

A drop or decline in OEE does not necessarily translate to negative financial performance.  From a cash flow perspective, the savings may be realized through reduced raw material purchases, reduced inventories, and subsequently lower carrying costs that may more than offset any potential decrease in OEE.  As we have discussed in previous posts, OEE should not be regarded as a stand alone metric.  It is important to understand the financial impact of each of the OEE factors to your bottom line.  We’re in business to make money and Cash is King.

Scope of Analysis – Keep it Simple

As the scope of the OEE analysis increases from shift, to daily, to weekly, to monthly summaries, the variables that affect the end result are compounded accordingly.  Extending statistical techniques to OEE data across multiple departments or even company wide introduces even more sources of variation that make statistical modeling unrealistic.

While the application of statistics may sound appealing and “neat”, it is even more important to be able to understand the underlying factors that affect or influence the final result in order to implement effective countermeasures or action plans to make improvements or simply to eliminate the source of concern.

Regardless of the final OEE index reported, someone will ask the question, “So, what happened to our OEE?”  Whether an increase or decrease, both will require an answer to explain the variance.  If there was a significant increase, someone will want to know why and where.  This improvement, of course, will have to be replicated on other like machines or processes.  If there was a significant decrease, someone will want to know why and where so the cause of poor or reduced performance can be identified and corrected.

Ironically, no matter what the result, you will have to be prepared to supply individual process OEE data.  So why not just review the primitive data and respond to the results in real time?  While we recommend this practice, there may be certain trends relative to the individual factors that can be statistically evaluated in the broader sense (Quality – PPM, Labour – Efficiencies).

Statistics on a larger scale

We would suggest and recommend using statistical techniques on the individual Availability, Performance, and Quality factors of OEE.  For example, many companies track labour efficiencies relative to performance while others measure defects per million pieces relative to Quality.

While most people readily associate statistics with quality processes, many operations managers are applying statistical analysis techniques to a variety of metrics such as run time performance, performance to schedule, downtime, and setup times.  Maintenance managers are also analysing equipment availability for Mean Time to Repair, Meantime Time Between Failures, and equipment life cycle performance criteria.

As one example, we have conducted and encouraged our clients to consider statistical analysis of production data.  Tracking the standard deviation of daily production over time can reveal some very interesting trends.  These results will also correlate with the OEE factors.  Where the standard deviation is low, the increase in production is reflected in other metrics as well including financial performance.

A final note

Lastly, OEE is a tool that should be used to drive improvements.  As such, the goal or target is forever changing whether in small or large increments.  Another SPC solution for OEE that may be a little easier to understand and execute is as follows:

  1. System – Define and establish an effective system for collecting, analyzing, and reporting OEE data – preferably in real time at the source.
  2. Process – Understand and establish where and how OEE data will actually be collected in your processes and how it will be used to make improvements.
  3. Control– Establish effective methods to control both systems and processes to assure OEE is and remains a truly integrated metric for your operations.

We strongly recommend and support “at the source” thinking strategy.  Quite simply, we prefer points of control that are as close to their source as possible whether it be data, measurement, or product related.  Quality “at the source” (at the machine in real time) is much easier to manage than final inspection on the dock (hours or even days later).  Similarly, OEE managed in real time, at the process or machine, will serve the people and the company with greater control.

We welcome your feedback.  Please leave a comment or send us an e-mail (leanexecution@gmail.com) with your questions, suggestions, or comments.

Until Next Time – STAY lean!

We respect your privacy – we will not distribute, sell, or otherwise provide your contact or other personal information to any outside or third party vendors.

6 things OEE is NOT!

While OEE has been receiving much deserved attention as manufacturers look for ways to improve their bottom line, it is not the cure for all that ails manufacturing.  Many in the manufacturing community seem to be getting caught up in the buzz and hype of OEE and its profound ability to improve the bottom line.

1.  OEE is NOT magic

As we were researching for our problem solving series, we couldn’t help but notice the numerous attributes that were being given to OEE and how it seems to be solving all the woes of manufacturing.  A thermometer won’t change the weather and OEE alone won’t change your operation.

OEE:  The Lens of Opportunity

We prefer to think that using OEE is like putting on a pair of much needed glasses.  What you are looking at hasn’t changed, your eyes haven’t changed, but the way you see it has.  Similarly, OEE is a very effective metric that serves as a lens to help you see and identify where losses are being incurred.

OEE will help to identify the problem or at least the symptoms.  The real opportunity is to determine root causes for the losses and implement effective corrective actions to eliminate them.  OEE can also be used to verify or validate the actions taken.  Remember,

2.  OEE is not a root cause analysis tool

3.  OEE is not problem solver

4.  OEE is not a solution provider

We recently reviewed an article suggesting that OEE is an indicator of a company’s profitability.  We would argue that OEE is a measure of loss or, to be more positive, profit potential.  Just because we’re effective, doesn’t mean we’re profitable.  Today’s economy and the current state of manufacturing clearly demonstrates this.

5.  OEE is not an indicator of profitability

Another misnomer is mistaking OEE as a measure of operational efficiency.  OEE measures how effectively we used the time for a given asset to make a quality part.  OEE isn’t concerned with the amount of labour or materials required to achieve the desired “rate”.  For example, using two people to achieve the rate of one is not efficient.  As another example, using a higher grade of material to achieve a quality part due to unresolved process issues is not efficient.

6.  OEE is NOT a measure of  Efficiency

Again, OEE measures how  effectively assets are being utilized to make a quality part.  For a complete discussion on measuring OEE, refer to our discussions on Calculating OEE (see the categories side bar).

What is the Answer?

OEE is the single metric that can be used to identify where significant losses are being incurred, the real opportunity to improving the process is to identify the root causes and finding the solutions to the problems that have been identified.

OEE is an excellent diagnostic metric that can help to focus your improvement efforts.  The data acquisition systems available on the market today provide real time intelligence and valuable insight into your processes.  These tools in collaboration with an effective problem solving strategy ultimately become the reason for your improved performance.

Statistics don’t improve quality, thermometers don’t change temperatures, clocks don’t prevent breakdowns.  Don’t confuse the measurement system with the solution – it’s one of the tools.

Effective analysis, problem solving, and timely and efficient execution of corrective actions to address the concerns and eliminate the real root causes – that’s the answer.

OEE is simply one method to grade your efforts.

We appreciate your feedback.  Please leave a comment or send your questions and suggestions to leanexecution@gmail.com

We respect your privacy – we do not and will not sell, distribute, share, or disclose your e-mail or contact information to any outside or third party entities.

Until Next Time – STAY lean!