How to choose most appropriate Machine Learning model?
Fit a linear model. Using rejected unit % as target. Then see the coefficients of the linear regression to see how much contributes each to the result.

You can adapt your code to this example of sklearn:

https://scikit-learn.org/stable/auto_examples/linear_model/plot_ols.html#sphx-glr-auto-examples-linear-model-plot-ols-py

If you are feeling confortable with this, you can move to higher performance/non parametric algorithms as decission trees. Or just use a LASSO regression.