Autocorrelation Techniques (Student Question)

M

myke74

#1
Goodmorning everybody,

like homework i should describe advantages and disvantages of three techniques for handle autocorreletion in statistical process control.

With the help of the book i tryed to do it, can you tell me what do you think about my job (i.e. if there are wrong stuff and where i should improve)?

Thanks, jack.

1) Time Series Models

2) An Approximate EWMA Procedure for Correlated Data

3) A Model free approach
 
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Marc

Hunkered Down for the Duration
Staff member
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#2
Re: Student question - Autocorrelation techniques

I'm confused. Probably a language issue.

Did you write the above, or is that copied from a text book? Assuming you did write it, are you asking for a critique of what you wrote?
 

Miner

Forum Moderator
Staff member
Admin
#3
Re: Student question - Autocorrelation techniques

Time Series approaches are designed to make predictions that, depending on the method utilized, can accommodate three patterns of behavior, trends, seasonality and cycles.

On the other hand SPC is designed to handle a stationary process, which is self-predicting. Control limits will react to trends, seasonality and cycles. In the context of SPC, the only way to handle autocorrelation is the following:
  1. Use an Individuals Moving Range chart. Multiple samples from an autocorrelated process will only show measurement error in the within-subgroup variation creating control limits that are too tight.
  2. Determine the number of lags for which the process is autocorrelated, and set the interval between measurements at least one lag greater. This will ensure that the sequential measurements are independent.
This is similar to your model free approach with important differences.
 
M

myke74

#4
Re: Student question - Autocorrelation techniques

I'm confused. Probably a language issue.

Did you write the above, or is that copied from a text book? Assuming you did write it, are you asking for a critique of what you wrote?
I took from a book, i will elaborate and develop the content, at the moment i'm just asking if could be ok or if is necessary to add/delete some information.
 

Darius

Quite Involved in Discussions
#5
Re: Student question - Autocorrelation techniques

I am agree with Miner, these are the best way (time between samples), but.., there is still another one.

There are some articles and a few books (Advanced topics on SPC, from Donald Wheeler {an excellent book}), that use an autocorrelation factor to grow the variation estimate in a way that it include autocorrelation, it's a shame that it doesn't go farther, because in the conclusion could be applied to control limits.

I have used it and works nice enought, it can be seen easily if you try to chart a sin function that slowly increases and then decreases (a case that in real life can be seen with processes that are controled by an electronic system).
 

Miner

Forum Moderator
Staff member
Admin
#6
Re: Student question - Autocorrelation techniques

There are some articles and a few books (Advanced topics on SPC, from Donald Wheeler {an excellent book}), that use an autocorrelation factor to grow the variation estimate in a way that it include autocorrelation, it's a shame that it doesn't go farther, because in the conclusion could be applied to control limits.
Darius,
Thanks for that information. I will have to look that one up. Is it only used for assessing capability, or is it used in construction of the control chart? I'm not sure of the benefit of sampling more frequently though because by definitition of autocorrelation, your process will not have radically changed until you reach the number of lags at which you are no longer autocorrelated.
 

Darius

Quite Involved in Discussions
#7
Re: Student question - Autocorrelation techniques

Darius,
Thanks for that information. I will have to look that one up. Is it only used for assessing capability, or is it used in construction of the control chart? I'm not sure of the benefit of sampling more frequently though because by definitition of autocorrelation, your process will not have radically changed until you reach the number of lags at which you are no longer autocorrelated.
I posted it before.
Discussion Thread about SPC and Autocorrelation

The book put it for capability (although it show charts), but you can be agree that capability is determination of how many times your process can fit into your specs, and that the Cp variation estimate is the same as the one used for control limits, it's your process variation!.

:2cents:Agree that your process may not changed radically - mostly all the time, but can you take the risk?, I apply it to any SPC chart (as one size fit all), and the adventage is that it doesn't affect if there is low autocorrelation in your data (less than 0.6).
 
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