Advancing Manufacturing Energy Efficiency: The Role of AI and Web-Based Tools

This paper introduces a web-based application that simplifies the data analysis processing chain by automating the analysis of arbitrary variables. In particular, our application allows users to easily upload and process data for the analysis of a target variable by exploiting machine learning and evo-lutionary algorithms for precise forecasting and optimization. We demonstrate the system's efficacy using a dataset from a textile company, where our application successfully predicted the target variables with a high level of R-squared of 0.78, using the best regression model. These results not only highlight its real-world applicability but also played an important role in enhancing sustainable manufacturing practices. This innovative application offers a significant step towards sustainable and efficient manufacturing, addressing the challenges of high energy consumption and environmental impact in the industry.