Taguchi Method involves identification of proper control factors to obtain the optimum results of the process. Orthogonal Arrays (OA) are used to conduct a set of experiments. Results of these experiments are used to analyze the data and predict the quality of components produced.
I have a problem while doing analysis in 4factor 3 level L9 orthogonal array... I am not getting the values of p and f while error being shown is that degree of freedom for error is 0.. How i can resolve this issue in minitab?
These are signal-to-noise ratios which measures how the response varies relative to the nominal or target value under different noise conditions. You can choose from different signal-to-noise ratios, depending on the goal of your experiment. Larger is better: Select when the goal is to maximize the response. Smaller is better: Select when the goal is to minimize the response. Consider your goal is to analyse the Material Removal Rate (MRR) of material while machining. Here, you would like to remove maximum material as you can remove/cut in single cutting operation. i.e. means you go for "Larger is better" option. So, overall it depends upon which parameter you are considering. For Surface roughness and Kerf width it is "Smaller the better"
Yes, you can plan manually i.e. you can decide number of factors and type of design (3-levels, 4-levels etc.) after that from available designs you can select any design and carry out your analysis.
hi , is it possible to analyse an experiment with tagushi method when you have parametere with different level ? (parametre A with 2 level and parametere B with 4 level ) ???
Yes, it's possible.For that you have to choose mixed level design. (For parameter A WITH 2 LEVEL AND PARAMETER B with 4 level you may choose L8 orthogonal array)
Ra and RMS are both representations of surface roughness, but each is calculated differently. Ra is calculated as the Roughness Average of a surfaces measured microscopic peaks and valleys. RMS is calculated as the Root Mean Square of a surfaces measured microscopic peaks and valleys. You will easily get it's formula on google just search as "Ra & RMS: Calculating Surface Roughness"
Taguchi Method involves identification of proper control factors to obtain the optimum results of the process. Orthogonal Arrays (OA) are used to conduct a set of experiments. Results of these experiments are used to analyze the data and predict the quality of components produced.
Why optimal condition on mean effect shown with the higher point on each factor?
I have a problem while doing analysis in 4factor 3 level L9 orthogonal array...
I am not getting the values of p and f while error being shown is that degree of freedom for error is 0..
How i can resolve this issue in minitab?
did you got the solution for it ?
What is the parameter name of lp cs agp
👍
Can we implement taguchi for two factors??
yes, L9
Hello, nice video. It was really helpful
I have a doubt
What Smaller or Larger is better mean? Is there any condition if I have to choose one of them?
These are signal-to-noise ratios which measures how the response varies relative to the nominal or target value under different noise conditions. You can choose from different signal-to-noise ratios, depending on the goal of your experiment.
Larger is better: Select when the goal is to maximize the response.
Smaller is better: Select when the goal is to minimize the response.
Consider your goal is to analyse the Material Removal Rate (MRR) of material while machining. Here, you would like to remove maximum material as you can remove/cut in single cutting operation. i.e. means you go for "Larger is better" option. So, overall it depends upon which parameter you are considering.
For Surface roughness and Kerf width it is "Smaller the better"
AK now I get it
Thanks to your video and explanation, now I can finish my proyect :)
is that I can make a plan manually, ie use a matrix maniuellemet (myself)
Sorry, I didn't understand your question. Can you explain your question briefly?
thank you very much,
using this program, is what I can change a plan of experiments manually, ie is what I can put test conditions myself,
Yes, you can plan manually i.e. you can decide number of factors and type of design (3-levels, 4-levels etc.) after that from available designs you can select any design and carry out your analysis.
Hope, your problem is solved.
thank you very much for the information
hi , is it possible to analyse an experiment with tagushi method when you have parametere with different level ? (parametre A with 2 level and parametere B with 4 level ) ???
Yes, it's possible.For that you have to choose mixed level design. (For parameter A WITH 2 LEVEL AND PARAMETER B with 4 level you may choose L8 orthogonal array)
so with have to adapte our level parametere to the taguchi table ?
thunk you for your respond , so we have to adapte our experiment to a tagushi table ?
Sorry, didn't understood your question. Can you be more specific?
Hi what is the effect of DOF on the result
The degrees of freedom is independent of the effect vs. interaction relationship and are dependent only on the number of runs.
Thank you
why is my taguchi showing invalid column 1?
have you gone through the same method which I have explained in this video?
Can you be more specific and explain in details about your problem?
Bro please tell me the formulae for surface roughness value
Ra and RMS are both representations of surface roughness, but each is calculated differently. Ra is calculated as the Roughness Average of a surfaces measured microscopic peaks and valleys. RMS is calculated as the Root Mean Square of a surfaces measured microscopic peaks and valleys.
You will easily get it's formula on google just search as "Ra & RMS: Calculating Surface Roughness"