Energy Efficiency Optimization Application in Food Production Using IIOT Based Machine Learning

The energy sources of the universe are limited and draining with increasing speed. One of the biggest consumption of energy is in the manufacturing industry with 35% of the overall consumption. Collecting and analyzing data is becoming a crucial topic with the Internet of Things (IOT). Using the science of data is becoming a hotter topic in manufacturing industries as well. The study aimed to apply theoretical analytical methods in real-life cases and demonstrate potential returns on IOT investments for fully automated systems. This study not only analyzed and predicted the energy consumption but also provided a prescriptive receipt to minimize energy spending while keeping high-quality production standards. For the use case, the data gathered from real-production of a multinational food manufacturer and machine learning algorithms were applied. The study provides an energy efficiency of 5–6% for a single machine which consumes 35–45% of the total energy spending of the entire factory.