Best way to analyse the data

#1
Hi,
I am new here, so not sure that this is the best place to ask the question or not. Here I go anyways.
As show below, I have a dataset in which the parts made in Tool1and from each run( runs_Tool1- nominal values) goes through Tool2 and runs - nominal value. After going through Tool 2, the parts are measured.
Each run from Tool1 has major impact on the measured data. What is the best way to standardize the data so that I am only looking at the variations from Tool2?
Regards
Will


1557092629536.png
 
#2
Hi Will,

I'm not sure exactly what do you want to check?

If for example, you run a regression the dependent variable (y) will take into consideration both tool1 and tool2.
 
#3
Hi Obh
The runs that I have mentioned are discreet so I can't really get a regression. That is the reason for my question
Regards
Will
 
#5
Hi Obh,
Sorry I don't understand your question. Each runs in Tool1 has certain number of parts go through it. The same parts then may be sudivised or all put through Tool
Regards
Will
 
#6
Hi
For each run from Tool1, I had calculated the median for each Tool2. The problem is if the parts from Tool1 does not get split between the 3 tools in Tool2, then the problem how do I compare the the 3 tools in Too
regards
will
 
#8
Hi Obh,
Hope this is clear

1557173691661.png
For each run from Tool1, I had calculated the median for each Tool2. The problem is if the parts from Tool1 does not get split between the 3 tools in Tool2, then the problem how do I compare the contributions from Tool2
regards
will
 

hlsmith

Not a robit
#9
@will1234 No idea what you are writing about and presenting here. Please take a big step back and tell us what field you work in, what is your overall question, and define these data. Do we need all of these columns, is this time series, is it quality improvement engineering stuff, etc.
 
#10
Hi Hlsmith/obh
I am an engineer in a manufacturing plant that makes sensors for cars. I recently started there. I know that the Tool1 in column 2 and each run in column 3 has huge impact on the measured data. That is assuming that the tools in column 5 are matched.
As I have stated before, if the parts from the same tool in Tool1 go through 3 or 3 different tools in Tool2 -column 5 then there is a way of comparing the difference or variations from Tool2 's but if it doesn't then the question is how do I compare the Tools in Tool2. So need column 2, column 3,column 5, and column 6
Regards
Will
 
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#11
@will1234 No idea what you are writing about and presenting here. Please take a big step back and tell us what field you work in, what is your overall question, and define these data. Do we need all of these columns, is this time series, is it quality improvement engineering stuff, etc.
Hi Hlsmith
I am an engineer in a manufacturing plant that makes sensors for cars. I recently started there. I know that the Tool1 in column 2 and each run in column 3 has huge impact on the measured data. That is assuming that the tools in column 5 are matched.
As I have stated before, if the parts from the same tool in Tool1 go through 3 or 3 different tools in Tool2 -column 5 then there is a way of comparing the difference or variations from Tool2 's but if it doesn't then the question is how do I compare the Tools in Tool2. So need column 2, column 3,column 5, and column 6
Regards
Will
 
#12
Not clear yet ...

So if I understand you ...
Each part going through 2 stations: Station1 and station2. (you called in tool1 and tool2)
In each station, you can use one of 3 tools (in station1, the following tools: a, b, c . in station2, the following tools: e, f, g)

If so and if you want to run a regression???? you should use dummy variables. for example, in station1 you should use 2 variables: a,b
if a tool was used: (a=1, b=0)
if b tool was used: (a=0, b=1)
if c tool was used: (a=0, b=0)

And a similar way for station2.

Are a, b, c and e, f, g the same tools? (say a is e,, b is f , c is g)
Do you produce the same product, and you want to choose what is the best combination (a,e) , (a,f), ...(c,g)
do you expect it to be the same measurements?
what does meas mean?
What do you expect meas value to be?
is your goal minimum standard deviation for meas ?
 
#13
Not clear yet ...

So if I understand you ...
Each part going through 2 stations: Station1 and station2. (you called in tool1 and tool2)
In each station, you can use one of 3 tools (in station1, the following tools: a, b, c . in station2, the following tools: e, f, g)

If so and if you want to run a regression???? you should use dummy variables. for example, in station1 you should use 2 variables: a,b
if a tool was used: (a=1, b=0)
if b tool was used: (a=0, b=1)
if c tool was used: (a=0, b=0)

And a similar way for station2.

Are a, b, c and e, f, g the same tools? (say a is e,, b is f , c is g)
Do you produce the same product, and you want to choose what is the best combination (a,e) , (a,f), ...(c,g)
do you expect it to be the same measurements?
what does meas mean?
What do you expect meas value to be?
is your goal minimum standard deviation for meas ?


Hi Obh,
Thanks for your reply. I am not sure how I can apply to my situation.
Meas means measurements
I have 2 stations
Station 1 has tool A,B&C. Each tool will have a run. Each run in each tool is unique. Let's say a run via tool A is A1,a second run is A2....etc. The same principle applies to tool B & C.
Station 2 has tool E,F,G. Each of these tool will inturn process whatever comes out station 1 tools. Let's say A1 run from tool A station 1 is split into E as E1 run and into F as F1 run. And let's say that the A2 run just goes through G as G1.
How do I compare only the variations on station2 tools without taking into account the input from station1 tools and runs.

Station1 tools and station 2 tools are different

The product is made in station 1 tools but further processing is carried out in station 2 tools before any measurements are carried out



I hope I have explained it well enough for you. If not please let me know and I will try again

Regards
Will
 
#14
Not clear yet ...

So if I understand you ...
Each part going through 2 stations: Station1 and station2. (you called in tool1 and tool2)
In each station, you can use one of 3 tools (in station1, the following tools: a, b, c . in station2, the following tools: e, f, g)

If so and if you want to run a regression???? you should use dummy variables. for example, in station1 you should use 2 variables: a,b
if a tool was used: (a=1, b=0)
if b tool was used: (a=0, b=1)
if c tool was used: (a=0, b=0)

And a similar way for station2.

Are a, b, c and e, f, g the same tools? (say a is e,, b is f , c is g)
Do you produce the same product, and you want to choose what is the best combination (a,e) , (a,f), ...(c,g)
do you expect it to be the same measurements?
what does meas mean?
What do you expect meas value to be?
is your goal minimum standard deviation for meas ?


Hi Obh,
Thanks for your reply. I am not sure how I can apply to my situation.
Meas means measurements
I have 2 stations
Station 1 has tool A,B&C. Each tool will have a run. Each run in each tool is unique. Let's say a run via tool A is A1,a second run is A2....etc. The same principle applies to tool B & C.
Station 2 has tool E,F,G. Each of these tool will inturn process whatever comes out station 1 tools. Let's say A1 run from tool A station 1 is split into E as E1 run and into F as F1 run. And let's say that the A2 run just goes through G as G1.
How do I compare only the variations on station2 tools without taking into account the input from station1 tools and runs.

Station1 tools and station 2 tools are different

The product is made in station 1 tools but further processing is carried out in station 2 tools before any measurements are carried out



I hope I have explained it well enough for you. If not please let me know and I will try again

Regards
Will