AN APPLICATION OF ANN FOR MODELING AND OPTIMISATION OF PROCESS PARAMETERS OF MANUFACTURING PROCESS: A REVIEW

Abstract

In this day and age, the technologies of fifth generation i.e. Artificial Neural Networks (ANN) and Machine Learning are extensively applied for modelling as well as optimizing the performance and effectiveness i.e. Optimization of process parameters of the manufacturing processes. Previously the choice of suitable process parameters was a hard and tedious task. Rule-based schemes, proficiency, understanding and familiarity of domain of particular technologists are mandatory to be known for the selection of suitable parameters of the manufacturing processes. At this time, there is a speedy change in the nature of manufacturing processes. It is now more complicated. As of varying customer's demand and reduced product life cycle, continuous changes are taking place, thus, manufacturing technologies those are easily and readily adjustable to such changes are in great demand. With the perspective of demand of readily adaptable manufacturing technologies, Artificial Neural Networks is an influential tool. This modern technology enables us to discover complex, non-linear patterns in data, and then on the basis of experimental data these patterns are converted into models. Next, they are applied to fine-tuning process parameters. This paper is a review on the appliance of the ANN and its incorporation with various optimisation methods i.e. Hybrid methods for the optimization of the manufacturing process.