Designing a process quality control framework using Monte Carlo simulation

Abstract

Quality control seeks to collect and analyze large amounts of data to take appropriate corrective actions and ensure that products or services meet quality requirements. This study proposed a methodological framework to analyze the quality control process employing Monte Carlo simulation. The methodology consists of four steps: (i) Establishment of probability distributions, (ii) Construction of the mathematical model, (iii) Running the simulation, and (iv) Analysis of the results. The application of the methodological framework in a carbonated beverage production made it possible to ensure with 99% confidence that one of the most important quality characteristics of the product, the degrees Brix, varies in a range of ± 0.02. The results show the methodology allows to broadly map the process variables behavior and to make decisions on optimal levels for quality monitoring and control.