Sustainability Through Industry 4.0 Technologies: Discrete Event Simulation for Data-Driven Energy Management

Efficient energy management is particularly significant for the automotive industry due to its high consumption in foundry operations. To satisfy ambitious environmental goals, it is imperative to develop tools and methods for optimizing energy consumption in such contexts. The foundry is currently equipped with sensors and data collection equipment, which presents equipment-specific graphs of energy consumption over time. Although these graphs can reveal patterns and trends in energy consumption by themselves, more systematic methods are needed to utilize this data to investigate and optimize improvements that reduce energy waste. This article investigates the use of Discrete Event Simulation as a tool for leveraging collected historical energy consumption data. The aim is to explore how such data can be collected and translated into simulation variables to generate insights that support improvement initiatives. A case study was conducted to explore this approach, demonstrating that tracking energy consumption data provides a valuable input for Discrete Event Simulation modeling. The findings suggest some methods for data collection of different equipment, its modelling, and that further investigation in this direction could reveal opportunities for optimized energy management in energy-intensive industries.