DOE

Design of Experiments


Hello! Welcome back to my blog. For this post, I'll be sharing about the activity that I did with Daryl on DOE!

Daryl (CEO) and I (CFO), were tasked to create a data analysis on task 1.

Study 1

Legend: A: Diameter
              B: Time 
              C: Power

These were the results given which we consolidated in the table shown above with - and + representing low and high values respectively. We also made another table shown below with the actual values for easy reference.


FRACTIONAL FACTORIAL

                                                                       A x B

                                                                      Step 1:
Next, we compared the list of interactions which are A x B, A x C and B x C. We then arranged the runs given from the table above accordingly to its subsequent low and high values for easy and quick calculations depending on which two factors we focused on.


Step 2 :

Once we have consolidated the values, we calculated the average reading of high and low A values at low B value and at high B value.


Step 3:

    The results are then plotted into a graph.


We performed the same steps for A x C and B x C to be able to compare which factor would be the most significant and which is the least significant. 


A x C

Step 1:
Step 2 :




                                                                      Step 3:


                                                  
                                                                              B x C
                                                                   
                                                                     Step 1:


Step 2 :


Step 3:


Results

After observing the gradients of each different interaction, we have concluded that B is the most significant factor followed by C then A being the least significant.

                                                             FULL FACTORIAL

We have chosen the 4 runs such that the high and low values are balanced out and suitable for full factorial.


For this step, it is very similar to step 2 in fractional factorial but for this, we calculated the average for all high and low values for A, B and C individually.



Lastly, we plotted the average values to compare the effects of each factor.


Results

For full factorial, we have concluded the most significant factor is C followed by B then A being the least significant.


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