Software Modeling for Standardized Work

The concept of Standard Work is understood in virtually any work environment and is not exclusive to the lean enterprise.  Typically the greater challenge of standardized work is actually preparing an effective document that adequately describes the “work” to be performed.

The objective of standardized work is to provide a documented “method” for completing a sequence of tasks that can be executed to consistently yield a quality product at rate, regardless of the person who is performing the work.  The documentation typically created usually falls short of this expectation.

The Ideal Model for Standardized Work

We would expect to find examples of well documented standardized work at Nuclear Stations, Military Installations, in Aerospace, and many other places where risks are high and operation sequences are critical.  High velocity, lean organizations recognize that a disciplined process approach is the key to discovering opportunities for improvement and to support future “problem” solving activities if required.

Computer programs are perfect models of standardized work in action.  They perform the same tasks day after day, collecting, storing, and processing data.  We have certain performance expectations although we seldom understand the inner workings of the programs themselves.

This is certainly true for the computers we deal with in our personal lives such as mobile phones, instant banking machines, GPS mapping systems, or the many “gaming” programs that people play.  Our interactions with the “program” are limited to the HMI or Human-Machine-Interface and represents only a tiny fraction of the thousands of lines of computer code that are executing the transaction requests in the background.

The Software Development Model

Although few of us may ever write a program, we do understand that every instruction or line of code in a program is critical to the successful execution of the program as a whole.  Every line of code represents a specific instruction, process sequence, or step that must be executed by the computer.  Similarly, standardized work identifies the specific steps that must be followed to successfully complete the task.

Any time a computer system “goes down” or critical error occurs, someone in the IT department is looking for the source of the problem.  The software is typically written to at least provide a hint as to where the problem may be.  In some cases the solution may be as drastic as rebooting the system or as simple as reloading the specific application.

We should be able to perform a similar analysis when a process fails to perform to expectations or when we are confronted with quality issues or other process disruptions or failures.  The ability to consistently repeat a sequence of steps is directly correlated to the quality and level of detail described in the standardized work document.

Aside:  An example from the Quality department:

Gage Repeatability and Reproducibility studies, also know as Gage R&R studies, are often used to validate the effectiveness of a measurement system or method (fixture or equipment) for a specific application.  If the Gage R&R result is less than 10%, the gauge or fixture is deemed to be acceptable; greater than 30% renders the measurement system unusable for the application.    The results can be evaluated statistically to determine or differentiate whether the “problem” is repeatability (equipment variability) or reproducibility (operator variability).

When the measurement system fails to meet the requirements of the application, a significant amount of time and effort is expended to achieve an acceptable result.  The gauging strategy is reviewed, including part / fixture net locations, quantity of net pads and / or pins, net pad and / or pin sizes, clamping sequences, and clamping pressures; all efforts to improve the measurement system.  Instructions are revised and operators are retrained accordingly.

In contrast, we seldom see the same level of time and effort expended to develop, analyze, test and document standardized work at the machine or station where the work is actually being performed.  Although the process may be improved to yield a quality product, the method or work instruction to achieve a consistent result is not adequately described or defined.

Understanding the tasks to be performed and the time required to perform them is essential to determine effective process cycle times (rates) and also to understand where changes to the process may yield improved performance.  This is of particular importance for companies using OEE as a key process metric.

Note:  an indicator that standardized work methods should be reviewed occurs when excuses for poor performance are attributed to a “new operator” or “steep learning curve”.

Extending the Program Model Concept

We can all appreciate the “built-in” or inherent discipline of computers executing thousands of lines of code in the same sequence every time the program runs.  To add complexity to our model, consider the discipline and learning that is necessary to write the code itself.  The software development team must understand the purpose of the program, how it will be used, design and create a user interface, determine programming algorithms to achieve the desired results and functionality, and ultimately they must write the code that will perform these functions.

Anyone who has attempted to write a program, or knows someone who has, will also be familiar with the term “DEBUG”.  There may be at least as many hours spent testing and debugging code as there are when writing it.  Even after hundreds of hours of testing, some “Bugs” still make it into the real world.  Microsoft’s bug laden operating system releases have been the target of Apple Computer advertising campaigns for this very reason.

Some code may function without error when executed in isolation and some bugs may not be discovered until the module is interacting with the program as a whole.  In this regard, it is also important to consider the potential of interactions with other processes when developing standardized work.  Upstream and downstream operations may have a direct impact on the work being performed. 

The software development team must select the programming language that will be used to develop the final code and the individual programmers must also follow and understand the syntax and language protocols.  Although the product of the software development team is the “executable” program that the computer will run, we can be assured that the process for arriving at this final product is also quite rigorous.

Although we never get to see the native or original code, the modules are likely highly optimized, commented thoroughly, and well documented.  These comments are technically “non-value added” steps in the program, however, they usually describe the scope and purpose of the procedure or clarify any code intentions or algorithms.  These comments are valuable when debugging may be required or when the code is subject to future reviews.

The discipline of software development is not too far from the level of discipline that should be in place to develop standardized work.  The quality of standardized work processes would improve dramatically if each sequence was given the same level of scrutiny as a single line of code.

Making Improvements with Standardized Work

You may be wondering how flexibility exists in an environment of extreme discipline and rigid rules.  It is actually the rigidity and discipline that supports or encourages flexibility.  The discipline is in place to encourage managed change events without compromising current process knowledge or levels of understanding.  A well-defined process is much easier to understand and therefore is also easier to analyze for improvement opportunities.  The level of understanding should be such that a quantifiable margin or level of improvement can be predicted.

With reference to our software model, you will appreciate that the efficiency or speed of the program is dependent on the methods or algorithms that programmer used to develop the solution.  How many times have you stared at your computer wondering “what’s taking so long?”  The timing for a simple data sort can vary depending on the method or sorting algorithm chosen by the programmer.

The very language elements or functions that the programmer uses will have a profound effect on program execution time.  Many programmers have developed and use high precision “timing” functions to help optimize their code for efficiency and speed of execution.  Machine language level programmers are likely to know how many clock cycles each instruction requires.

Understanding the “process instructions” at this level creates very specific challenges with predictable outcomes and degree of certainty when changes are considered.  Changing an algorithm is quite different from simply changing a line of code within a specific function.  However, the scope, purpose, and impact of the change can be clearly defined and assessed in advance.

Last Words:

One of the more significant lean developments in manufacturing was the introduction of Quick Changeover and Single Minute Exchange of Dies (SMED).  The setup time reductions that have been achieved are truly remarkable and continue to improve with advances in technology.

When Quick Changeover and SMED programs were first introduced, most companies did not have a defined setup procedure or process.  The most significant effort was spent developing actual setup instructions:  identifying tasks to be completed, determining the sequence of events, who was responsible, and when they could be performed.

Ultimately external and internal setup activities were defined, setup teams were created, specific tasks and sequences of events were assigned and defined, and setup times were reduced from hours to 10 minutes or less.

Standardized Work is a fundamental element of Lean Manufacturing.  As notes are the language of musicians and make for great songs and sounds, so too is Standardized Work to a Lean organization.

Until Next Time – STAY Lean!

Improving OEE: A Hands On Approach

We have explored Overall Equipment Efficiency (OEE) from several perspectives and how it can be used as an effective performance metric.  The purpose of measuring and monitoring OEE, at a minimum, should be three fold:

  1. To ensure the current performance levels are sustained,
  2. To identify new opportunities for improvement,
  3. To assess the effectiveness of current improvement initiatives.

The Culture of Continuous Improvement and Innovation

A continuous improvement “mindset” must be part of the organizational culture to achieve maximum results.  Too many companies charge the engineering department or some other “arm” of the organization to generate the ideas that can be implemented to improve availability, performance, and / or quality.  We strongly urge you to include everyone in the improvement process, especially the very people who perform the tasks on a daily basis.  Why?  The simple answer is, “They are the eyes and ears of the process”.

Despite some of the old school thinking that may persist in industry, most people take pride in their work and want to do a good job.  OEE is as much a performance metric for the individuals on the shop floor as it is for the management and leadership of the company.  Even the most educated doctor will ask the patient what the symptoms are as part of the assessment process.

While it may be difficult to assess what level of improvement can be achieved, it has been suggested that world class OEE is 85%.  We suggest that you establish a reasonable baseline and determine relative improvements accordingly.  The baseline you use should be comprised of two key components:

  1. Historical data for OEE and each factor (Availability, Performance, and Quality)
  2. A detailed Standard Operating Procedure for each process under consideration

Getting Started – Collect and Communicate Data

Almost every continuous improvement (CI) activity or project is accompanied by a list of actions that must be implemented.  Where does this list come from?

There are at least two very basic approaches to getting the improvement process underway:

  1. Collect and analyze data from the current process
  2. Set up a FLIP Chart at the line or machine

Step 1 should be fairly straightforward.  The premise here is that OEE data is already being collected and analyzed on a regular basis.  Step 2 may not be as familiar to you.

FLIP Charts

This is probably one of the most fundamental and basic data collection tools available on the market.  This approach may seem overly simplistic but the objective is to keep it simple and effective.


  1. Data collection in “real time”
  2. Anyone can add to the List
  3. Anyone can update the List
  4. Readily Available to ALL
  5. Writing Skills ONLY
  6. Instant Feedback
  7. Highly Visible

What do we record on the FLIP chart?  We have experienced the best success with the following simple format.  At the top of the FLIP chart write down Today’s Date and Shift, then setup the following headings:

Time   Problem/Concern   Assigned To   Task Completed   By (Initials)

Any time an event occurs or an opportunity arises for improvement, simply enter the appropriate data under the headings shown.  The flip chart can also be used to track progress – INSTANTLY.  Whenever a task is completed, the person responsible for the “fix” simply enters the time / date and their initials.

FLIP Chart – Built in Accountability

Using the flip chart as a living “action item list” introduces accountability from all levels to the process on the shop floor.  As tasks or actions are completed, everyone will see that the concerns are being addressed causing the improvement cycle to continue and reinforcing the value of everyone’s input to the process.

Our experience has shown the FLIP chart to be one of the most engaging improvement processes on a continuing basis.  Improvement history is readily available on the shop floor.  No complex searches, computer programs, or advanced skill set is required to see what is going on and what is being done about it.  As much as we don’t like to put problems on display, you may be surprised how impressed your customers are with this type of interactive CI process.

The FLIP chart is a very primitive but effective tool for collecting data and communicating results.

Improving OEE

Since OEE is comprised of three elements, it stands to reason that at least three major improvement initiatives exist:  Availability, Performance, and Quality.  How do we go about improving these elements?

Availability: Start with a downtime assessment:

  1. Categorize Events (Planned vs. Unplanned)
  2. Frequency / Occurrence Rate
  3. Duration
  4. Type:  Planned, Preventable, Predictable, Unplanned, Unknown

From our previous discussions on Availability, the known “Planned” events may include such change events as materials, tooling, and personnel (shift changes and / or breaks).  Improving availability requires the elimination of UNPLANNED events and reducing the duration of PLANNED events.  Successful improvements can only be developed and achieved if there is integrity in the baseline information and data.

Implementing SMED (single minute exchange of dies) is one strategy to reduce the duration of die changes.  A detailed die change process is used to determine the activities that can be performed while the machine is still running (External Events) and those that can only be performed while the machine is down (Internal Events).  Further assessments are conducted to determine what improvements are possible to reduce the duration of the internal events.  Such improvements may include hydraulic clamping, quarter turn screws, standardized shut heights, standardized locating pins, standardized pass heights to name a few.

Scheduling sequences may also be an important factor in the change over process.  If a common material (type or color) is used for two different parts, it may be more effective to run them back to back through the same machine.  Tooling may be shared among different part numbers and would require less change over time if they were considered as a product family for scheduling purposes.

Policy changes and capital investments are easily justified when you are able to demonstrate the improvements using a “plan vs actual” strategy that is complimented by data and a standard operating procedure.

Performance: Improving performance is not to be confused with reducing the process time (making it faster).  They are two different activities entirely.  If the original cycle time or process rate was calculated correctly, then 100% performance should be achievable right?  Once again, the answer to this question depends on company policy and the method that was used to establish the standard.

Our purpose is not to introduce more confusion, but rather, to make sure that whatever policy is in place is clearly defined and understood.  Remember, the only real industry standard for OEE is the formula used to calculate the result:  A x P x Q.  A standard definition or criteria for determining the individual factors does not exist.

The cycle time for an automated process can easily be determined by measuring the output without disruption over a known period of time.  Is this consistent with company policy?  Is the standard cycle time based on the stated nameplate capacity (rate) or is it based on the actual achieved (optimum) cycle time?

A “button to button” cycle time may be established for a manual operation in a similar manner.  Although it may be perceived as a flaw, the button to button analysis may not necessarily consider container changes or restocking of components that may be required from time to time.  If these “other” tasks are not factored into the cycle time, then it would be impossible to achieve 100% performance unless someone other than the operator was made responsible for those activities.

Start with a Performance Assessment

  1. Confirm company policy and methods for calculating the cycle time.
  2. Confirm the Cycle Time or Production Rate (Time Study)
  3. Compare the Actual versus Standard Operating Procedure
  4. Review the process performance history and data records.
  5. Equipment Condition Assessment – Preventive Maintenance
  6. Process Type:  Automation, Semi-Automation, Manual (Human Effort)
  7. Confirm Reporting Integrity

Only after you have reviewed the data and discussed the opportunities with the team will you be able to develop a performance improvement plan.

Using the “button to button” manual process described above, we already indicated that a person other than the operator could be responsible for restocking components and changing containers to allow the operator to run the machine without interruption.  There may be other activities as well that could be performed someone other than the operator.  A detailed Standard Operating Procedure complete with clearly defined steps (step tasks) and timing for each is the best tool available to improve performance.

Is it possible to change the method or sequence of events that the operator is following to reduce the time taken to perform a step task.  Is the operation “handed”, in other words, does it favor right versus left handed people?  Is the material arranged in such a way as to optimize (minimize) the operator’s movements during the cycle?  Are all operator’s performing the step tasks per the standard operating procedure?  Is the machine itself performing at the optimized cycle or is it running at a slower speed due to electrical, mechanical, or fluid faults?

Some of the activities identified may result in speed increases that will lead to performance improvements relative to the current standard.  Again, company policy should dictate when and how standards are to be updated.  If the standard is updated everytime the cycle time is reduced, how will you recognize the improvement?  We would recommend resetting the standards annually in conjunction with the new fiscal year.  The new performance levels should also be reflected in the business plan.

Quality: This is perhaps one of the easiest to factors to define and may be one of the more difficult factors to improve.  Again this will depend on the definition or criteria used to calculate the Quality factor.  The typical definition adopted by most manufacturers states that any parts failing to meet First Time Through quality criteria include those designated as scrap, test, rework, sort, and / or hold.  In other words, First Time Through quality applies only to those parts that are considered acceptable at the point and time of production.

When do you start counting?  Should set up parts be included in the Quality definition?  We would argue against including set up parts in the quality calculation, however, that doesn’t mean they shouldn’t be accounted for because the material loss is a real cost to the company.  We would define set up time as starting from the last good part produced to the first good part produced for the next job in.

The objective of any Quality improvement strategy is obviously zero defects.  The task is getting it done.

Quality: Start with a Quality Assessment:

  1. Review Process Failure Modes Effects and Analysis (PFMEA)
  2. Review Current Quality Control Plans (Inspection Requirements)
  3. Review and Analyze Quality Performance Data
  4. Review scrap and rework analysis
  5. Identify Top Opportunities (Pareto Analysis)
  6. Initiate Problem Solving Activities (DMAIC, PDCA, PDSA, IDEA Loops)
  7. Execute problem solving strategy
  8. Update Lessons Learned and Best Practices

The ultimate goal for any quality program is to achieve a level of zero defects.  A second, closely related goal is to eliminate, reduce, and control variation in our processes.  Variation and defects are directly correlated and are typically quantified by statistical modeling tools such as the normal distribution or bell curve.  Many tools are available to study and analyze the various attributes of a process to effectively determine the root cause for a given defect.

Some of the many problem solving methods and tools include 8-Discipline Analysis, 5 Why, Fault Tree Analysis, Cause and Effect Diagrams, Pareto Analysis, Design of Experiments (DOE), Analysis of Variance (ANOVA) tools among others.

Next Steps

We have identified the various methods to generate improvement activities. The key to success is developing the action plans and executing them in a timely manner.  This is the critical part of the improvement process.

A word of caution:  Don’t confuse activity with action.  Too many times, the data collection and study processes consume all the resources and more time is spent on data presentation than real analysis.  The goal is to improve the process, solve the problems, and eliminate the defects.

No Input Change = No Output Change

Lessons Learned and Best Practices

It is possible that the wrong process was selected for the product being manufactured.  This may range from the actual tooling to the very equipment that is used to run it.  It is also possible that the capability of the machine was overstated or over-rated prior to purchase.

Maintaining a lessons learned database is one way to make sure that we don’t make the same mistake twice.  It can also serve as a future reference when developing standards for future products or processes.

Perhaps a product or process requires a technology that simply doesn’t exist.  Could this be the stepping stone for a future research and development project?  How do we take things to the next level – the break through?

Until next time – STAY lean!

Twitter:  @Versalytics

Please feel free to forward your questions or comments to us by e-mail at LeanExecution@gmail.com

OEE for Multiple Parts – Single Machine (Multipart Processes)

How to Calculate OEE for Single Machine and Multiple Parts.

Flexible manufacturing provides the advantage of producing many different parts on the same piece of equipment.  The same is true for processes such as stamping presses, molding machines, or machining operations.

The first question most often asked is, “How do we calculate OEE for a piece of equipment that is capable of manufacturing multiple parts?”  The overall OEE for a stamping press, molding machine, machining process, or other “multipart” process is easily calculated using the same formulas presented in our previous posts “How to Calculate OEE” and “Practical OEE“.

We presented three machines running at various rates and producing unique products.  We demonstrated how to calculate the OEE for each part individually and for all parts collectively.  The machines A, B, and C could very easily be parts A, B, and C running on one machine.  The application of the OEE formulas presented for these three machines is the same for multiple parts running on the same machine.

We have prepared two Excel spreadsheets that demonstrate how to calculate OEE for a single machine that produces multiple parts.  We have also created a separate Excel spreadsheet that will show you how to calculate OEE for Multiple Departments and Multiple Machines running Multiple Parts.

Calculating OEE for any period of time, department, or group of equipment is a simple task.  With the understanding that OEE measures how effectively Net Available Time is used to produce good parts at the ideal rate, the formula for any OEE calculation follows:

OEE (Any Category) = Total SUM of IDEAL Time / Total SUM of NET Available Time

Once this basic premise for OEE calculations is clearly understood, any combination of OEE summaries can be prepared including OEE summaries by Shift, Operator, Manager, Division, Process, and Process Type.

FREE Downloads 

We are currently offering our Excel OEE Spreadsheet Templates and example files at no charge.  You can download our files from the ORANGE BOX on the sidebar titled “FREE DOWNLOADS” or click on the FREE Downloads Page.  These files can be used as is and can be easily modified to suit many different manufacturing processes.  There are no hidden files, formulas, or macros and no obligations for the services provided here.

Multipart OEE – Confronting the Challenges

Most manufacturing environments are challenged with the task of minimizing inventories requiring more frequent change-overs or setups.  By far, the greatest challenge of multipart equipment is managing the change-over process and is usually reflected in the OEE Availability factor.

We recommend including setup or change-over time as part of the unplanned downtime calculation.  Then, by definition, one method to improve Availability is to reduce change-over or setup time.  Reductions in change-over time will also be reflected by improved Availability.  The Availability factor is now a useful metric for tracking improvements.

According to our definition, change-over time or setup time is measured from the end of the current production run (“the last good part made”) to the start of the next production run (“first good part produced”).  We have worked with some manufacturers that decided to do change-overs on the off shift so that they could avoid the down time penalty.  They clearly didn’t get the point – deferring the time when the change-over is performed doesn’t change the time required to perform it.

Several programs such as SMED (single minute exchange of dies) are available and, when coupled with best practices for quick die change (QDC) or quick tool change techniques, can greatly reduce the time lost during your tool change events.

We will consider posting best practices for SMED or QDC and would welcome any reader comments in this area.

We always welcome your feedback and comments.  Feel free to send us your questions or comments to leanexecution@gmail.com

Until Next Time – STAY Lean!