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DSD Screening Replication

rich_bubb

Community Trekker

Joined:

Jun 4, 2015

In trying to try to control a visual quality characteristic, we are nearly ready to run a 4 factor (all are continuous variables, e.g., temperature, feed rate, etc.) DSD at 3 levels per factor.  This will have us run 9 treatments for the DSD.

My question is: Should I run one or more replications on the DSD screening-type DOE?

1 ACCEPTED SOLUTION

Accepted Solutions
louv

Staff

Joined:

Jun 23, 2011

Solution

RB,

I would give a try to (-,-,+) for Temp = 540,Feed = 5 and Factor 3 = 500. Factor 4 does not seem to impact response so choose the economical/ergonomical setting for that one.

13 REPLIES
louv

Staff

Joined:

Jun 23, 2011

If you have the resources to consider replication of the design then perhaps I would challenge you to brainstorm additional factors above the 4 factors that you are considering. The true power of the DSD's manifests itself when one is considering many more factors than 4. Of course the answer to your question is yes there is an advantage to adding replicates in any design especially if your measurement system my in your case be subjective?

rich_bubb

Community Trekker

Joined:

Jun 4, 2015

LouV,

We've already narrowed down the likely factors, and performed a multi-vari analysis to be sure our production system (i.e., equipment & measurement systems) and setup/operators were not causing variation. 

Now we're down to "incoming material variation" & "process parameters".  And the incoming material isn't varying much.

Per our Cause & Effect diagram (the Ishikawa had 24 possibilities), we were able to get to the four most likely factors.

The DSD method was chosen because the # DSD runs (9) is less than the normal screening # runs (16), and because we can screen for multiple levels in one screening run.

I'm more interested in detecting factor curvature* vs. economical design.

* I'm pretty sure one or more of the factors exhibit curvature.

Don't know if this is very relevant, but I'm using JMP7.

Thanks for the help.

RB

ryan_lekivetz

Joined:

Nov 1, 2013

I would recommend considering the 6 factor DSD for the 13 runs (and drop the 2 extra factors).

The 9-run DSD can't fit the full RSM model for any subset 3 factors, while the 13-run design is able to. In JMP 12, we now use the 13-run as the default.

Good luck!

rich_bubb

Community Trekker

Joined:

Jun 4, 2015

Ryan,

Thanks for the 6 factor DSD tip, & I'll look into it today.

Are you referencing this paper:

http://www.jmp.com/content/dam/jmp/documents/en/white-papers/definitive-screening.pdf

specifically the designs on page 5?

And by "dropping the 2 extra factors", do you mean dropping the two right-most columns of the m=6 design?

ryan_lekivetz

Joined:

Nov 1, 2013

You are right on with the "dropping the 2 extra factors".

I would use the m=6 design rather than using Augment design, but I'm partial to the special structure of DSDs.

Lou makes a very good point about considering extra factors. If you use the DSD for 6 factors, you're getting to study 2 extra factors for "free". If there's truly no effect on those extra factors, it's simple enough to remove them from the model, but you may end of finding something you didn't expect.

rich_bubb

Community Trekker

Joined:

Jun 4, 2015

Ryan,

I got the m = 6 DSD screening (13 runs) finished & gave it to our process engineer.  Hopefully he'll be able to start running the treatments soon.  I think I got it copied into this message (see below).

Due to confidentiality considerations I have to rename Factor 3 & 4. And I sorted the table based on the Temp column since it take forever to adjust our furnace's temperature & wait for it to normalize... so technically it probably should be a Blocked Factor.

I will add "Y" data when I get it.

Best regards,

RB

                                                                                                                                                                                                                                             

Treat-ment
  #
PatternTemp.FeedProprietary Factor 3Proprietary Factor 4"Y" rating aka undesirable visual quality characteristic
Low-54051000.7
Nom0560103001.3
High+580155001.7
1-0+-540105000.7
2--0+54053001.7
3-++0540155001.3
4-+-+540151001.7
5----54051000.7
60+--560151000.7
70-++56055001.7
80000560103001.3
9+0-+580101001.7
10++0-580153000.7
11+--058051001.3
12+-+-58055000.7
13++++580155001.7
ryan_lekivetz

Joined:

Nov 1, 2013

Hope the experiment goes well!

In the future, if blocking for DSDs has been added in JMP 12 which will give you some extra flexibility in the number of blocks you can consider (as well as more balanced block sizes instead of 3 runs for the "center" block).

There have also been improvements to the way we construct DSDs compared to the original paper - I'm not sure if the DSD add-in works in JMP 7.

Cheers,

Ryan

rich_bubb

Community Trekker

Joined:

Jun 4, 2015

Table below has the results data (Original data then two replications).

Obviously the area around run 2 is where future experimentation will be focused.

                                                                                                                                        

RUNPattern based on m = 6Temp.FeedFactor 3Factor 4

Visual Rating

1=Best
5=Worst

Signal-to-Noise (LIB)

Y1Y2Y3S/NRank
1-0+-540105000.72.62.12.0

-7.039 

2
2--0+54053001.72.32.02.0-6.4641
3-++0540155001.23.63.62.1-10.0484
4-+-+540151001.74.84.84.0-13.15813
5----54051000.73.53.42.3-9.8683
60+--560151000.74.44.54.0-12.68012
70-++56055001.73.53.33.0-10.2995
80000560103001.23.83.23.6-10.9857
9+0-+580101001.74.04.13.7-11.90311
10++0-580153000.73.73.43.8-11.2169
11+--058051001.23.83.63.8-11.44510
12+-+-58055000.73.93.72.5-10.6886
13++++580155001.74.14.02.5-11.1468

NOTE: Color shading in Y1, Y2, & Y3 only used to indicate better (green), moderate (yellow-orange), and bad (red) visual-quality rating.

Rating method was to arranged all Y1, Y2 & Y3 samples side-by-side for comparison/evaluation purposes.  We had to do this type of rating method because no one make a reasonably affordable gage (giving quantitative results) for this product's visual characteristic we're trying to reduce.

RB

PS Thanks to all who provided help on this (LouV & Ryan Lekivetz).

PPS. Now I have ammo to justify getting JMP12... woohoo!

louv

Staff

Joined:

Jun 23, 2011

Solution

RB,

I would give a try to (-,-,+) for Temp = 540,Feed = 5 and Factor 3 = 500. Factor 4 does not seem to impact response so choose the economical/ergonomical setting for that one.