Hi @ScientistNMC11,
From what you describe, you seem to already have screened out significant/important factors and want to optimize your response.
So you may be interested in Response Surface (but not very appropriate here since you have only one continuous factor) and I-Optimal designs.
With very few factors (and only one continuous) and a target to optimize one response, the easy way to design your DoE is by trying the "Custom Design". It will give you flexibility about which effects you want to see : main effects, interactions, quadratic effect for the continuous factor, ...
By doing so, you'll be able to have the best number of experiments depending on the level of details you want to have.
For example, if you want to estimate all main effects, interactions and the quadratic effect for the continuous factor, JMP recommends 27 runs (minimum 15 runs).
Depending on your experimental budget, you can add more runs (with replicates or by adding centre runs), or decrease the number of runs (by changing estimability of quadratic effect and/or interaction effects to "If Possible" instead of "Necessary"). You can also change the optimality criterion to I-optimal (red triangle next to Custom Design, Optimality Criterion).
At the end, always try several designs and compare them, to see how the design changes affect the prediction precision/variance, the aliases, the power for effects, ...
I hope it will help you
Victor
Victor GUILLER
L'Oréal Data & Analytics
"It is not unusual for a well-designed experiment to analyze itself" (Box, Hunter and Hunter)