Hello Sir! I missed a lecture in my undergraduate studies and you saved my exam score! Your method of explanation is so simple and yet comprehensive. I cannot thank you enough. Your work has helped many people, may you be blessed.
Thank you! I’m currently studying six sigma and this has helped me understand the components of the xbar and r chart. Showing a step by step explanations with visuals has helped me so much!
Great video! Love seeing someone who really understands this teaching it. Too many people on youtube are just slapping +/- 3x the global standard deviation on their line charts and calling it a control chart.
Global standard deviation is far less sensitive to special causes because it includes ALL variations ALL AT ONCE with no regard to time in its calculation. This includes special cause variations which tends to heavily skew your limits. The entire purpose of a control chart and its calculations is to identify significant differences between short term (within subgroup) and long term (between subgroup) variation. For a stable process you would expect the short term outputs of a process to be the about same as the long term outputs.
This is well explained. This is how I was taught it, and now that I finally may be getting back into the manufacturing that utilizes these tools, you sir will serve as my refresher course. Thank you.
Hello Sir. I just wanted to thank you so much for taking the time to produce these RUclips videos. Your method and style of teaching helped me pass my ASQ-CQA exam yesterday. Thank you, Thank you!
Wow! I have been trying to understand this concept for so long. I have referred to so many articles and videos. I wish I had found this sooner. I finally understand it. Great job!
Man, this is amazing information, I just got a bunch of information that was explained to me in a 3 weeks course, and you explained it so smooth!!! Thanks for your content, sir!!
you explain right to the point, the exact points we need, Its a huge help for students who come across these modules among other science subjects and has no basic knowledge, Thank you !👏
Thanks for the video! What do you recommend when we have much larger subgroup sizes? And do you have any recommendations for how to create the centerline? I imagine it's a rolling statistic rather than something static?
Great question! I would recommend using a consistent sample size over time because it will make it easier to manage the control chart over time. Changing sample sizes is not impossible, but you have to make sure that as you change the sample size you don't violate the requirement of having a rational subgroup, and you will have to re-calculate your control limits with your different sample sizes.
Thank you so much for sharing your knowledge Sir! I received my B.S. in Chemical Engineering in Mexico a few years back. I am a naturalized American citizen now. What are the requisites to apply for the CQE exam? I'd really like to enroll in your academy. I enjoy your videos a lot but more importantly the way you teach is very easy to understand.
Hey There!! I'm glad you enjoyed that video! Okay about the requirements to sit for the exam, check out this video: ruclips.net/video/qPLGuXYPXUI/видео.html And then to join the academy, check out this free course: cqeacademy.teachable.com/p/top-10-topics That free course will also come with details about the full course - The CQE Master Class
Hey Sunny! That honestly depends on your process, and how stable and mature it is, and there is no hard and fast rule. If you go-live with a control chart and your process appears to be stable over time, then that re-calculation does not have to happen that often. If you go-live and your process is not stable, you can do both - address those sources of special cause variation, and re-calculate your control limits. But do make sure not to include any OOC (Out Of Control) data points when calculating those control limits.
I have a few questions, I hope that you can help me. 1) How about for subgroup more than 25? 2) Can I calculate the UCL and LCL myself without referring to the constant? especially for big subgroup. 3) I have different orders for a product (mean same setting but different manufacturing date with different batches of raw material), each order with certain number of jumbo rolls, each jumbo rolls will be checked at certain meter length, each meter length will be checked several position from left to right. Should I consider all result is 1 jumbo roll as 1 subgroup and all result in 1 order as 1 subgroup. 4) If we do not use software and only excel, how should we monitor the control chart as we need to calculate the mean, UCL and LCL very frequent?
Hey Chong! For question #1, most tables stop at 25. . I tried to google it but couldn't find anything larger. Honestly, after 25 samples, you should stop using the range value and start using the standard deviation (X-bar and S chart). That transition to the S chart usually happens around 10 samples. For #2, no, you need to constants to calculate the UCL and LCL. You might not need the table I guess if you have the constants memorized. For #3, the question here is all about rational subgrouping, and you want to minimize the variation within a sub-group. I doubt you could argue that all of the measurements on a single roll are 1 rational subgroup. It seems more rationale that whenever you take multiple samples at each meter in length, those measurements would be considered a single rational subgroup. Honestly without knowing your process better it's hard to say what a rational subgroup is. #4, there are excel spreadsheets to perform all of the control chart calculations (UCL, LCL, etc), all you have to do is type in the measurement data
Dear Andy, I need to select a control chart to follow up our customer complaints(for CAPA triggers) , we produce single products (not batches) and there are many attributed customer complaints categories (such as: uncomfortable, broken, wrong parameters ,etc..). number of manufactured products and number of complaints varies each month. My best pick is P chart where I divide the total number of complaints received each month by the number of manufactured products from the previous month (if on January we produced 100 products and on Feb we received 10 complaints then my data point is 10/100=0.1), obviously the only control limit in my interest is the UCL. Do u think I picked the proper control chart? would like to hear your thoughts in general:)
Hi! May I ask, where did you make your x-bar and r chart? Is there any particular application or website you recommend for me to use in making a control chart? Thank you!
Thanks for your videos, it really helps a lot. A quick question though, what if I measure each sample 2 times? Do I need to count each of them as 2 samples or as 1 sample but using their average measurement?
Hey Agra, I assume that when you take those 2 measurements, that you're measuring the same characteristic - not two different things (dimensions, etc). I haven't run into that situation before - why would you measure the same sample twice?
@@CQEAcademy Yes, it is the same characteristics but 2 replications. I am not really sure why there are 2 replications because I just retrieved it from old data, probably because there is a doubt in the gage precision
@@agradhanurwedhasakti4865 That's what came to mind when I first read the two replicate measurements, that someone was worried about gage precision. Honestly, what I'd do is run a Gauge R&R, and if the R&R is acceptable - go down to only a single measurement! That might be a huge form of waste (over-processes) by measuring the same sample twice. And if the gauge R&R is bad. . . it might be time to find a new gauge - too much precision should not be overcome by repeated measurements.
OK, this is about starting the charts but is there also a video or explanation what and how to act when the process gets out of control... when and how to recalculate limits, eliminate outliers etc... Thanks for this intro anyway. Greetings.
Hey West, Generally the answer is no, unless you're measuring some attribute that can also be zero. For example if you were monitoring the temperature of a cold process, you could realistically measure temperature values below zero. However, if you're simply measuring a small attribute that can never be a negative number, and your lower control limit is a negative number, the general practice is to move that up to zero. -Andy
I always viewed x bar & r charts as the x belongs to the operator (it’s what they can adjust), the r belongs to management (equipment, tooling, material, environment). Unfortunately to many managers want everything to fall to the operator, hence actual improvement is not possible.
That’s an interesting take. I’ve never heard it explained that way. IMHO, special cause variation can effect either chart so I don’t usually distinguish responsibility like that
Shut down all other videos on RUclips for Xbar-R Charts. This is enough. Gold Standard.
May the force be with you.
THANKS!!!!
Effectively explained
Thanks so much!!!
Actually, and without exaggeration, you are the best tutor I have ever seen explaining TQM & Six Sigma, May Allah bless you. A bunch of thanks, Sir.
Wow, thank you so much Iman!!! I am extremely blessed, and I want to be a blessing to others!
Best video on this topic on RUclips
Wow, thanks Jacques!!!
Hello Sir! I missed a lecture in my undergraduate studies and you saved my exam score! Your method of explanation is so simple and yet comprehensive. I cannot thank you enough. Your work has helped many people, may you be blessed.
Really Loved Your Explanation : )👌👌👌
Thanks so much Devanshu!!
this is amazing that I was struggling for 2 weeks on this topic and you video simplify it. love it
Thank you! I’m currently studying six sigma and this has helped me understand the components of the xbar and r chart. Showing a step by step explanations with visuals has helped me so much!
Hey Ash, I'm glad the video was helpful!!!!
Thank you so much! There's a reason why you have no dislikes on this video, because you're awesome!!!
wow, thanks so much!!!! I appreciate the awesome feedback!
Great video! Love seeing someone who really understands this teaching it. Too many people on youtube are just slapping +/- 3x the global standard deviation on their line charts and calling it a control chart.
Does that +/-3x global stv still senstive enough to capture the abnormal signal? what is the pro and cons for those 2 methods?
Global standard deviation is far less sensitive to special causes because it includes ALL variations ALL AT ONCE with no regard to time in its calculation. This includes special cause variations which tends to heavily skew your limits. The entire purpose of a control chart and its calculations is to identify significant differences between short term (within subgroup) and long term (between subgroup) variation. For a stable process you would expect the short term outputs of a process to be the about same as the long term outputs.
Very helpful for me eventhough i have bad english, THANK YOU SO MUCH❤️
You're welcome!!
I teach LSS certification classes, and this video is worth sharing with my students becuase it is so clear, consise, and easy to follow.
Thanks so much!
Helpful. In kenya, we say, "Asante kwa kazi nzuri."
I have struggled with this concept for a while, and now get the basics to move forward again. Thank you!
Glad it was helpful!
This is well explained. This is how I was taught it, and now that I finally may be getting back into the manufacturing that utilizes these tools, you sir will serve as my refresher course.
Thank you.
Glad it was helpful!
Thank you for this! I missed this lecture in operations class and was so lost with only the slides. I appreciate the walkthrough!
You're absolutely welcome!
I managed to learn about X bar R chart fast and clearly. Thanks for the great teaching!
You're absolutely welcome!!!!
Thank you, you've explained that clearly 🙏
You’re welcome!
Hello Sir. I just wanted to thank you so much for taking the time to produce these RUclips videos. Your method and style of teaching helped me pass my ASQ-CQA exam yesterday. Thank you, Thank you!
Thanks for this video.
You're welcome!
Your VDO is very crystal clear short but sharp! Thanks from Thailand
You're welcome!!!!
Best explanation I have found, thanks a lot
Wow, thanks Reynard!!!
Thank you so much! This video saved my day.
Wow thanks Naveena, I'm glad you enjoyed it!! And thanks for the comment!
Very helpful video. Thank you CQE Academy.
You're welcome Lizzy!!!!
I am studying for my promotion and this is GOLD!!
Hahahaha I’m glad that was so helpful
Wow! I have been trying to understand this concept for so long. I have referred to so many articles and videos. I wish I had found this sooner. I finally understand it. Great job!
Glad it was helpful!
Thank you I really needed this for my work .This was very helpful
You're welcome!
Man, this is amazing information, I just got a bunch of information that was explained to me in a 3 weeks course, and you explained it so smooth!!! Thanks for your content, sir!!
You're absolutely welcome Rodolfo, and thanks so much for the great feedback and positive comment!
you explain right to the point, the exact points we need, Its a huge help for students who come across these modules among other science subjects and has no basic knowledge, Thank you !👏
You're absolutely welcome!!!!
Great video, nice and straight to the point. Thank you 😃
Thank you!
Great work, Andy. Well explained. You are good
Glad you enjoyed it!! Thanks for the positive comment!
Great vid. Has really helped me to understand the process. Thanks
You're welcome Alan!
Very helpfull, easy to follow!
You're welcome!!!
Simplest explanation. Thankyou. You save me.
You a star, thank u...I loved the simplicity, thanks man
Thanks!
Thank you for clearly explaining the critical acceptance of defect rate per type of product.
You're welcome!!!
I have a quiz today and I randomly came across your video. This helped me grasp the concept entirely. Thank you so much. Subscribing!
Well explained, thank you
Glad you enjoyed it!
-Andy
Great video presentation and explaination!
Thank you .. sir . 💟
You're welcome!!!
May Allah bless u thanks alot
You're welcome Muhammad!!!
This is a lifesaver, my friend!!!!! Fantastic! Thank you so much.
You're welcome Tammy!!!
Good explanation. Thank you andy.
You're welcome Amsyar!
Great tutorial! Thank you Andy.
Thanks! I'm glad you liked it!
You are a good teacher!🙌
Thank you! 😃
Excellent !! great , Thank you!! do you have all the formulas sheet for calculating control charts values
I do have them as a free giveaway on my website!
Thank you so much for this much needed video, gained a much better understanding 👍🏾 appreciate your help
Thank you sir, very easy to understand! Truly appreciate it :)
thanks for clearing it up. also i'm your 1000th like 👍
Awesome, thanks Kaneki!!
Thanks for the video! What do you recommend when we have much larger subgroup sizes? And do you have any recommendations for how to create the centerline? I imagine it's a rolling statistic rather than something static?
Same questions too 🙋
Thanks for your video
Is there video longer than this
You're welcome Peino! I do cover this topic in alot more detail in my course, The CQE Master Class
Thanks
Thanks a lot. Very useful 👍👍👍
You're welcome!
Do we need the same number of sample size for all sub groups?
Great question! I would recommend using a consistent sample size over time because it will make it easier to manage the control chart over time. Changing sample sizes is not impossible, but you have to make sure that as you change the sample size you don't violate the requirement of having a rational subgroup, and you will have to re-calculate your control limits with your different sample sizes.
God bless ur soul now i wont fail my exams thank u so much
hahahaha thanks!!!! I'm glad you love it!!
-Andy
So much helpful then my textbook for my upcoming exam! Thank you for taking your time ! 🙏🏻
Thank Yvette!!! You're absolutely welcome, I'm just glad I was able to help you!
i am from india this helped me very much for my exam tomorrow thank you very much....
This is so easy to follow. Very helpful. Great work!
Wow thanks so much, I appreciate that!!
Love you sir from India
Thanks Rushikesh!!!!!!!!
thank you so much. this is really easy to follow.
You're welcome!!!
I'm glad you enjoyed it and found it easy to follow!
Thank you so much for sharing your knowledge Sir! I received my B.S. in Chemical Engineering in Mexico a few years back. I am a naturalized American citizen now. What are the requisites to apply for the CQE exam? I'd really like to enroll in your academy. I enjoy your videos a lot but more importantly the way you teach is very easy to understand.
Hey There!!
I'm glad you enjoyed that video!
Okay about the requirements to sit for the exam, check out this video:
ruclips.net/video/qPLGuXYPXUI/видео.html
And then to join the academy, check out this free course:
cqeacademy.teachable.com/p/top-10-topics
That free course will also come with details about the full course - The CQE Master Class
I studied this in college and didn't understand it. Man, I wish this video was available to me back then!
Thanks Darcie!!!!
Thank you for sharing and very clear explanination on setting up the UCL & LCL. How frequent do we need to review and recalculate the Control Limit?
Hey Sunny!
That honestly depends on your process, and how stable and mature it is, and there is no hard and fast rule.
If you go-live with a control chart and your process appears to be stable over time, then that re-calculation does not have to happen that often.
If you go-live and your process is not stable, you can do both - address those sources of special cause variation, and re-calculate your control limits. But do make sure not to include any OOC (Out Of Control) data points when calculating those control limits.
Amazing content thanks!
Thank you!
you explain very well , thanks a lot
You're welcome!
Thank you so much for the great explanation! Really saved me the trouble of understanding my prof's terrible slides xD
hahahaha, you're welcome!!!
amazing video it was easy to follow. thank you.
I have a few questions, I hope that you can help me.
1) How about for subgroup more than 25?
2) Can I calculate the UCL and LCL myself without referring to the constant? especially for big subgroup.
3) I have different orders for a product (mean same setting but different manufacturing date with different batches of raw material), each order with certain number of jumbo rolls, each jumbo rolls will be checked at certain meter length, each meter length will be checked several position from left to right. Should I consider all result is 1 jumbo roll as 1 subgroup and all result in 1 order as 1 subgroup.
4) If we do not use software and only excel, how should we monitor the control chart as we need to calculate the mean, UCL and LCL very frequent?
Hey Chong!
For question #1, most tables stop at 25. . I tried to google it but couldn't find anything larger. Honestly, after 25 samples, you should stop using the range value and start using the standard deviation (X-bar and S chart). That transition to the S chart usually happens around 10 samples.
For #2, no, you need to constants to calculate the UCL and LCL. You might not need the table I guess if you have the constants memorized.
For #3, the question here is all about rational subgrouping, and you want to minimize the variation within a sub-group. I doubt you could argue that all of the measurements on a single roll are 1 rational subgroup. It seems more rationale that whenever you take multiple samples at each meter in length, those measurements would be considered a single rational subgroup. Honestly without knowing your process better it's hard to say what a rational subgroup is.
#4, there are excel spreadsheets to perform all of the control chart calculations (UCL, LCL, etc), all you have to do is type in the measurement data
Is there a table with more than 100 sample size for A2 and D4? Or how can I calculate those?
Thanks man your video was really helpful
Glad it helped
Your the best teacher ❤❤❤
Thanks so much!
Well explanation ....!!!!!!!!
Thanks Sameera!!
Dear Andy, I need to select a control chart to follow up our customer complaints(for CAPA triggers) , we produce single products (not batches) and there are many attributed customer complaints categories (such as: uncomfortable, broken, wrong parameters ,etc..). number of manufactured products and number of complaints varies each month. My best pick is P chart where I divide the total number of complaints received each month by the number of manufactured products from the previous month (if on January we produced 100 products and on Feb we received 10 complaints then my data point is 10/100=0.1), obviously the only control limit in my interest is the UCL. Do u think I picked the proper control chart? would like to hear your thoughts in general:)
Sir, how did you find the A2 value? What is the formula behind it?
Hey Manikandan!! I love this question - they actually can be derived from the d2 values, and sample sizes.
This is exactly what I needed
Time stamp - 9:30
Do we not do a "X bar S chart" for this one since our subgroup size is more than 8?
Thank you so much for this video !!
You're welcome!!!!!!!
thank you
You're welcome Gretel, and thanks for the comment!
Is that d2 ad d3 value is standard
Yes, those values are all standard
Hi! May I ask, where did you make your x-bar and r chart? Is there any particular application or website you recommend for me to use in making a control chart? Thank you!
Hey There!! I made that control chart in Excel
@@CQEAcademy Oh I see, thank you!
@@Name-ur6oj You're welcome
Well explained with clear presentation
I really like your videos, because after seeing that I haven't any doubts 👍
Awesome, thanks for the feedback, I'm glad you like them!
@@CQEAcademy also make a video on MSA
@@akanksharai1366 will do! I'm sure i'll create a video on MSA here in the next 2 months or so.
BTW - feel free just to call me Andy :)
🔥lit explanation
I was going through hard time of understanding this...
Now I thought how easy it is...
Awesome, thank you Rupesh!!!
I'm glad I can help you grow!
@@CQEAcademy Ya, it helped me in my diploma exam... 😅 Last minute studies!
@@Rupss.87 fantastic, what are you getting your degree in?
@@CQEAcademy I'm currently in last year Diploma (Mechanical)
@@Rupss.87 Best of luck!!!! I got my degree in mechanical.
Let me know if there are any other topics that you'd like to see.
-Andy
wow! Thanks this is really helpful.
studying this topic for my engineering exams
Is the performance target going to be the same?
Hey Nicole!
Can you clarify a bit, what do you mean by the performance target?
Thanks for your videos, it really helps a lot. A quick question though, what if I measure each sample 2 times? Do I need to count each of them as 2 samples or as 1 sample but using their average measurement?
Hey Agra, I assume that when you take those 2 measurements, that you're measuring the same characteristic - not two different things (dimensions, etc).
I haven't run into that situation before - why would you measure the same sample twice?
@@CQEAcademy Yes, it is the same characteristics but 2 replications. I am not really sure why there are 2 replications because I just retrieved it from old data, probably because there is a doubt in the gage precision
@@agradhanurwedhasakti4865 That's what came to mind when I first read the two replicate measurements, that someone was worried about gage precision.
Honestly, what I'd do is run a Gauge R&R, and if the R&R is acceptable - go down to only a single measurement!
That might be a huge form of waste (over-processes) by measuring the same sample twice.
And if the gauge R&R is bad. . . it might be time to find a new gauge - too much precision should not be overcome by repeated measurements.
Great information. This is the youtube channel i've been looking for! fucking amazing
Wow thanks so much Jarod!!!!
Thank sir. students can easily understand
Thanks, I'm glad you enjoyed it!!!
How can you calculate the control limits with your formula? I thought the limits were given on the blue print.
The specifications of a dimension are given on a blueprint.
Specifications are not the same as control limits.
Shouldn't this have been cleared up before this video in the series. If I was confused I'm sure there are many others who think the same thing.
OK, this is about starting the charts but is there also a video or explanation what and how to act when the process gets out of control... when and how to recalculate limits, eliminate outliers etc...
Thanks for this intro anyway. Greetings.
This is amazing 🤩
Hi, may I know the how do you get the data of A2, D3 and D4? Is it same in the worldwide?
Yes it’s the same worldwide, and you can usually find those values in most statistics textbooks
really appreciate your efforts! thanks so much!
You're welcome!!!
In the last slide for X Bar chart I think the lower line 3.9 value should be rename as LCL not UCL. But very fine analysis.
Great catch, and you're correct, thank you though!!
Is the moving range chart and x-bar chart the same?
extremely helpful !
Super helpful!!! One Question: can the Y values for the Xbar and R chart chart be negative?
Hey West, Generally the answer is no, unless you're measuring some attribute that can also be zero.
For example if you were monitoring the temperature of a cold process, you could realistically measure temperature values below zero.
However, if you're simply measuring a small attribute that can never be a negative number, and your lower control limit is a negative number, the general practice is to move that up to zero.
-Andy
hi! One question, if we calculate the icl and lcl by hand, how can we get the z (number of normal standard deviations)? Thanks :)
Hey Adriana! In your example, do your UCL and LCL change over time, or are they fixed after you perform the calculation?
Hi, what is the "underlying distribution" of a process?
You are a genius. Make more videos, Awesome!!!!!!!!!!
Thanks! I'm glad you like it!
I always viewed x bar & r charts as the x belongs to the operator (it’s what they can adjust), the r belongs to management (equipment, tooling, material, environment). Unfortunately to many managers want everything to fall to the operator, hence actual improvement is not possible.
That’s an interesting take. I’ve never heard it explained that way.
IMHO, special cause variation can effect either chart so I don’t usually distinguish responsibility like that