Abstract
Inefficient production policies and practices have led to unprecedented wastages within various manufacturing domains. This unprecedented wastage and environmental exacerbation due to unsustainable practices have made it necessary to implement green manufacturing methods. However, the traditional methods have not been as efficient as expected and lack precision. Where Machine Learning models have been implemented in various research work done to date, they have shown efficient outcomes, and reduced human errors or even human involvement up to some extent. This review rigorously compiles and presents a set of research works done to date, which will give a clear perspective and applicability of ML models in various manufacturing processes.