Tag: Integrating Lean

Contingency Planning For Lean Operations – Part III

Contingency Planning for Lean Operations – Part III

 

Deaths spark huge crib recall” was the main headline of today’s Toronto Star (24-Nov-09).  This recall was the result of 4 infant deaths and affects up to 2.1 million units sold.  Click here to access the full article.  This announcement has made headlines throughout North America and is certain to be featured on all of the major network news stations.

Managing a major product recall is likely one of the more significant events where contingency plans are fully executed and developed.  As tragic or unfortunate as the events may be, it is imperative for a company to manage the recall event in professional and responsible manner.  While it may seem difficult to prepare for an event that has not yet occurred, learning to anticipate the sequence of events to recovery and to script are necessary steps to developing an effective contingency plan.

What are the elements of an effective contingency plan?

We will be covering the elements of an effective contingency plan over the next few posts.  Before we get too far into the process, it is important to recognize that one of the critical skills required as part of the contingency planning process is the ability to perform an effective risk assessment.

It is not our intent to cover all aspects regarding risk assessments and analysis as this would require a book in itself.

A newly released book, The Failure of Risk Management – Why It’s Broken and How to Fix It, by Douglas W. Hubbard (copyright 2009) and published by John Wiley & Sons, Inc., provides extensive insight and resources to perform effective Risk Management Assessments and Analysis.  The reasons why some risk management methods fail or are susceptible to failure are also covered in detail.

As exemplified in the opening article, there is no real means to measure the net effect or impact of a recall campaign of this magnitude.  Elements such as Consumer Confidence, Brand Loyalty, Loss of Life, or Warranty are difficult to value in tangible terms.

Unfortunately, there are too many examples of crisis events where the knowledge was available to rectify or fix the situation before any tragic event occurred.  As heard in many workplaces, “Why is that nothing is done until something bad happens?”

An effective contingency planning is not only designed to manage tragic or crisis events, it should also aid to identify potential failure modes that can be captured and addressed before a product is ever released for mass production or to market.  Consider the following two scenarios:

  • Scenario 1: (Highly unlikely …)
    • Jill:  What if the part fails?
    • Jack:  We’ll recall it.
    • Jill:  How will we do that?
    • Jack:  We have an excellent recall management process

What if the dialogue took a different turn as follows:

  • Scenario 2:  (More likely …)
    • Jill:  What if the part fails?
    • Jack:  What could possibly go wrong?  It’s perfect.
    • Jill:  Engineering said it barely passed the tests.
    • Jack:  Well, maybe we should take another look at the design.
    • Jill:  Great, you know we can’t risk a recall.

Developing a Contingency Plan – The Process

1.  Corporate Responsibilities – Charter

If contingency planning ever concerns an individual person in the company directly, it is the Chief Executive Officer or the president who are personally at risk of significant legal ramifications and also the greatest level of exposure.

This past year Maple Leaf Foods experienced a major Listeria outbreak at one of their food processing facilities.  Contaminated product reached the market place resulting in illness and loss of life.  A major recall was initiated and the company immediately initiated corrective actions.  During this crisis, the CEO took personal responsibility for public relations, communicating the strategy, and ultimately overseeing the recovery process.

The CEO or President should be leading the charge for the development of contingency plans and to assure their effectiveness.  To this end, it is also imperative that the team responsible for formulating the plan includes a cross-section of people from across the company.

The CEO or President will also want to assure that everyone is trained to respond to events that pertain their specific areas of responsibility.

2.  Contingency Planning – Form a Team

As we mentioned in our previous posts, contingency planning is an enterprise-wide process.  The collective intelligence of the team is greater than that of any team member.

You should consider the skill sets that may be required to support the team.  Although we are not suggesting that you need to be an expert in probability theory or statistics, someone having exposure to these types of assessment tools or an outside consultant may be worth the effort.

It is not possible for one committee to prepare contingency plans for every area in the company.  When forming teams, how the skills and levels of expertise required to support the team in one area may be vastly different for another area.  For example, Product Engineering and Operations will have different failure modes to contend with.

To ensure the appropriate resources are available, we recommend that  executive management or a steering committee are assigned to oversee the contingency planning and development process.

Based on some of the scenarios cited in this post, it would stand to reason that most CEO’, Presidents, and / or owners are primary stake holders in the Contingency Planning process.

More will follow:

  • Performing Risk Assessments
  • Contingency Planning Tools
  • Do The DRILL
  • Publish
  • Review

Until Next Time – STAY Lean!

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 Integration – Where do We Measure OEE? – Part I

OEE Integration Part IX – Where do we measure OEE?

Our recent posts have included numerous examples to calculate OEE correctly. We also discussed integration of OEE as an effective metric for managing your processes and ultimately how to analyze and use the data to improve your profitability.  We spent little time discussing where this measurement should occur.  OEE can be measured for both manual and automated lines as well as any stand alone operation.

The OEE factors (Performance, Availability, and Quality) are process output results.  The expectation, of course, is to manage the inputs to the process to assure the optimal result is achieved.  Availability, Performance, and Quality can be measured in real-time during production. However, the results should be subject to a due diligence review when production is complete.

At a minimum, it makes sense to measure OEE at the end (output) of the line or process but this is not always ideal.  The complexity of OEE measurement occurs when single or multiple sub-cells are constrained by an upstream or downstream operation or bottleneck operation.  The flow, rate, or pace of a process is always  restricted or limited by a  sequence / process constraint or bottleneck operation.  Just as a chain is only as strong as its weakest link, so too is the line speed limited by the bottleneck operation.

We contend that the “Control-Response” loop for any process must enable immediate and effective corrective action based on the measured data and observations.  Measuring OEE in real-time at the bottleneck process makes it an ideal “Trigger Point” metric or “Control-Response” metric for managing the overall process even in “isolation” at the bottleneck operation.  Any variations at the bottleneck correlate directly to upstream and downstream process performance.

A disruption to production flow may occur due to a stock-out condition or when a customer or supplier operation is down.  While these situations affect or impact the OEE Availability factor, external factors are beyond the scope of the immediate process.

Real-time OEE requires that these events and others, such as product disposition, are reported in real-time as well.  External events are more difficult to capture in real-time and by automated systems in particular.  Operator interfaces must accommodate reporting of these events as they occur.

Reporting PITFALL – After-the-Fact events

If a quality defect is discovered several days after reporting production and all parts are placed on hold for sorting or rework, the QUALITY Factor for that run should be changed to ZERO.  In turn, the net OEE for that run will also be ZERO.  If the system is not changed, the integrity of the data is lost.  This also exemplifies that real-time data can be deceiving if proper controls are not in place.

“Where do we measure?” is followed by “When do we measure?” The short list of examples provided here are likely events that are far and few between.  If this is a daily occurrence, consider adopting the banking policy of, “adjustments to your account will be reflected on the following business day”.  Your process / system is in need of a rapid fix.

OEE is one of the few vital signs or key performance metrics for your manufacturing operation.  As such, measure where you will reap the greatest benefit and focus your attention on the process or operation accordingly.  OEE is as much a diagnostic tool as it is a monitoring tool.

Until Next Time – STAY lean!

Vergence Analytics
Versalytics

Weighted OEE: How To Calculate Total Plant OEE

In this post we will present a simple method to calculate a truly weighted OEE, including weighted factors Availability, Performance, and Quality.

The QUICK weighted OEE method:

Recalling our original definition of OEE, we are measuring how effectively our planned production time (net available time) is used to make a quality (saleable) product.  The weighted OEE then is the total time required to make a quality product divided by the total net available time.

From our examples in the “Calculating OEE” post, the following table summarizes the time required to produce quality products ONLY for machines A, B, and C:

  1. Machine A:  365 minutes
  2. Machine B:  318.75 minutes
  3. Machine C:  254.34 minutes

The total time to produce good quality (saleable) products is 938.09 minutes.

The total net available time for the three machines is 1365 minutes (3 * 455 minutes). 

The total weighted OEE for the 3 machines = 938.09 / 1365 = 68.72%

Calculating the Weighted Factors:

A similar process to the one described above can be applied to the individual factors.  It stands to reason that when the individual factors are multiplied together that we should get the same result.  We will use this to check our answer.

Weighted Availability:

Availability measures machine uptime efficiency.  The definition applied to an individual process also applies to the total of all the machines.  Availability is calculated using the formula:

Availability:  Net Operating Time / Net Available Time

From our examples in the “Calculating OEE” post, the following table summarizes the Net Operating Times for machines A, B, and C:

  1. Machine A:  423 minutes
  2. Machine B:  437 minutes
  3. Machine C:  433 minutes

The total Net Operating Time = 1293 minutes.

The total Net Available Time for the three machines is 1365 minutes (3 * 455 minutes). 

The weighted AVAILABILITY for the 3 machines = 1293 / 1365 = 94.73%

Weighted Performance:

Performance measures machine operating time efficiency when compared to the “ideal” cycle or operating time.  The definition applied to an individual process also applies to the total of all the machines.  Performance is calculated using the formula:

Performance:  Ideal Operating Time / Net Operating Time

From our examples in the “Calculating OEE” post, the following table summarizes the Ideal Operating Times for machines A, B, and C:

  1. Machine A:  373.33 minutes
  2. Machine B:  337.50 minutes
  3. Machine C:  267.17 minutes

The total Ideal Operating Time to produce ALL parts = 978 minutes.

The total Net Operating Time for the three machines is 1293 minutes (See Availability Calculations Above). 

The weighted PERFORMANCE for the 3 machines = 978 / 1293 = 75.64%

Weighted Quality:

Quality measures how efficiently the “ideal” operating time is used to produce quality (saleable) products.  Again, the definition applied to an individual process also applies to the total of all the machines.  Quality is calculated using the formula:

Quality:  Ideal Operating Time to Make Quality Parts / Ideal Operating Time

From our examples in the “Calculating OEE” post, the following table summarizes the Ideal Operating Time to produce Quality Parts ONLY for machines A, B, and C:

  1. Machine A:  365.00 minutes
  2. Machine B:  318.75 minutes
  3. Machine C:  254.34 minutes

The total Ideal Operating Time for Good Parts = 938.09 minutes.

The total Ideal Operating Time to produce ALL parts for the three machines is 978 minutes (See Performance Calculations Above). 

The weighted Quality for the 3 machines = 938.09 / 978.0 = 95.92%

Weighted OEE cross check:

Let’s compare the results.  From the calculations above, the results are summarized as follows:

  1. Weighted Availability:  94.73%
  2. Weighted Performance:  75.64%
  3. Weighted Quality:  95.92%

Now, we multiply the individual weighted OEE factors together:

OEE = 94.73% * 75.64% * 95.92% = 68.73%

You will see the result is the same as the Quick check introduced at the start of this post.

In our next post we will show you how to calculate the weighted factors for each individual process and introduce yet another way to confirm the weighted OEE calculation.

We have created a number of Excel spreadsheets that are immediately available for download from our FREE Downloads page or from the Free Downloads widget on the side bar.  These spreadsheets can be modified as required for your application.

If you have any questions, comments, concerns, or suggestions for a future topic, please forward them by e-mail to leanexecution@gmail.com  We look forward to hearing from you and trust this information will get you going.

Until Next Time, STAY Lean!

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