Optimizing Process Parameters of Fuel Consumption of Rotary Furnace – An Interactive regression analysis and python approach


Ratan Kumar Jain, Jai Kumar Sharma
Department of Mechanical Engineering, ITM University, Gwalior, India.


An interactive approach of regression analysis and python being used as the tool for optimizing the fuel consumption of an industrial tilting rotary furnace, operating with an additional amount of stoichiometric air has been presented in this paper. The author has made an attempt of optimizing fuel consumption in ferrous foundries in view of energy conservation. The experimentations were carried out on a 200 kg oil-fired industrial tilting rotary furnace installed in a medium-scale cast iron foundry at Agra manufacturing cylinder heads and engines. On basis of experimental investigations, it was found that crucial operating parameters like preheated excess air significantly affect the melting time, melting rate, and fuel consumption The author has tried to establish the mathematical relationship between fuel consumption and all other input parameters utilizing regression analysis and python. It is believed that this modeled relationship may prove beneficial for industrial foundries to predict the fuel consumption of a furnace operating under a specific set of input parameters without actually operating the furnace thus saving time and energy The results of regression analysis and python correlates with the experimental results.