Within manufacturing, measurements are used to make decisions related to product verification and process control. The selection of production machines and instruments involves a trade-off to achieve the required accuracy while minimizing cost. Similarly, deciding on the level of confidence at which products are rejected is a trade-off between the cost of rejecting acceptable parts and the cost of passing substandard products to the customer. These trade-offs can only be optimized if the uncertainties are fully understood. Currently multiple methodologies are used to understand uncertainties and variation within manufacturing, such as measurement systems analysis (MSA), statistical process control (SPC), and uncertainty evaluation. The industry lacks a unified approach that provides a complete understanding of uncertainty. This means that optimal decisions cannot be made to maximize the profitability of production systems.