Query regarding design using categorical factors

[#1]

JMP student edition 18
I was trying a custom design with 2 categorical factors and 3 levels. All effects -main and interaction show non significant p value despite using the recommended 9 run by the software.

[#2]

Hi @Manisha !

Welcome in the Community !

What is your objective (s) with this DoE : identify important effects, optimize your system, test the robustness of your system against noise factors, ... ? What are your factors ? Why are they only categorical with 3 levels ?

There are many possibles explanations to why you may not find any effects statistically significant:

• High noise/experimental variability in response / inadequate measurement precision & repeatability : Have you any replicate runs in your design that may help estimate experimental variability ?
• Factors ranges too small : in your case you're using only categorical factors, but are the levels studied different enough to see some variation ?
• Missing of other important factors in the design
• Inappropriate model and/or factors definition
• Maybe these factors are indeed statistically non-significant and impactful on the response studied and with the levels tested.
• ...

Regarding your design, I guess you have done all combinations involving your 2 three-levels factors (3x3). Maybe you could add some runs to have replicated runs and better estimate experimental variability, or adjust the p-value threshold depending on the power analysis : if you're very early in your study and regarding the small number of experiments, I doubt that a "standard" p-value threshold of 0.05 will enable to identify statistically significant effect (unless there are very strong effect sizes and very low noise/RMSE). You could use the Power analysis when designing your DoE with an estimate of anticipated noise in your response to adjust the size of the DoE and/or the alpha level (significance level).
What are the effects estimates ? Are they practically important ? Do they have a meaningful influence on the response ?

You can also read this similar topic (and responses) for information : Using DOE result as a quantitative or qualitative prediction (based on effect summary) 
With more information about your context it will be easier to help you,