Six Sigma | Never build a control chart this way! | Green Belt 2.0® Lean Six Sigma | fkiQuality HD

[@fkiQuality]

Control charts have been made unnecessarily complicated and downright defective by people who don't understand their origins. For instance, some teachers say that the data has to be normally distributed - not true, as the control chart theory is independent of any statistical model, such as normality. Or that the process has to be in control before using this type chart - false, since the purpose of the tool is to detect out if control situations.

[@shannonvanpatten8774]

It's good to know how to not to create the limits of a control chart along with the correct way. It was great to visually see that incorrect limits does not help see any abnormal behavior.

[@aleksandardejkovic6496]

Nice clarification between the Sigma lines and Standard Deviation.

[@EricGavlick-r7z]

Great visual and explanation of how to build a control chart the correct way to detect abnormal process behavior.

[@jahairasantillan9930]

this is a good explanation on what the difference is between UCL and LCL

[@GregBoal-o2m]

good explanation of the differences of std deviation and the 3 sigma lines and why they can be a less advantages way to chart them

[@KyleNwogu]

This was informative, it teaches how to build a control chart the correct way to be able to observe process behavior so that abnormal behavior can be observed if there is any.

[@KristinaPostula]

A good reminder that standard deviation and sigma, as used in the control charts, mean different things. We shouldn't set up control charts to 3 standard deviations, but the UCL and LCL limits are based on variation from one sample to the next (3 sigma lines).

[@DannyG-d2f]

It's good to know that we should be careful of the difference in the word "sigma" depending on the context of how it is being used

[@AndyPostula]

Good explanation on how to properly prepare a control chart so a normal process behavior is displayed.

[@fkiQuality]

Keep in mind that the control chart user wants to display both normal and abnormal behaviors so that it knows to take action when it sees abnormalities and to leave the process alone when it shows stability.

[@donnalevy8455]

Great visual explaining sigma and standard deviation and how to correctly use the control chart. I liked the side by side visual of showing the correct and incorrect control charts. It was easy to understand.

[@amandafreeze-d8l]

Good example of how people can over complicate the assessment of data

[@JoeyBethea]

Control charts are a good judge to determine whether a process is stable and detects changes early for timely corrective actions. Thanks for the info!

[@joshklinzing4608]

This helps us focus on control charts and UCL, x-bar, and LCL. It seems to me the words and labels of standard deviation, deviation, s, and sigma have taken on additional meanings and applications as the concepts behind them get (sometimes incorrectly) applied to processes. The "sigma" of a process is not the standard deviation (represented by the greek letter sigma), and as we talk about deviation and variation, it gets tempting to apply a normal distribution and it's properties to everything - we're looking for connections. Here, they don't exist. Stick with the way control charts are correctly built and use them and their terminology for what they are meant to represent.

[@fkiQuality]

Josh Klinzing, great comment. Control charts have been made unnecessarily complicated and downright defective by people who don't understand their origins. For instance, some teachers say that the data has to be normally distributed - not true. Or that the process has to be in control before using this type chart - false, since the purpose of the tool is to detect out if control situations.

[@drtonyburns7321]

Except that it is rubbish. "Six Sigma Champions are con men" “All you have is smoke and mirrors” - Creator of Six Sigma, Mikel Harry 91 % of Six Sigma companies have trailed the S&P 500 (Qualpro survey). Six Sigma’s once best reference, GE, has thrown the trash out. An 8 yr study at Ford showed an average of 1 in 5 parts defective AFTER improvement for “successful” Six Sigma projects. There is never justification to stray from the giants of Quality Dr Shewhart, Professor Ishikawa, Professor Lewis, Professor Deming, Dr Taguchi and Dr Wheeler, for the lunacy of Six Sigma’s con man. How the Six Sigma fraud was started: kzbin.infoFPJCS46nexY Lean was tacked on to prolong the Six Sigma Scam. 98% of LSS implementations FAIL (IW survey)

[@jaimesnodgrass5049]

I like how this showed the side by side comparison to show that the data can be skewed by utilizing the 3s control chart and utilizing the correct control chart.

[@mattmack8103]

Great visual on how confusing +/- sigma with sigma can be and the effect on control limits differ between the two.

[@douglasomachel2284]

It's great seeing these models of correct versus incorrect running side by side for easy comparison. Thank you.

[@BeatriceDosu]

Great explanation of the difference between the Sigma lines and the standard deviation. The control chart gives you a visual representation of data over time. It shows whether a process is displaying abnormal behavior .

[@ChristopherStefan]

Very helpful video showing the correct way to prepare a control chart. I've seen the chart prepared using standard deviation to determine the UCL/LCL before and didn't realize this was wrong until it was discussed in the Lean Six Sigma course.

[@CjRodriguez-nn3vk]

I can see how there can be confusion with using standard deviation when creating a control chart. But why use the word sigma?

[@fkiQuality]

Good question! I also think that the term is used in too many confusing ways. This is why, in class, I distinguish between "s", the global standard deviation, and "Sigma(x)," the measure of dispersion within the samples that is used to calculate the UCL and LCL.

[@joshturnbull1850]

I left Tuesday's class thinking the UCL and LCL were the same as +/- 3 sigma. This video really helped break it down and explain the difference.

[@nikiansell9949]

I never realized how using the 's' in your calculator could be that detrimental to your UCL and LCL. This could throw everything else off. Great tips in this video!

[@Jaguzma2]

Great visual on the difference of using the standard deviation on excel.

[@GregBenz-de7nt]

Very good explanation of the difference in meanings between the 1,2 & 3 sigma lines and the sigma used to show the standard deviation

[@brigittedickey3298]

I like how the video shows a visual chart. Control charts shows variation of a process when built correctly.

[@charlesbonham8974]

Good graphic explanation of UCL/LCL using 1/2//3s lines to study control chart value behaviors.

[@jeremya5241]

In addition to learning about how to make control charts, I like that I am starting to understand how they are misunderstood and misused.

[@christopherscott3264]

Again, I like how these concepts are explained in a visual way. Makes it far easier to grasp and 'see' how data is used.

[@joycestadter945]

Very helpful summary of control charts

[@jasonglatz232]

The control chart is a great tool. In class several control charts were reviewed. Understanding the control limits and identifying your targets of the natural occurrence. The process may show that the operator is not incorrect but the process experiences out of control measures.

[@jamesmcelwee5666]

I will be sure to refer to this later. I took a couple screenshots to aid me during exam prep. It is a useful reminder!

[@janayhayes255]

Great demonstration

[@hemmamistry7743]

Remembering the formulas are important to distinguishing the difference between the two and making sure that the control charts are drawn using the +/-2.66mr formula and not the standard deviation.

[@adammademann4414]

Also really like the side by side demonstrations of the correct and incorrect control charts. The biggest and most obvious takeaway for me here is, and not to copy Francisco's summary word for word, but to NEVER use S (sigma) when calculating control limits in a control chart.

[@slee3249]

i like how control chart gives you a visual representation of the data over time.

[@christinasheehan3852]

The explaination of sigma and standard deviation in this video was very clear and I enjoyed the visual of the effects of using sigma incorrectly on thr control chart showing the UCL and LCL with the range between the two spread out.

[@ernestbroom9995]

This video helped to understand how variables inside the control limits could still mean there is an abnormal behavior. Before this video I was under the impression only if variables were outside the control limits would they be abnormal.

[@mmaphefoseseni6625]

This is golden information as data accuracy is one of the biggest challenges when working with data especially when looking to derive insights. It is important to know of every little bit of tweak involved when using constants in calculations.

[@drtonyburns7321]

Golden garbage. The guy has no clue. Read Shewhart. "Six Sigma Champions are con men" “All you have is smoke and mirrors” - Creator of Six Sigma, Mikel Harry 91 % of Six Sigma companies have trailed the S&P 500 (Qualpro survey). Six Sigma’s once best reference, GE, has thrown the trash out. An 8 yr study at Ford showed an average of 1 in 5 parts defective AFTER improvement for “successful” Six Sigma projects. There is never justification to stray from the giants of Quality Dr Shewhart, Professor Ishikawa, Professor Lewis, Professor Deming, Dr Taguchi and Dr Wheeler, for the lunacy of Six Sigma’s con man. How the Six Sigma fraud was started: kzbin.infoFPJCS46nexY Lean was tacked on to prolong the Six Sigma Scam. 98% of LSS implementations FAIL (IW survey)

[@sherisezynel5048]

This video was very informative on what not to do when building a control and what to do to create a valid control chart. Thank you. =)

[@ryanperlic4567]

Interesting with the use of sigma in several different meanings how it can affect your control chart interpretation.

[@insertwords10791]

Good to know the difference between USL/LSL and UCL/LCL, and how to assess within them. I'm not sure I was ever made aware of the difference between the two, and how they can be used to better understand production/process behavior.

[@fkiQuality]

Please notice that the video does not discuss USL/LSL but rather how to calculate UCL/LCL correctly instead of the usual, wrong way.

[@JamesBehn-pl4li]

Very informative video showing how using three-standard-deviation limits rather than three-sigma limits in control charts is incorrect. Using three-standard-deviation limits widens the control limits and may not show abnormal process behavior.

[@ajvarg1882]

Since control charts are about data set across a periodnof time, it makes sense that the limits and standard deviations would be determined as time goes by, not before.

[@fkiQuality]

The limits are set after the "learning" period of the control chart, that is after obtaining the first 10 to 20 observations that show the behavior of the process. Once set, they are not changed unless specific conditions are met, such as a change in the process (new machine, new material, ...).

[@jeffreysundwall7812]

I see the value of having the +/- sigma lines. It can offer us a tool to investigate a process that is 'in control' but also could be trending/having problems that we are unaware of. I think that I need a bit more clarification on this concept.

[@nsmith9976]

I would agree that the UCL and LCL should not also be referred to as the +/- sigma control limits. Why apply a dual meaning to a term. i.e. Sigma. This just blurs the lines of understanding between sigma and standard deviation and doesn't advance the logic. USL and LCL works for me.

[@JacobReuter28]

Great video that really shows that the LCL and UCL are different than the +/- 3 sigma or standard deviations.

[@nicholaspesek5902]

Its good to know we shouldn't use calculators for this. This video helped me understand 3+- sigma in relation to control limits and how not to create a control chart.

[@jdpatt904]

great explanation

[@frankalessi3490]

Very True. Many times, the easiness of having at hand a quick button to get anything done immediately, it fails the true purpose of the aimed goal. In this case, using pre-set formulas, like the stdev in excel, won't help in detecting the abnormal behavior of the analyzed individual variable....

[@denisek743]

I also feel that the visual display helps solidify the necessity of building control charts using upper and lower control limits versus 3 times the standard deviation. It shows how “off” it really is!

[@kristinwerner2431]

Thank you for the explanation-making a mental note.

[@shyamkumarnarayana6110]

Video shows proper use and representation of control charts

[@julianmcdonough1590]

Good to know that there are other formulas that create a different picture. I prefer using the most conservative methods to avoid inflating results.

[@johnsciortino7217]

I can follow the control chart and think I have the understanding of how it works except for how the UCL and LCL moved as more was added. Hoping that can be gone over a little in the class tomorrow.

[@patriciazuno1694]

We've talked about not managing data correctly and the consequences of it, and now we've seen how misunderstanding the calculation portion of the UCL and LCL can also lead to complications.

[@Bittersweetdstny]

This video outlines the difference between the different sigmas and the -/+ or LCL and UCL. It's important to understand the difference, otherwise your calculation will be off. Now you know how to correctly prep your control chart.

[@ryanw1633]

Great review

[@tedkozelka203]

This video helped clear up a major question I had: UCL/LCL is based on proven observations of organizational behavior. Also, the use of 1s/2s/3s lines is a reference, not an actual standard deviation (easy to get confused).

[@drtonyburns7321]

NEVER use 1s/2s/3s "Six Sigma Champions are con men" “All you have is smoke and mirrors” - Creator of Six Sigma, Mikel Harry 91 % of Six Sigma companies have trailed the S&P 500 (Qualpro survey). Six Sigma’s once best reference, GE, has thrown the trash out. An 8 yr study at Ford showed an average of 1 in 5 parts defective AFTER improvement for “successful” Six Sigma projects. There is never justification to stray from the giants of Quality Dr Shewhart, Professor Ishikawa, Professor Lewis, Professor Deming, Dr Taguchi and Dr Wheeler, for the lunacy of Six Sigma’s con man. How the Six Sigma fraud was started: kzbin.infoFPJCS46nexY Lean was tacked on to prolong the Six Sigma Scam. 98% of LSS implementations FAIL (IW survey)

[@jennifersacksteder9846]

It was interesting to realize that i shouldnt use the S on my calculator. Im glad it went through the example on the right way to do it.

[@alanharker2433]

I definitely see how using this chart the wrong way could result a huge negative impact on a business. I look forward to using this in future projects.

[@xxqqff]

When should you calculate new control limits to test against and when should you carry the current control limits into a new test? The demonstration in th video shows the limits being developed as the test is run, should the limits always be redeveloped when testing or should there be a baseline that is consistently referenced?

[@bradhentz7102]

I know this is beyond the scope of this video, but if using 3s "is a totally different concept" what value/purpose does the 3s method serve? What does it reveal? In being a "totally different concept" it doesn't mean that it is useless/bad but rather not pertinent/useful in regards to an accurate control chart and evaluation of a process. When would using 3s be appropriate?

[@fkiQuality]

Building a control chart using 3 standard deviations to measure the distance between the control limits and the average is following the wrong method. It is never appropriate, but a common mistake.

[@bradhentz7102]

So, to clarify, it is more than a totally different concept. Rather it's an invalid one that serves no purpose other than to cloud/confuse the creation of a control chart?

[@fkiQuality]

Brad Hentz the standard deviation must not be used to calculate control limits, but it serves the purpose of measuring the dispersion of a data set.

[@nathanfey6835]

Thanks for clarifying the difference between std devs and 3 sigma.

[@antrioneday1272]

I have used a control chart to help me maintain a particular process for many years. I recall asking why would you question data that shows a number of consecutive points in line with the average. I didn't realize that the average in your example may not have been the target. Also, should you question an outlier if it is only one point that occurred some time ago?

[@sheiladwyer6482]

With the same word such as sigma reflecting multiple meanings, you can see how you could use it incorrectly if you are not careful. You point out the distinction about the control chart and measuring the variability, using the moving range and calculating the LCL and UCL (not to confuse this with the standard deviation). Important distinction about using the correct formula.

[@kennethmckillip3983]

I agree with David,s comment below. I thought I had a good understanding, but am now confused after this video. Why was sigma chosen for the lines in between the UCL and LCL? Sigma was already in use for standard deviation. Or was it visa versa?

[@nathanstratton7918]

Just because a specific data point is within the control limits, does not mean there is no concern. If data gets close to these limits, more analysis should take place

[@michaelparks8673]

Control charts when built properly will show the variations of a process. Variations outside the upper or lower control limits show a need to investigate cause.

[@cjtrumpeter]

A lot of good points here, especially the misrepresentation of sigma and LCL/UCL

[@stacieevans139]

the control limits are not the standard deviation rather they are the variation within the specific data set. using just the standard deviation ignores the data variation and does not accurately reflect the actual control limits of the specific data set.

[@mayraambriz9894]

preparing by next class..... from this it looks like no one table gives you the exact reasons for those out of control points in the process

[@DavidRoberg]

Bottom line, use the right formula! I'm not sure if I'm more confused now or less :)

[@jerryyedlinski3186]

Hi, I guess the simple question is why do we “sometimes” call the UCL/LCL 3-sigma? However I am assuming this is why the control limits are calculated using the 2.66 not 3. I can clearly see it will be our responsibility to verify how the control limits are calculated before we start any data observations.

[@karimerrills207]

What I learned that just because data falls within the limits it doesn't mean there isn't something abnormal occurring

[@domingomoccia2038]

I have been using 2 Standard Deviations to establish the UCL and LCL . Now I know the correct way to do it

[@florahatzis5019]

Adding the +,- 3 sigma to the Upper and Lower control limits would have made me think the values are the same, good differentiation.

[@RichardThiel-y5j]

So, as was said early in the training, 'Trust the data.' Let it determine the appropriate UCL and LCL (using long-proven multipliers) instead of applying standardized sigmas.

[@fkiQuality]

The key concept here is that the UCL and LCL are calculated from the data using the measure of dispersion within the samples Sigma(x).

[@renztabiliran8131]

Just wondering about the math where the constant of 2.66 came from.🤔

[@fkiQuality]

2.66 comes from some scary-looking triple integrals ! Seriously, it is the adjusting factor that converts short-term (also known as "within") variation nto long-term (or "between") variation.

[@ronaldtucci6091]

Don't we want to limit the standard deviation of a process? First get the process in control and than limit the deviation. I am a little confused.

[@Student-ws8wg]

Using STDDEV to calculate movement will create insensitive and too wide control limits.

[@investing4legacy153]

Simply put, use the correct formula when creating a control chart. Nice reminder of an easy mistake that can be made when making these

[@karlajohnson8017]

Important concept that I could see could be confused

[@danielarcher9175]

Interesting. I can see how inaccurate information can change the end results.

[@dwartneywortham2353]

By watching this video I have done a lot of charts the wrong way.

[@fkiQuality]

The great statistician Donald Wheeler, lists a few myths about how to construct and use control charts. The following is from his 7 Sep 2011 Quality Digest article "Myths About Process Behavior Charts." 'It has been said that the process must be operating in control before you can place the data on a process behavior chart ... there are correct and incorrect ways to compute the limits ... The most common of the incorrect ways of computing limits consists of using three-standard-deviation limits rather than three-sigma limits. While this approach was identified as incorrect on page 302 of Shewhart’s 1931 book, it is found in virtually every piece of software available today. While three-standard-deviation limits will mimic three-sigma limits whenever the process is operated predictably, they will be severely inflated when the process is being operated unpredictably. The express purpose of the process behavior chart is to detect when a process is changing, and to do this we have to be able to get good limits from bad data.' Three-sigma limits achieve this. When this is not understood, then we start to take wrong measures to fix the data without any justification like 'censoring of the data prior to placing them on the chart (removing the outliers), and the use of two-standard-deviation limits.' Recall the method to compute three-sigma limits for the XmR chart: calculate the x average, calculate the moving ranges and their average, then multiply the moving range average by 2.66 and add/subtract from the x average to obtain the limits, known as upper and lower (control) limits.

[@kslead27]

Thanks. Simply, don't ever use 'S' in your control charts.

[@yunielcarmona3377]

great explanation