Hi @SignalFerret615 : What you seek is very complicated. It involves finding a confidence interval for a ratio of variances (each being a linear combinbation of variances!); and intervals on even the simplest of ratios can be challenging indeed. The ratio can be linearized perhaps and then numerical methods can be used to find the confidence interval, but even then there are a load of moving parts.
Linearization, for example, can be carried out via: ratio = (VC[repeat]+VC[repro])/(VC[repeat]+VC[reprod]+VC[part-to-part])
Some algebra results in L = VC[repeat] + VC[repro] -ratio*(VC[repeat] + VC[repro] + VC[part-to-part])=0. Then get the upper bound of the confidence interval for L for some value of ratio. Then used fixed-point interation (https://en.wikipedia.org/wiki/Fixed-point_iteration) to find the value of ratio that makes the interval =0. You could do a similar thing to get the lower bound.
You'll need to use methods like the following:
https://www.sciencedirect.com/science/article/abs/pii/016771529190118B
https://www.tandfonline.com/doi/abs/10.1080/00949659008811240