Process Analysis. “An operation is composed of processes designed to add value by transforming inputs into useful outputs. Inputs may be materials, labor, energy, and capital equipment.”
Historic performance analysis models of large computer and manufacturing systems often encounter large scale prediction errors due to the smaller errors at each step. We seek to minimize these errors, particularly when predicting retail demand or supply shortages.
Our method of modeling a system consists of:
1) Record or compile time-series data about the system
2) Derive relative probabilities of different system reactions
3) Build the algebraic abstractions that describe the process, and minimize random error build-up.
Sounds simple in theory, but the reality of building a model describing a complex system can be a daunting task for any analyst or engineer. Our process algebra models use a different system to predict process problems where other modeling efforts have failed.