Tag: How to work with OEE

OEE Integration – Part III

The primary components of your OEE infrastructure are People and DATA.  The people are the life of the OEE system, all else is support.  Data collection and management technologies play an important role in the OEE process, however, they are data collection / process / delivery systems that are programmed to provide reports as requested by the people that use the system.

So, now that we have determined that people are the drivers of the system, the core task then is to provide the people with the education and training they need to be an integral part of the OEE process.  Remember, the people ultimately analyze and make sense of the data using a variety of technology solutions.  Your team is also responsible for recommending actions to improve the current processes based on the data.

Training

Trained and qualified personnel are at the core of any initiative and are fundamental to the success of the program in general.  Our recommendation is to ensure that all personnel across the organization, from the shop floor to the executive leadership, understand the principles of OEE and how it will become an integral part of the company culture to sustain and drive continual improvement.

The executive leadership must embrace the concept of OEE and determine the policies and procedures that surround its measurement and support the actions required to execute improvements to the system and processes accordingly.  To this end, we also recommend that the training is performed by personnel within the organization and not necessarily by executive or senior management.

Consultants serve as an excellent resource to facilitate the initial training and to provide the necessary tools or materials to assure its success.  More importantly however, consultants serve as catalyst to facilitate the integration and implementation process.  A consultant would best serve your interests by supporting a “train the trainer” methodology.

Executive and senior management are responsible for defining the policies and procedures of the OEE management process or system.  While OEE goals and objectives may be determined by management in conjunction with the team, or some of its members, the team is ultimately responsible for the development and execution of the action or improvement plans.

For this reason, we recommend that employees are trained by their immediate supervisor, team leader, or each other (peer to peer).  The objective of peer to peer training is to engage all employees in the training process by encouraging each employee to teach a portion or segment of the training module.  Of course this latter approach assumes that you have training materials available to support this activity.

Training with your own staff will affirm the commitment of the company and the employees will appreciate the presence and development of in-house expertise to make the OEE initiative a success.  This approach also assures that ownership remains with the users of the system – the company.  The best way to teach someone is to give them the responsibility to teach others.  Those who assume the responsibility to teach will certainly become better students as well.

This approach may strike you as a protectionist measure to preserve our integrity as consultants.  To the contrary, our objective as consultants is to serve as a catalyst to develop the infrastructure of your organization using a strategy where the system is ultimately self-sustaining and integral to the culture of your operation.

Over the past few posts we have developed a strategy for engaging your teams in the OEE process.  As we have indicated throughout our series, there are a variety of technology solutions available to measure OEE, few however, provide the tools to develop the infrastructure in your organization to make them effective.

We will pursue this strategy further in future posts.

Until Next Time – STAY lean!

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OEE Integration – Part II

Training and Integration

Integrating OEE into your organization will take some time.  However, the benefits are definitely worth the effort.  Preparing an effective integration strategy will pay off dividends in the execution phase of your program and can serve as the core theme to launching many of your other lean manufacturing initiatives.

The challenge for many organizations is turning lean metrics, more specifically OEE, into part of the everyday language of the company.  The world of sports provides an excellent analogy to demonstrate how metrics are a necessary and integral part of the games we watch.  Baseball, football, basketball, hockey, cricket, and others all offer statistics or metrics that don’t necessarily determine the outcome of the game but certainly provide insight into the performance of the players and potential of the team.

While it may be a bit much to ask our employees to embrace lean performance metrics like OEE with the same energy and enthusiasm as they may have for sports, we can certainly encourage them by providing them with the education and training they need to better understand these metrics and why it is important to their future and the future of the company.

Defining the Need

It is imperative that you and your employees understand the need for an OEE system before even commencing with any physical implementation strategy.  It is even more critical to define and understand what is being measured and how the measurements will be used to improve your operation or processes.

To be effective, the team must have confidence and trust in the leadership coupled with a firm understanding of the practical intentions of the OEE system.  If employees perceive punitive intentions, you will most certainly lose.  How OEE data is used in your operation or processes will determine how successfully it can be integrated across the entire organization.

Understanding the rules of engagement is the key to making the metrics meaningful and effective.  Educating and training your team is at the very foundation of the lean journey.  Without it, the efforts are sure to fail.  Resistance to change is often fueled by lack of knowledge and understanding.

The VISE – Get the Commitment – Create the Charter

Vision:  We will manage in Real Time using metrics to measure our performance and effective use of capital and human resources;

Intelligence:  We will become students and teacher of our business, training and educating ourselves and each other;

Strategy:  We will develop effective, detailed plans to support our vision, goals, and objectives to be a viable, sustainable, and growing business enterprise;

Execute:  We will execute specific, detailed action plans in a timely and efficient manner, addressing all impediments to assure our success;

WHY:  to drive continual improvement, support our lean initiatives, and eliminate waste in our organization.

Using acronyms can be an effective way to communicate your expectations.  The VISE provides a strategic super-view that is easily embraced by any organization serious about their present and future business prospects.

More on this topic in tomorrow’s post.

Until next time – STAY lean!

OEE Calculation Errors

Database Errors

We agree that collecting and tracking OEE data is a task best suited for a database, however, all the bells and whistles of an OEE system don’t serve much purpose if the calculations are wrong.  Before you make a significant investment in your OEE data collection, tracking, and monitoring system, make sure the system you plan to purchase is calculating the OEE results correctly.

The ultimate system is one that supports automated data collection technology to minimize data entry costs, reduces the risk of entry errors, and provides reporting or monitoring of OEE in real time.  These solutions may be purchased “off the shelf” or customized to your specific process application.

Excel Spreadsheets

If a database is the best approach, you may ask why we use Excel spreadsheets to present our examples or why we supply templates to allow you to track and monitor OEE.  We have four primary reasons:

  1. Almost everyone is familiar with spreadsheets and most people have access to them on their computer.
  2. We determined that a customized database solution being used was not calculating the weighted OEE factors correctly and the overall OEE index was also wrong.  We found it necessary to develop a spreadsheet that made it easy to validate the database calculations.
  3. Database enhancements were easier to develop and demonstrate using a spreadsheet.  We encountered a production process that was equipped with automated data collection capability and provided an overwhelming amount of performance data in real time.  It was easier to perform database queries and use the power of PIVOT tables to develop the desired solutions.
  4. Spreadsheet templates allow you to start collecting and analyzing data immediately.  It also allows the users to get a “feel” for the data.  Although the graphs and drill downs offered by databases are based on predetermined rules, humans are still required to make sense of the data.

Recommendations

In summary, validate the software and its capabilities prior to purchase.  We have observed installations where the OEE data is used to monitor current production performance and the reports generated by the system are used to support the results – good or bad.

We have also evaluated a number of other free OEE spreadsheet offerings on the web and observed that some of these also fail to correctly calculate OEE where multiple machines or part numbers are concerned.  Take a look at our free spreadsheets offerings (see the sidebar).  Our tutorial provides an in depth explanation of how to calculate OEE for single and multiple machines or parts.

The purpose of measuring OEE is to ensure sustained performance with the objective to continually improve over time.  Don’t fall into the trap of setting up a system that, once installed, will only be used to generate reports to justify the current results.

Take the time to train your team and demonstrate how the results will be used to improve their processes.  Involve all of your employees from the very beginning, including the system selection process, so they understand the intent and can provide feedback for what may be meaningful to them while, in turn, they can support the company’s goals and objectives.

Reference Posts.

We encourage you to visit our previous posts showing how to calculate OEE for multiple parts and machines.

  1. Single Process – Multiple Shifts:  OEE

  2. Multiple Parts / Processes:  OEE

  3. Practical OEE

  4. Weighted Calculations:  OEE

  5. How to Calculate OEE

  6. Overall Equipment Efficiency

If you have any questions, comments, or wish to suggest a topic for a future post, please forward an e-mail to leanexecution@gmail.com

We appreciate your feedback.

Until next time – STAY Lean!

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.

Upcoming Topics for March 2009

We have received several topic requests that we will work on for the month of March, 2009.  If you have a topic that you would like to see featured on our site, send an e-mail to LeanExecution@gmail.com.

OEE on the Shop Floor – Measurement:  What should we be measuring to make OEE practical at the shop floor level.  What factors are critical to the person or persons doing the work?  We have presented the pros and cons of various systems that are used today.  We would suggest that the number of solutions is as varied as the number of companies seeking them.  A customized solution for your specific business operation is likely the best option.  A tailored solution is not necessarily a costly one.

OEE Innovations – TRIZ:  Ultimately the reason for measuring OEE is to make improvements in capacity utilization.  TRIZ is a very valuable tool that can be used to bring new and innovative solutions to improving your OEE.  Many companies are likely unaware of the TRIZ process as so much focus is placed on LEAN and Six Sigma.  Combining these disciplines with TRIZ can yield a highly successful solution that may just be the next generation ideal.

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.

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!

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!

OEE For Dedicated – Single Part – Processes

OEE For Dedicated – Single Part – Processes

Definition: 

Dedicated – Single Part – Process:  A process that produces a single product or slight variations on a theme and does not require significant tooling or equipment changeover events.

A single part process is the easiest application for a OEE pilot project.  The single part process also makes it easier to demonstrate some of the more advanced Lean Thinking tools that can be applied to improve your operation or process.  In our “Variation, Waste, and OEE” post, we introduced the potential impacts of variance to your organization.  We also restated our mission to control, reduce, and eliminate variation in our processes as the primary objective of LEAN.

We need to spend more time understanding what our true production capabilities are.  The single part process makes the process of understanding these principles much easier.  The lessons learned can then be applied to more complex or multipart processes.  In multipart or complex operations, production part sequencing may have a significant impact on hourly rates and overall shift throughput.  How would you know unless you actually had a model that provided the insight?

Process Velocity:  Measuring Throughput

Let’s start this discussion by asking a few simple questions that will help you to get your mind in gear.  Do you measure variation in production output?  Do you measure shift rates?  Do you use the “average” rate per hour to set up your production schedules?  How do you know when normal production rates have been achieved?  Does a high production rate on one shift really signify a process improvement or was it simply a statistically expected event?

Once again an example will best serve our discussion.  Assume the following data represents one week of production over three shifts:

Machine A:  Production Process Performance Report

Cycle Time (Seconds):   57      
Shift Standard (440 minutes) 440      
             
Day Shift Planned Quantity
Production Time Total Test Scrap Accept
Mon 1 440 420 1 2 417
Mon 2 440 390 1 1 388
Mon 3 440 320 1 3 316
Tue 1 440 361 1 1 359
Tue 2 440 392 1 5 386
Tue 3 440 365 1 2 362
Wed 1 440 402 1 7 394
Wed 2 440 317 1 6 310
Wed 3 440 430 1 1 428
Thu 1 440 453 1 5 447
Thu 2 440 419 1 3 415
Thu 3 440 366 1 1 364
Fri 1 440 400 1 2 397
Fri 2 440 411 1 4 406
Fri 3 440 379 1 2 376
Totals 15 6600 5825 15 45 5765

The following table is an extension of the above table and shows the unplanned downtime as well actual, standard, and ideal operating times.

Day Shift Unplanned Operating Time
Down Time Actual Standard Ideal
Mon 1 25 415.0 399.0 396.2
Mon 2 55 385.0 370.5 368.6
Mon 3 122 318.0 304.0 300.2
Tue 1 84 356.0 343.0 341.1
Tue 2 65 375.0 372.4 366.7
Tue 3 82 358.0 346.8 343.9
Wed 1 45 395.0 381.9 374.3
Wed 2 130 310.0 301.2 294.5
Wed 3 30 410.0 408.5 406.6
Thu 1 5 435.0 430.4 424.7
Thu 2 40 400.0 398.1 394.3
Thu 3 90 350.0 347.7 345.8
Fri 1 45 395.0 380.0 377.2
Fri 2 45 395.0 390.5 385.7
Fri 3 60 380.0 360.1 357.2
Totals 15 923 5677 5533.8 5476.8

The table below shows the OEE calculations for each day and shift worked.  Note that this table is also an extension of the above data.

Day Shift Overall Equipment Effectiveness (OEE)
Availability Performance Quality OEE
Mon 1 94.3% 96.1% 99.3% 90.0%
Mon 2 87.5% 96.2% 99.5% 83.8%
Mon 3 72.3% 95.6% 98.8% 68.2%
Tue 1 80.9% 96.3% 99.4% 77.5%
Tue 2 85.2% 99.3% 98.5% 83.3%
Tue 3 81.4% 96.9% 99.2% 78.2%
Wed 1 89.8% 96.7% 98.0% 85.1%
Wed 2 70.5% 97.1% 97.8% 66.9%
Wed 3 93.2% 99.6% 99.5% 92.4%
Thu 1 98.9% 98.9% 98.7% 96.5%
Thu 2 90.9% 99.5% 99.0% 89.6%
Thu 3 79.5% 99.3% 99.5% 78.6%
Fri 1 89.8% 96.2% 99.3% 85.7%
Fri 2 89.8% 98.8% 98.8% 87.7%
Fri 3 86.4% 94.8% 99.2% 81.2%
Totals 15 86.0% 97.5% 99.0% 83.0%

The results from the table above suggest that the process is running just short of world-class OEE (83% versus 90% for dedicated processes.  Note that 85% is considered world-class for multipart variable processes).  As you can see from the daily and shift results, a lot of variation is occurring over the course of the week.  This is the opportunity that we need to pursue further.  A quick scan of the data suggests that Wednesday 2nd shift and Monday 3rd shift are the main contributors to the reduced OEE.  We will investigate the data a little further to really understand what opportunities exist.

A dedicated, continuous process should yield a higher OEE since the process is not subject to continual setup and change over.  Although some model changes or variations to the existing product may exist, they are typically less disruptive.  A OEE of 90% may be an achievable target and is typical for most dedicated operations.

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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Availability and OEE

What is Availability?

In its simplest form, availability measures the uptime of a machine or process against the planned production time.  As one of the factors of Overall Equipment Efficiency (OEE), Availability is expressed as a percentage.  The uptime is calculated by taking the difference between the planned production time and total duration of the downtime events that occurred during the planned production period.

We specifically address the “Availability” factor in this post for the simple reason that the definition of availability is likely to be one of the most debated and hotly contested topics of your OEE implementation strategy.  The reason for this, in many cases, is the lack of clarity in some of the most basic terminology.  The purpose of this discussion is to present some topics for consideration that will allow you to arrive at a clear definition that can perhaps be formed into a standard policy statement.

We will also demonstrate that it is possible to calculate the downtime by simply knowing the cycle time or process rate, the quantity of parts produced, and the planned production time.  We recommend using this technique to validate or reconcile the actual documented downtime.  We would argue that the first and foremost purpose of any machine monitoring or downtime event measurement system is to determine the “WHY and WHAT” of the downtime events and secondly to record the “When and How Long”.

You will learn that monitoring your processes to determine causes and duration of downtime events  is key to developing effective action plans to improve availability.  The objective of any machine automation, sensor strategy, or data collection and analysis is to determine methods and actions that will improve the availability of the equipment through permanent corrective actions, implementing more effective trouble shooting strategies (sensor technologies), improved core process controls, or more effective preventive maintenance.

Define the purpose of OEE

While it looks like we’re taking a step back from the topic of discussion, bear with us for just a paragraph or two.  A clear statement of purpose is the best place to start before executing your OEE implementation strategy:

To identify opportunities to improve the effectiveness of the company’s assets.

You will quickly realize that, when attempting to define the measurement criteria for the OEE factors, in particular Availability, your team may present rationale to exclude certain elements from the measurement process.  These rationalizations are typically predicated on existing policy or perceived constraints that simply cannot be changed.  People or teams do not want to be penalized for items that are “out of their control” or bound by current policy.  Continuous improvement is impeded by attempts to rationalize poor performance.

We understand that some of these “exclusions” present a greater challenge, however, we do not agree with the premise that they cannot be improved.  Again, it is a matter of “purpose”.  Limiting the scope of measurement will limit the scope of improvement.  Now it’s time to explore what could be the foundation for a sound definition of availability.

Availability Considerations

It may seem reasonable to assume that, at a minimum, the only planned down time events that should be excluded from the availability factor are  planned preventive maintenance activities, mandatory break periods, and scheduled “down” time due to lack of work.  We would argue and agree that the only justification for an idle machine is “Lack of Work”.

What would be the reason to settle for anything less?  If Preventive Maintenance is critical to sustaining the performance of your process, doesn’t it make sense to consider it in the measurement process?  The rationale that typically follows is that Preventive Maintenance must be done and it’s really out of our control – it is a planned event.  We would argue that the time to complete Preventive Maintenance can be improved.

Is it possible that the Mean Time Before Failure or Required Maintenance can be extended?  Is it possible to improve materials, components, or lubricants that could extend the process up time?  Is it possible to improve the time it actually takes to perform the required maintenance?  If so, what is the measure that will be used to show that additional capacity is available for production.

If set up times for die changes or tool changes can be improved from hours to minutes, could the same effort and devotion to improve Preventive Maintenance techniques yield similar results?  We think so.

One example is the use of synthetic oils and lubricants that have been proven to significantly extend the life of tools and components and also reduces the number changes required over the service life of the machine.  Quick change features that can assist with easy and ready access to service points on tooling and machines can also be implemented to reduce preventive maintenance times.

The other exclusion that is often argued is break times.  Labour laws require you to provide break times for your employees.  However, since automated processes are not subject to “Labour Laws”, the “mandatory break times” do not apply.  We would argue that methods should be pursued to reduce the need for human intervention and look for ways to keep the machine running.  Is it possible to automate some of the current processes or rotate people to keep the machine running?

Aside from this more obvious example, consider other organizational policies that may impact how your organization runs:

  1. Shift start-up meetings
  2. Employee Communication Meetings
  3. End of Shift clean up periods
  4. Quality first off approval process
  5. Shift first off versus Run first off
  6. Weld Tip changes – PM or Process Driven

 What is the purpose of the shift start-up meeting?  What is the purpose of the monthly employee communication meeting?  Could this information be conveyed in a different form?  What length of time is really required to convey the message to be shared?  Is the duration of the meeting actually measured or do you resort to the standard time allotted?

Clean up periods at the end of the shift  are also a common practice in many plants.  What is being cleaned up?  Why?  Is it possible to maintain an orderly workplace during the shift – clean up as it happens in real-time?  Again, do you record the actual clean up time or do you just enter the default clean up time allotted?

How much time is lost to verify the integrity of the product before allowing production to commence?  What process parameters or factors would jeopardize the quality of the product being produced?  No one wants to make scrap or substandard components, however, the challenge remains to determine what factors influence the level of quality.  If it is possible to determine what factors are critical to success in advance, then perhaps the quality verification process becomes a concurrent event.

Measuring Downtime.

 There are other factors that can impact availability including, but certainly not limited to, personnel (illness, inclement weather), material availability, other linked processes (feeder / customer), material changes, tool changes, quality concerns, and unexpected process, equipment, or machine faults.

It is possible to use manual or automated systems to collect various machine or process codes to record or document the duration and type of downtime event.  We recommend and support the use of automated data collection systems, however, they should be implemented in moderation.  One of the primary impediments to success is overwhelming volumes of data that no one has the time to analyze.

The Goal = 100% Up Time = ZERO Down Time = Zero Lost Time = Zero Defects = 100% Availability

The goal is to use the data and tools available to either permanently resolve the problem by implementing an effective corrective action or to assist the trouble shooting process by identifying the failure mode and to minimize the duration of the downtime event.

We have witnessed data collection strategies where an incredible number of sensors were installed to “catch” problems as they occur.  The reality was the sensors themselves became the greater cause of downtime due to wear or premature failure due to improper sensor selection for the application.  Be careful and choose wisely.

When used correctly, automation can be a very effective tool to capture downtime events and maintain the integrity of the overall measurement process.  With the right tools, trouble shooting your process will minimize the duration of the down time event.  Monitoring the frequency of these events will also allow you to focus your attention on real opportunities and circumvent nuisance faults.

The objective of collecting the “downtime event” history is to determine what opportunities are available to improve uptime.

Duration versus Frequency

The frequency of a downtime event is often overlooked as most of the attention is devoted to high duration downtime events.  Some sources suggest that short duration downtime events (perhaps as little as 30 seconds) are not worth measuring.  These undocumented losses are reflected, or more accurately hidden, by a corresponding reduction in the performance factor.

Be careful when setting what appears to be simple policy to document downtime.  A 20 second downtime event that occurs 4 times per hour could quickly turn into 10 minutes a shift, 30 minutes a day, 2.5 hours a week, 125 hours a year.  Rather than recording every event in detail, we recommend implementing a simple “tick” sheet to gain an appreciation for the frequency of failures.  Any repetitive events can be studies and reviewed for corrective action.

Verify the Downtime

One of the advantages of OEE is that it is possible to reconcile the total time – OEE should never be greater than 100%.  Of course this statement requires that the standard cycle time is correct and the total quantity of parts produced is accurate.  So, although all of the downtime events may not be recorded, it is very easy to determine how much downtime occurred.  This will help to determine how effectively downtime data is being recorded.

A perfect example to demonstrate this comes from the metal stamping industry.  Progressive dies are used to produce steel parts from coil steel.  The presses typically run at a fixed “predetermined” optimum run rate.  Depending on the type of part and press, progressive dies are capable running at speeds from as low as 10 strokes per minute up to speeds over 300 strokes per minute.

For ease of calculation, assume we have a press that was scheduled to run a part over an 8 hour shift having two 10 minute breaks.  The standard shift hours are 6:45 am – 3:15 pm and 3:30 pm – 12:00 am.  The company provides a 30 minute unpaid meal break after 4 hours of work.  The optimum press speed to run the part is 20 strokes per minute (spm).  If a total of 6200 parts were made – how much downtime was incurred at the press?

To determine the press time required (also known as earned time), we simply divide the quantity of parts produced by the press rate as follows:

Machine Uptime:  6200 / 20 = 310 minutes

Our planned production time was 8 hours or 480 minutes.  Assuming that company policy excludes break times, the net available time to run the press is 480 – (2 x 10) = 460 minutes.

Calculated downtime = Available – Earned = 460 – 310 =150 minutes

Availability = Earned Time / Net Available Time = 310 / 460 = 67.39%

We can see from the above example that it easy to determine what the downtime should have been and, in turn, we could calculate the availability factor.  This calculation is based on the assumption that the machine is running at the stated rate.

The Availability TWIST (1):

Knowing that press and die protection technologies exist to allow presses to run in full automatic mode, the two break periods from our example above do not apply to the equipment, unless company policy states that all machines or processes must cease operations during break periods.

Assuming that this is not the case, the press is available for the entire shift of 480 minutes.  Therefore, the availability calculations from above would be:

Calculated downtime = Available – Earned = 480 – 310 =170 minutes

Availability = Earned Time / Net Available Time = 310 / 480 = 64.58%

The Availability TWIST (2):

Just to expand on this concept just a little further.  We also indicated that the company provided an unpaid lunch period of 30 minutes.  Since meal breaks don’t apply to presses, the reality is that the press was also available to run during this period of time.  The recalculated downtime and availability are:

Calculated downtime = Available – Earned = (480 + 30) – 310 =200 minutes

Availability = Earned Time / Net Available Time = 310 / 510 = 60.78%

The Availability TWIST (3):

Finally, one last twist (we could go on).  We deliberately indicated that there was a 15 minute break between shifts.  Again, is there a reason for this?  Does the machine have to stop?  Why?

Availability – NEXT Steps

As you begin to look at your operations and policies, start by asking WHY do we do this or that?  The example provided above indicates that a significant delta can exist in availability (close to 7%) although the number of parts produced has not changed.  The differing results are related to policy, operating standard, or both.

If the performance (cycle time or production rate) and total quantity of parts produced data have integrity, the availability factor can be reconciled to determine the integrity of the downtime “data collection” system.  From this example it should also be clear that the task of the data collection system is to capture the downtime history as accurately as possible to determine the opportunities to improve availability NOT just to determine how much downtime occurred.

This example also demonstrates why effective problem solving skills are critical to the success of your lean implementation strategy and is also one of the reasons why programs such as six sigma and lean have become integrated as parallel components of many lean execution strategies.

The Goal:  100% uptime / Zero downtime / Zero lost time /100% availability

Regardless of the measurement baseline used, be consistent.  Exclusions are not the issue, it is a matter of understanding what is involved in the measurement process.  For example, maintenance activities performed during break periods may be a good management practice to improve labour efficiencies, however, the fact that the work was performed during a break period should not exclude it from the “downtime” event history.  We would argue that all activities requiring “equipment time” or “process time” should be recorded.

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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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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