Data analysis and machine learning-based modeling for real-time production

Abstract

This article primarily focuses on data analysis and real time data modelling using linear regression and decision tree algorithm that might make revolutionary prediction on production data. Factual time data points include temperature, load, warning, on all the presented axis are the dependent parameters which be contingent on the changes in the autonomous paraments like load. Monitoring and innovative prediction is very much needed in industry as there are recurrent load changes that would create an data drift and in term of maintenance that could impact the production side as need of continues monitoring and control machine learning based approaches would work better on these real time production datasets.