Tag: Beating OEE

Advanced Lean Manufacturing, APQP, Eliminate Waste, Lean, Lean Metrics, OEE: Overall Equipment Efficiency, Problem Solving

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

Advanced Lean Manufacturing, Availability, Lean Metrics, OEE: Overall Equipment Efficiency, Process Control and OEE

OEE: Take the Hit

The simplicity of measuring and calculating OEE is compounded by the factors that ultimately influence the end result.  Because the concept of OEE can be readily embraced by most employees, it is easy for many people to get involved in the process of making improvements.

Unfortunately the variables involved with OEE, like those of many other measurement systems, fall under scrutiny.  The goal of achieving yet even higher OEE numbers is met with yet another review of the factors and how they are treated.  Usually the scope of this often heated discussion is focused on Availability.

The greatest task of all occurs when attempting to classify what qualifies as planned versus unplanned downtime.  Availability is the primary factor where significant improvements can be realized and is most certainly the focus of every TPM program in existence.  However, another significant factor that can greatly impact Availability is setup time.

We still receive questions and comments from our readers regarding setup time and whether or not they should “take the hit” for it.  We have met up with different rationale and reasoning to exclude setup time from the availability factor such as:  “We have all kinds of capacity and do the setups in our free time.” Or, “We do the setups on the off shift so the equipment is always ready when the first shift comes in.”

Regardless of the rationale, our short answer to the question of inclusion for setup time remains a simple, “Yes, take the hit.”  Before we get to much further let’s define what it is.  Setup time is typically defined as the time required to change or setup the next process.  The duration of time is measured from the last good part produced to the first good part produced from the new process.

Improving setup times provides for shorter runs, reduced inventories, increased available capacity, increased responsiveness, improved maintenance, and in turn, improved quality.  Shorter runs also provide the opportunity to maintain tools more effectively between runs as they are not as subject to excessive wear caused by longer run times and higher production levels.

Setup and Quick Die Change / Quick Tool Change

An exhaustive amount of work has been completed in many manufacturing disciplines to reduce and improve setup times.  Certainly, by simply ignoring the setup time, there is no real way to determine whether the new methods are having an impact unless another measurement system for setup is introduced.  We already have a measurement system in place, so why invent another one?

Quick Die Change and other Quick Tool Change strategies are common place in industries such as automotive stamping plants.  The objectives for Quick Die Change are attributed to LEAN principles such as single part flow and reduced inventories.  The benefits of these efforts, of course, extend to OEE and availability.

Setup and Production Sequencing

To exemplify the effect of sequencing and setup, consider a single tool that makes 8 variations of a product.  For the sake of discussion, let’s assume the only difference is the number of holes punched into the part.  The time for each punch removed from, or added to, the tool is the same.

The objective for scheduling this tool is quite obvious.  We need to minimize the number of punch changes to minimize the downtime.  If the parts required range from 1 hole to 8 holes, and we need 100 parts of each variant, we would arrange the schedule in such a manner as to make sure we are only adding one punch to the tool as we move on to the next variant.

In this case, setup time and sequencing are clearly a cause for concern and consideration.  Secondly, it is much easier to calculate the time required to run all the parts and how much capacity is required.  Including setup in the OEE factor also simplifies the calculation of overall capacity utilization for the piece of equipment in general.

In Conclusion

As we have stated in previous posts, the objective of measuring OEE is to identify opportunities for improvement.  Achieving higher numbers through the process of debate and elimating elements for consideration is not making improvements.  Don’t masquerade the problem or the opportunities. 

Setup is certainly one area where improvements can be measured and quantified.  Availability and OEE results provide an opportunity to demonstrate the effectiveness of these improvements accordingly.

If the leadership of the company is setting policy then the explanations for performance in this regard should be understood.  The only numbers that really matter are on the bottom line and hopefully they are black.

We would also encourage you to visit two of our recent posts, Improving OEE – A hands on approach (posted 03-Jan-09) and OEE and Availability, (posted 31-Dec-2008).

Until next time, stay LEAN.

Advanced Lean Manufacturing, Lean, Lean Metrics, OEE: Overall Equipment Efficiency, Process Control and OEE

Upcoming OEE Topics – February 2009

The following topics will be featured in an upcoming post, we’ll try to squeeze them in before February 2009 rolls off the calendar.  If you have a topic that you would like to see featured on our site, send an e-mail to LeanExecution@gmail.com.

Capacity Planning with OEE:  By definition, it only makes sense to use OEE as an integral part of your capacity planning process.  We will cover the details to do this effectively.  Effective capacity planning naturally extends to improved resource management and effective production planning.

OEE, Value Streams, and COST:  Although some managers may rise to the challenge and volunteer, many are either assigned or designated to be project champions.  In many cases, unfortunately, the scope of the project is extremely limited or restricted and project managers simply become “metric managers”.  Who is in charge of OEE?  The answer is quite simple:  EVERYONE.  OEE is a multi-discipline metric and, like other sound lean strategies, requires seamless interaction among managers and departments.

OEE cannot and should not be managed as an independent metric.  Having said that, don’t get caught in the trap of “stand alone” OEE reviews.  While there may be a number of strategies for improving OEE, such as constrained capacity, we will present a model that explicitly ties operational costs to your processes.  When OEE data is sensitised by cost data, a completely different strategy for improvement will emerge.  If the ultimate goal is to improve your bottom line, then our Cost sensitisation model will bring the concept of OEE and your bottom line to a whole new level.

OEE and Lean Agility:  Can OEE be a leading indicator of your ability to respond to change?  Well we think so and happen to have a few ideas that will show you how and why.

Send us your questions or comments or simply suggest a topic for a future post or article.

Stay tuned for more!  We appreciate your feedback.

Advanced Lean Manufacturing, Lean Metrics, OEE: Overall Equipment Efficiency, Process Control and OEE

OEE and Morale

Is employee morale impacting your OEE?  If so, how much of a concern is it?  As we wrote in one of our recent posts,  “Perhaps the greatest “external” influence on current manufacturing operations is the rapid collapse of the automotive industry in the midst of our current economic “melt down”.  The changes in operating strategy to respond to this new crisis are bound to have an effect on OEE among other business metrics.”  We would argue that these times of economic crisis demand, now more than ever, that Lean Practices must become even more prevalent in our manufacturing operations.

People are concerned about the state and stability of the company’s finances and the industries they serve.  The automotive industry has been devastated by the recent decline, or more accurately, collapse of the market.  Significant changes in operating strategy including lay offs and reduced production days have impacted all of the OEM’s including Ford, GM, Chrysler, Toyota, and Honda.  No one company is immune from the effects of the current economic conditions.

It is clear that the auto industry fell behind the “power curve” and crashed.  Did conditions change too quickly to avoid the inevitable?  Was it so big that, like the Titanic, the ultimate demise could be predicted but not avoided?  Toyota was the number one producer of automobiles in 2008 but failed to yield significant profits.  Conditions such as these were ripe for continued growth in years past.  It is clear that even the best of the Lean practitioners are not immune from the effects of the current economy.

A company’s agility will certainly be tested during times such as these.  Sustainability and viability are among the few significant objectives of Lean dynamics.  As such, Lean dynamics should be at the forefront of every business leader.  How adaptable is your business?  Are you reinventing your business in response to the changes of your industry?  The true Lean practitioner is certainly challenged to eliminate waste and variation beyond current means and traditional approaches.  As change is constant, we must continually seek out ways to redefine or “better” define our businesses.

At the most fundamental level, everyone is concerned about the state of the economy, however, individuals, at the personal level, are concerned about their jobs and careers.  We all want to preserve our current life style to some degree and, at a minimum, continue to pay our bills.  It would be a difficult task to estimate the lost productivity that occurs when someone’s state of mind is focused on their own personal situation versus that of the company.  We have observed first hand how employee morale has diminished as a result of the recent economic doom and gloom.  Nothing can come between an indivual and their prosperity – this is an instinctive, almost primitive, response mechanism – a self defense position.

Recommendations:

While you may not be able to change the economy, we would suggest that you can influence the “morale” of your employees.  People will understand that you didn’t cause the current economic crisis, however, they do expect that you will let them know what the impact is to your business and ultimately to themselves.

Be honest with your employees, let them know where you stand – where they stand.  They need to prepare for their futures too, whether it is working for you or someone else.  During times of crisis such as this, it is time for the executive leadership to stand behind their Vision and Mission statements and treat their employees – THE PEOPLE -the most important assets a company can have – with the dignity and respect they not only deserve but worked so hard to earn.  Be present and available to your team.

Our employees recognize that we only attract, retain, and hire the best employees.  Regardless of the economy, the standard remains and we take great pride in the strength of our people.  They know this intrinsically.

People come to companies to work for PEOPLE.  Their immediate supervisor or manager is, in their eyes, the company.  Arm your staff with the information they need so people can make informed decisions.  Believe it or not, people are motivated when they feel that they are part of the process and not regarded as part of the problem.  Reality check:  “People come to companies to work for themselves.”  How does this statement change your perspective?  Who do you work for?

How many times have you heard, “Our labour is just too high,  we need to cut back.”  Well, who made the decision to hire the people in the first place?  Look in the mirror.  Treat people like they are part of the team, part of the solution.  Get them engaged and focused on moving forward.  Will they be motivated?  They will be if they feel that they are valued players on the team, performing meaningful work that is contributing to the success of the company.  Times of crisis tend to bring teams closer together and, in the end, they become stronger for the cause.

A great business parable written by Patrick Lencioni, “The Three Signs of a Miserable Job”, may provide some useful insights to motivate your team and even grow your business into a more profitable venture despite the current economic crisis.

While people think they work for a company or other people, we ultimately believe that people work for themselves and we, as a company, are the beneficiaries of their efforts.

Conclusion

So how does all of this tie to OEE?  Weill, performance typically lags when people are not focused on the task at hand.  There is a sense that, no matter what they do, they can’t change the current circumstances so, “Why bother?”  Distractions of this magnitude are hard to ignore.  As the leadership of the company, it is your responsibility to be in tune with the morale of your team and workforce in general.  It is possible to mitigate the effects of low morale by addressing them early on and encouraging employees to be part of the turn around process.

This might be one of the few times in history where the term “CHANGE” will be viewed in a positive light and actually be embraced by your team.

We may just discover the 5S process for managing our economy with a real process in place to manage the fifth “S” Sustainability.  Another one of the “anomalies” that just don’t make sense is, “This is just part of the nautral cycle of the economy.  We were long overdue.”  Somehow, that doesn’t say much about our governments or industry leaders. Why?  Because it suggests we should have been more than prepared to deal with this a long time ago.  The current scramble suggests the contrary to be true.  Secondly, what is “natural” about the economy – it’s manmade – driven by the decisions of business leaders and governments around the globe.  Natural? Never.  A logical excuse that every one seems to accept as part of “nature”?  Maybe.

Until next time – STAY Lean!

Advanced Lean Manufacturing, Eliminate Waste, Lean Metrics, OEE: Overall Equipment Efficiency, Process Control and OEE

OEE Measurement Error

How many times have you, or someone you know, challenged the measurement process or method used to collect the data because the numbers just “don’t make sense” or “can’t be right”?

It is imperative to have integrity in the data collection process to minimize the effect of phantom improvements through measurement method changes.  Switching from a manual recording system to a completely automated system is a simple example of a data collection method change that will most certainly generate “different” results.

Every measurement system is subject to error including those used to measure and monitor OEE.  We briefly discussed the concept of variance with respect to actual process throughput and, as you may expect from this post, variance also applies to the measurement system.

Process and measurement stability are intertwined.  A reliable data collection / measurement system is required to establish an effective baseline from which to base your OEE improvement efforts.  We have observed very unstable processes with extreme throughput rates from one shift to the next.  We learned that the variance in many cases is not always the process but in the measurement system itself.

We decided to comment briefly on this phenomenon of measurement error for several reasons:

  1. The reporting systems will naturally improve as more attention is given to the data they generate.
  2. Manual data collection and reporting systems are prone to errors in both recording and data input.
  3. Automated data collection systems substantially reduce the risk of errors and improve data accuracy.
  4. Changes in OEE trends may be attributed to data collection technology not real process changes.

Consider the following:

  1. A person records the time of the down time and reset / start up events by reading a clock on the wall.
  2. A person records the time of the down time event using a wrist watch and then records the reset /start up time using the clock on the wall.
  3. A person uses a stop watch to track the duration of a down time event.
  4. Down time and up time event data are collected and retrieved from a fully automated system that instantly records events in real time.

Clearly, each of the above data collection methods will present varying degrees of “error” that will influence the accuracy of the resulting OEE.  The potential measurement error should be a consideration when attempting to quantify improvement efforts.

Measurement and Error Resolution

The technology used will certainly drive the degree of error you may expect to see.  A clock on the wall may yield an error of +/- 1 minute per event versus an automated system that may yield an error of +/- 0.01 seconds.

The resolution of the measurement system becomes even more relevant when we consider the duration of the “event”.  Consider the effect of measurement resolution and potential error for a down time event having a duration of 5 minutes versus 60 minutes.

CAUTION!

A classic fallacy is “inferred accuracy” as demonstrated by the stop watch measurement method.  Times may be recorded to 1/100th of a second suggesting a high degree of precision in the measurement.  Meanwhile, it may take the operator 10 seconds to locate the stop watch, 15 seconds to reset a machine fault, and 20 seconds to document the event on a “report” and another 10 seconds to return the stop watch to its proper location. 

What are we missing?  How significant is the event and was it worth even recording?  What if one operator records the “duration” after the machine is reset while another operator records the “duration” after documenting and returning the watch to its proper location?

The above example demands that we also consider the event type:  “high frequency-short duration” versus “low frequency-long duration” events.  Both must be considered when attempting to understand the results.

The EVENT is the Opportunity

As mentioned in previous posts, we need to understand what we are measuring and why.  The “event” and methods to avoid recurrence must be the focus of the improvement effort.  The cumulative duration of an event will help to focus efforts and prioritize the opportunities for improvement.

Additional metrics to help “understand” various process events include Mean Response Time, Mean Time Between Failures (MTBF), and Mean Time To Repair (MTTR).  Even 911 calls are monitored from the time the call is received.  The response time is as critical, if not more so, than the actual event, especially when the condition is life-threatening or otherwise self-destructive (fire, meltdown).

An interesting metric is the ratio between Response Time and Mean Time To Repair.  The response time is measured from the time the event occurs to the time “help” arrives.  Our experience suggests that significant improvements can be made simply by reducing the response time.

We recommend training and providing employees with the skills needed to be able to respond to “events” in real time.  Waiting 15 minutes for a technician to arrive to reset a machine fault that required only 10 seconds to resolve is clearly an opportunity.

Many facilities actually hire “semi-skilled” labour or “skilled technicians” to operate machines.  They are typically flexible, adaptable, present a strong aptitude for continual improvement, and readily trained to resolve process events in real time.

Conclusion

Measurement systems of any kind are prone to error.  While it is important to understand the significance of measurement error, it should not be the “primary” focus.  We recommend PREVENTION and ELIMINATION of events that impede the ability to produce a quality product at rate.

Regrettably, some companies are more interested in collecting “accurate” data than making real improvements (measuring for measurements sake). 

WHAT are you measuring and WHY?  Do you measure what you can’t control?  We will leave you with these few points to ponder.

Until next time – STAY Lean!

Advanced Lean Manufacturing, Availability, Eliminate Waste, FREE Downloads, Lean, Lean Metrics, OEE: Overall Equipment Efficiency, Performance, Problem Solving, Quality, Quality Factor, Root Cause Analysis, Training, Trouble Shooting

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

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Until Next Time – STAY Lean!

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