Water Particles Monitoring in the Atacama Desert: SPC Approach Based on Proportional Data

Statistical monitoring tools are well established in the literature, creating organizational cultures such as Six Sigma or Total Quality Management. Nevertheless, most of this literature is based on normality assumption, e.g., law large numbers, and brings limitations towards truncated processes open questions field. This work was motivated by register elements related to water particles (relative humidity), an important source moisture for Copiapó watershed, Atacama region Chile (the Desert), presenting high asymmetry rates proportions data. paper proposes a new control chart interval data about (symbolic data) when they not results Bernoulli process. The unit-Lindley distribution has many interesting properties, having only one parameter, from which we develop both classical symbolic performance proposed analyzed using average run length (ARL), median (MRL), standard deviation (SDRL) metrics calculated through extensive Monte Carlo simulation study. Results real applications reveal tool’s potential be adopted estimate limits Process Control (SPC) framework.