ANOVA for Production Optimisation

$15-25 USD / hour

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5年以上前

$15-25 USD / hour

What are the Inputs Factors influencing ANOVA (GLM) Results in an Production Optimization experiment? I want to predict the important production parameters affecting my production process (Sheet metal Rolling) and product end properties (Yield Strength - Dependent Parameter). The independent parameters are, Chemical Comp. - Si, Mg, Fe etc, Hot Rolling Temp, Homogenization Temp. etc. All my indepent parameters have different levels (Some times, some factors might have up to 35 Levels) I used ANOVA-GLM in minitab for my analysis. The data I used for the analysis belongs to the last two years production data. 1.) The problem is, when I use the complete two years process data for my analysis, I get different % contribution in comparison to results for which I used only a part of the two years data. With smaller no. of datas I get a better model which explains 95% of the variance. Whereas the other with large set of datas explains only 65% of varaince. So, I want to know which one to accept / beleive and what is the recommended no. of data to use that would replicate the behaviour of my process? 2.) What is the effect of using, duplicate datas (Same data repeated twice or thrice or more) in the analysis.? 3. ) For all of my analysis i have got PRESS, RSq(pred) as *. What does this mean.? 4. ) Are there any other tool / method that would be suitable for my data.? I think taguchi cannot be used, due to its constrains with usage levels.

Mathematics

R Programming Language

SPSS Statistics

Statistical Analysis

Statistics

プロジェクト ID: 17746108

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アクティブ 6年前

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@Vasilchenko

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6.7

@suyashdhoot

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@ProDataAnalyzer

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@DrAmirAdly

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@cyash61

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5.0

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@anaurmeneta

Hello, I would like to help you in your study. I think the problem of the differences in contribution to explanation of the variance between the samples is due to the homogeneity (or lack of it) of the samples. Normally, if you analyze smaller groups you will find more homogeneity in your data (as long as the sample is not too small). While in a large sample you may find less homogeneity. Remember that to obtain an optimal result in ANOVA, it is necessary that the groups are very different between them (inter-subject effects), but, that the members of the same group are very similar to each other (intra-subject effects). I would have to review your data, but it is possible that this is the problem you have with your results. The rest of the issues can be dealt with later. I understand that you already have your results. I know minitab, but I usually use SPSS and R. But, we can talk about it. Cordially. Ana Urmeneta, PhD

$25 USD 40日以内