Unarguably, the automation of data collection and subsequent statistical treatment enhancethe quality of industrial management systems. The rise of accessible digital technologieshas enabled the introduction of the Industry 4.0 pillars in local companies. Particularly,such practice positively contributes to the triple bottom line of sustainable development:People, Environment, and Economy. The present work aims to provide a  general automatedframework for data recording and statistical control of conveyor belts in production lines.The software has been developed in three layers: graphical user interface, inPHPlanguage;database collection, search, and safeguard, inMySQL; computational statistics, inR; andhardware control, inC. The hardware components are based on open source hardwareasArduinoboards and modular or industrial sensors. Specifically, the embedded systemis designed to constantly monitor and record a number of measurable characteristics ofthe conveyor belts (e.g. electric consumption, on-line and of-line time periods, noise,air pollution, temperature and distance), via a number of sensors, allowing both thecomputation of statistical control metrics and the evaluation of the quality of the productionsystem. As a case study, the project makes use of a laminated limestone production line,located at the

Mineral Technology Center, Nova Olinda, Ceará state, Brazil.