Application of ML & Al for energy efficiency in manufacturing

With the global energy crisis and rising pollution levels, the energy efficiency model is very necessary for energy saving in the manufacturing sector. In terms of total energy usage, the manufacturing industries are the world’s largest, energy consumers, consuming 42% of all electricity in 2018 [1]. The huge amount of energy consumed in the manufacturing industry provides a great opportunity to minimize (CO₂-eq) emissions while simultaneously providing a financial incentive for businesses to improve their energy efficiency. Al and ML-based techniques play a vital role in increasing the energy efficiency of the machine tool. AI and ML are used in almost every sector. In manufacturing nowadays, AI is employed for data analysis and future scope and efficiency prediction. Most devices that are manufactured today have a sensor that collects the data. This big data was collected and analyzed by using the different Al and ML techniques that improve productivity and decision-making. In this article, we discuss the different Al and ML techniques and algorithms for energy efficiency in legacy machine tools and the economic approaches to collecting the data from the legacy machine tool. We also discussed the scope of AI in manufacturing.