IIT Hyderabad to study supply chain network of biofuels using technology

Researchers at the Indian Institute of Technology Hyderabad are using computational methods to understand the factors and impediments in incorporating biofuels into the fuel sector in India. This work has been spurred by the increasing need to replace fossil fuels by bio-derived fuels, which, in turn, is driven by the dwindling fossil fuel reserves all over the world, and pollution issues associated with the use of fossil fuels.

The model developed by the IIT Hyderabad team has shown that in the area of bioethanol integration into mainstream fuel use, the production cost is the highest (43 per cent) followed by import (25 per cent), transport (17 per cent), infrastructure (15 per cent) and inventory (0.43 per cent) costs.

The model has also shown that feed availability to the tune of at least 40 per cent of the capacity is needed to meet the projected demands.

A unique feature of this work is that the framework considers revenue generation not only as an outcome of sales of the biofuel but also in terms of carbon credits via greenhouse gas emission savings throughout the project lifecycle.

Dr. Kishalay Mitra, Associate Professor, Department



of Chemical Engineering, IIT Hyderabad, said, “In India, biofuels generated from non-food sources is the most promising source of carbon-neutral renewable energy.

These second-generation sources include agricultural waste products such as straw, hay, and wood, among others, that do not intrude upon food sources.”

Biofuel technologies are evolving in India. The design and implementation of technological, regulatory and policy approaches and pricing strategy of biofuels depend on a deep understanding of the supply chain network.

Such models allow the society to understand the effects of uncertainty in the network parameters on the demand-supply dynamics and can help policymakers devise and revise strategies to meet the future demands of biofuels.

Elaborating on this research, Kapil Gumte, Research Scholar, IIT Hyderabad said, “We use Machine Learning techniques to understand the supply chain network.

Machine learning is a branch of Artificial Intelligence in which, the computer learns patterns from available data and updates automatically to produce an understanding of the system and predictions of the future.”