Statistics Control Process

[benikenobi]

Hi,

I dont know if this question for this site but I think people with this background could help. Could anybody suggest books or references abount CumSum and Shewhart control charts? I am thinking to use this kind of tecniques to monitor 2.000.000 devices. Does it make sense?

Thanks in advance

[Scott Johnson]

I'd say Understanding Statistical Process Control by Wheeler or Statistical Process Control by Oakland.  Wheeler is not a big fan of six sigma.  His belief to be world class is to be on target with minimum variance.  Not a field I'm real familiar with tho'

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Regards,

Scott Johnson

[DrQ]

There's gobs of stuff about this subject on the web, but it helps to get the name right: Statistical Process Control or SPC (as Scott has indicated).

Process refers to a manufacturing process and the usual context is monitoring some kind of "quality" of the process, e.g., number of defects. 

Defects are discrete counts, viz., a single metric. The UCL and LCL control limits are chosen to be a 3σ above and below the statistical mean. 

That, in turn, assumes a Gaussian distribution for the defects (which may or may not be true).

With that as background, how do you anticipate applying SPC to 2 gazillion "devices"?

[Scott Johnson]

You might want to look at the R package spc for Shewhart control charts

Look at pg 103

https://cran.r-project.org/web/packages/spc/spc.pdf

Package ‘spc’

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Regards,

Scott Johnson

[benikenobi]

Thanks for the references, I will have a look. I would prefer python-based info :) but I would have a look definitively. I am just exploring these approaches. The main idea is that those devices will report low level error counters and I am thinking to use these approaches to distinguish expected number of errors from abnormal number of errors. Other subject that I would like to have a loot at is Anomaly detection. Again, I am just exploring these approaches, anyway , any input will be very welcome.

Thanks very much. 

El sábado, 28 de mayo de 2016, 5:11:16 (UTC+2), Puft escribió:

You might want to look at the R package spc for Shewhart control charts

Look at pg 103

https://cran.r-project.org/web/packages/spc/spc.pdf

Package ‘spc’

On Fri, May 27, 2016 at 5:25 PM, 'DrQ' via Guerrilla Capacity Planning <guerrilla-cap...@googlegroups.com> wrote:

There's gobs of stuff about this subject on the web, but it helps to get the name right: Statistical Process Control or SPC (as Scott has indicated).

Process refers to a manufacturing process and the usual context is monitoring some kind of "quality" of the process, e.g., number of defects. 

Defects are discrete counts, viz., a single metric. The UCL and LCL control limits are chosen to be a 3σ above and below the statistical mean. 

That, in turn, assumes a Gaussian distribution for the defects (which may or may not be true).

With that as background, how do you anticipate applying SPC to 2 gazillion "devices"?

On Friday, May 27, 2016 at 1:41:41 PM UTC-7, benikenobi wrote:

Hi,

I dont know if this question for this site but I think people with this background could help. Could anybody suggest books or references abount CumSum and Shewhart control charts? I am thinking to use this kind of tecniques to monitor 2.000.000 devices. Does it make sense?

Thanks in advance

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Regards,

Scott Johnson