Proposed method of forecasting cumulative effects of variation in manufacturing

Manufacturing, in general, creates a finished good from a set of simpler supplied parts. Supplied parts are installed into higher assemblies, higher assemblies move into even higher assemblies, and eventually this terminates at the finished good. Delays or variation during the manufacturing process ripple all the way to the finished good, possibly from different branches of the build and possibly magnifying any individual effect. There is extensive literature regarding Lean Manufacturing and it provides strategies and business philosophy to deal with variation, however it offers little in the way of quantitative analysis on the effects of that variation upon the whole. Digital Twins and discrete event simulations can and have been used to model the impact of variation in its totality. Various papers on Digital Twins have explored how to model manufacturing, but very little on generalized behavior. (i.e. How schedule slips at the subassemblies impacts the delivery dates / quantities at the finished good level). This paper explores the analytical quantitative effects of input/sales variation through the manufacturing cycle and the resultant effect on the finished good manufacturing schedule/cycle. We demonstrate that even small random variations/interruptions propagate up the build chain, get reduced in magnitude and end up producing predictable reductions in the average build rate of the final product. Additionally, it is shown that the more supplied parts that comprise a finished good the greater the expected reduction in average build rate.