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You must be prepared for this training, have basic knowledge of statistics, if you have a problem to solve at work, I recommend you bring it to the course to solve your doubts. The trainer is very experienced and knowledgeable, he was really good answering our questions

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How to DoE in JMP Software

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Don't know much for the moment, except that a strong statistical background is required. 

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Don't know much for the moment, except that a strong statistical background is required. 

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How to prepare to do a DoE in JMP

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DOEs help conduct a series of tests to find an answer in the most efficient and resource optimized way

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When to use which DoE model

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How to use the software Jmp

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How does DoE actually work. What's the steps and what's required to do an DoE

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How does DoE actually work. What's the steps and what's required to do an DoE

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What is different to MiniTab

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how to close the Design workbook

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Understand the methodology and learn how to prepare and run DOEs for any specific topic

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What we need for a DOE

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Learn the DOE and refreshments of the first two weeks

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Learn the DOE and refreshments of the first two weeks

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I’d  like to reinforce the knowledge in JMP Software, applied to DLSS

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How to use JMP software applying DOE

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Useful repetition, awesome catapult action and solid ANOVA experience

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2-way Anova

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1-Way & 2-Way Anova, refreshment of Minitab

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Analyse 2-way ANOVA separately when factors are ordinal/disordinal.

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statistical evaluation for more than one factor and interpreting the numbers 

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statistical evaluation for more than one factor and interpreting the numbers 

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Impact of randomization and sample size

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Anova way 1 & 2

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VIF 1 Green
VIF 5 red

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Interesting stuff but sometimes too fast

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Interesting stuff but sometimes too fast

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Morning went fine and was very interesting. However I was having a hard time in the afternoon to follow the steps in minitab while also really understanding the results and the interpretation. It would be cool if we could take a little bit more time to deal with the examples and its results if possible.

PS: Great catapult action

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The first half of the day was instructive.
It was possible to work through and understand the ANOVA in the minitab using one's own data.
Learning by doing.
second day was senseless. No time to understand / document the regression, let alone the procedure in Minitab. Mental state in the evening was that of a beaten dog.

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connection theorie - praxis is not completle clear. Very fast Minitab lessons. Is there a guideline for process cycle available? Catapult is king

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Impact of number of factors on model complexity (ANOVA with 2 factors vs. 3 factors).

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It was good, but I have problems about the MiniTab settings

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Differences between simple, multiple & multivariate multiple regression
Correlation is the first step before regression
You have  to eliminate redundances
Correlation doesn´t necessarily lead to causality
Andy

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fast klicking in Minitab sometimes hard to follow. Use also more time to talk about interpretations / analysis

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Some things were already known from former exercies, that was a fine repetition. Like the Pareto.

Overall it was sometimes very difficult to follow the tasks and to write in parallel some notes, making screenshots,...

A rough summary of the different steps of the regression analysis would be fine. What is the first step, which plot, what should be the outcome of it . . .

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a lot of new minitab features and settings

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please repreat again when to apply ANOVA and when Regression

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Taguchi and Factorial DoE were topics that stayed in my head. Factorial DoE if you got no clue about the most important / influencial factors.
+ interesting Speech / project from C. Henkel
To be better: more of self solving topics and less of watch and click

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The 6 types of doe with some examples
First steps in JMP

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Very useful screening types / reduction of factors. JMP introduction was good. Ferrari shapes are already visible. Interesting story about the Z-folding machine.

PS: I miss the catapult ;-)

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Type of testplan is usecase dependent e.g. Taguchi considers noise, SFD for a mathematical model,

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three steps of DOE:
- Screening
- Optimization
- Robust Design

Overview 6 Screening types

Z-folder

It was easier to follow compared to the first two days. good ratio between theorie, questions and doings

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DSD, SFD, Taguchi ...

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Different types of DoE`s.
First steps in Jmp

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Tangible experiments / data to be implemented and analysed in JMP
good mix of theory and practice
In: Response Surface in JMP and general evaliuation of data

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1. How to handle linear and non-linear behaviour (FFD vs. RSD) and
2. Possibility to extend a linear testplan to a non-linear when center points are existing

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DOE does not always show the real limits of the configurations.
the 3 steps of DOE:
- screening
- optimization
- robust design
using JMP with linear and non linare models

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Day 4 Optimization
- FFD for linear models
- RSM for non linear models
- tkS, Minitab & JMP have a different nomenclature for Factors, Signlas & Noise (at Taguchi)
- Using Counter Profile to optimize my system

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We got to see more functions in JMP, check for curviness, expand the range in case the maximum is outside, modify the factors in order to maximize more than one response. Catapult results were a bit misleading but this was due to the low number of repititions

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1st and 2nd order models / Linear and non linear

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It´s a must use the P-diagram before DOE - JMP use a special configuration X1,X2=Signals, X4, X3, N1, N2, C3, C1 C2 = Noises
How to do a tolerance design based on Taguchi´s parameter optimization.
Select the proper Taguchi array

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Refreshments of Minitab in doing ANOVA 1, 2 & 3.
DOE in JMP:
all 6 DOE types have been presented, but custom is the strongest

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Reinforce knowledge in DOE, how to use JMP:  JMP includes methods to minimize the impact of data problems on your analysis, often eliminating the need (and effort required) to make your data pristine.
how to apply the Mahalanobis methodology.
Interactions can be assessed graphically prior to the experimental design using interaction plots. Types of correlations, univariate simple OLS, univariate multiple OLS regression, multivariate simple OLS, multivariate multiple OLS regression.

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Different types of DoE. For the daily business , I will stick to the custom DoE. Much Theory which was validatet with the catapult -> thumbs up .  The pace at the beginning could be a bit lower. As you know you need to warm up an engine before you can race it.
In general what stick to the brain was:
1) ANOVA
2) Residuals
3) diff. types of DoE

I would recomend the training and also participate one more time to get a greater understanding.

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- refreshing with the X-factor and ANOVA.
- Basic information of all DOE's
- DOE Screening and optimization

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There was a lot of content, starting with the repitition in Minitab (regression, ANOVA...) which was really needed as this topics are not part of my line of work, up to first steps using JMP. We saw different screening methods and it was surprizing how little the effort would be to filter out the most significant factors. We went on by optimizing our results including the understanding of a robust design. Having the catapult with us most of the time, we could apply the newly learned procedures at a practical example.

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- ANOVA single and multiple
- causality
- correlation
- regression
- DOE Structure
- Screening
-  Optimization
- Robust Designe
- Different types of Screening and what is the target of the screening itself
- FFD for linear systems
- RMS for non linear systems
- . . .

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I learned how to apply Anova, Regression and DOE. The Catapult examples where very useful to get the link from theory to practial use.

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- Learned how to use JMP and its benefits
- Know better what the p-diagram and its contributors are
- Planning is like 80% of the effort and 20% is testing
- You need to know what you're doing
- Fun and practical games successfully connected theory with practice

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Good recap about the statistics (Anova, regression,..)
all the diferent Doe in Jmp and the right way to do a robust design.
The mix between theory and games was very good, to understand the functions better.

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1. Preparation of the testplan is important (randomisation, assignement of factor type e.g X2, X4 etc.)
2. Overview of different types of DoE's and the limitations (e.g considering of linearity)

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Different DoE types, ANOVA and how to use JMP

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Great expertise of trainer
Would have been nice to have the slides beforehand to take notes directly.
3-way ANOVA and Taguchi took a bit too much time --> training could have been shorter instead of 5 days.
General overview of DoE types would be helpful to compare differences and specialties.

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Learned about different variants of DOE

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- You'll learn on how to become a professional catapult operator. Might help if you suddenly wake up in medieval times and you need to find a new job

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- Recommended training to hone your statistical and analytical skills and mindset
- Cool and competent teachers
- Funny and practical games with real life examples to connect with the theory

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As most of us don`t need to work with the kind of data and topics we got to know during the training, it was definitely hard to understand the theory and procedures at the beginning. For me personally, it was great to get an idea what is actually possible to do in the statistics world and which pre requerements are needed to carry out proper experiments (randomization, eliminating of noise, sample size... ). I`m not sure if I will be able to use the procedures we learned in twoo weeks time or later, but I know whom to consult and what`s the theoretical background. The fact that there`s also our regular work which needs to be taken care of before and after the training sessions made it an exhausting week, but hey: No pain, no gain. Thanks Alberto for introducing us to the big, crazy but interesting world of DOE

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Interpretation of the different charts, e.g. target value analysis

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It was very interessting to see how you can reduce the amount of runs/samples with DOE --> A good planning can reduce a lot of effort in Testing!

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The training is quite complex and sometimes hard to follow for someone who had nothing or nearly nothing to do with DOEs and Data analysis so far. But it gives a great overview of the possibilities how to work with data, how to prepare a development testing and how mucht the testing effort can be reduced with the correct settings.

The trials with the catapult were very helpfull to better understand the theory behind a DOE. There we could see in a physical example what is a factor, signal, noise, . . . and in the end it makes a lot of fun.

The trainer was competent and very motivated with a lot of patience.

I am recommanding this training but I am not sure how much I can implement into my daily business.

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Training is not a piece of cacke. But when you are willing to try to understand the basics, you will get some tools to your hand that will leave everyone else behinde.
I would recomend the training with the premise, to refresh some basic knowledge in statistic befor the training.

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Without pre-knowlege of DoE's, the training is sometimes challanging to follow. A general explenation of DoE's in advance would be helpfull or adding more examples.

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Training style:
- some clear examples of the Minitab and JMP examples are missing and would be very helpfull for us.
- It would be better to show only one way during an example of solving, than 3 or more (what often happens).
- The catapult is very good to bring some fun in the lessons.
- starting the training in german and then do it in english doesnt help. -> german prefered
- cockies are very good for the breakes
- show shortly what DOE can at the beginning of the lesson, that we know what avaits us at the end of the training.

Training informations:
- The basic training of statistik is realy necessary for common people for this training.
- There are many information in short time, what is very hard to capture.
- There were oft so many side informations, that the key message was often not transfered.

Training and connection to daily buisness:
- it is not so easy to find this connection.
- For us it would make more sense to do more with minitab than with JMP, because we won't have JMP. -> better to just show over 1 day what JMP can and train us to interpret the results.

Would I do the training again? -> something between: I am not shure / Yes -> it depends how much i can use in my daily buisness in future