• Home
  • Edu News
  • IIT Delhi Faculty designs mathematical model to Implement India’s vision of a self-reliant economy

IIT Delhi Faculty designs mathematical model to Implement India’s vision of a self-reliant economy

Model paves the way to meet low cost production demand in Industry 4.0 environment

Industry 4.0 shows how the efficient use of high, medium and low precision machine variants can bring a paradigm shift in a non-conventional manufacturing environment. SOURCE: Unsplash

Our Correspondent

Published on : 12, January, 2021 12:12

Last Updated at : 12, January, 2021 05:44

An Indian Institute of Technology (IIT) Delhi faculty has come up with a mathematical model for implementing India’s vision of a self-reliant economy. 

Professor Surya Prakash Singh of the management studies department at the institute and his research scholar Shubhangini Rajput have highlighted in their research paper titled ‘Industry 4.0 Model for circular economy and cleaner production’ how the traditional Indian industrial sector is lagging behind in implementing Industry 4.0 concept in their manufacturing processes and offered a tangible solution for implementing it.

The paper has been published in the Journal of Cleaner Production.

Singh’s proposed model for Industry 4.0 set-up to achieve circular economy and cleaner production shows how the efficient use of high, medium and low precision machine variants in a non-conventional manufacturing environment can bring paradigm shift for Industry 4.0.

It also presents the economical trade-off among various processing costs and energy consumption of the machines in that ecosystem relevant for an industrialist looking to migrate towards an Industry 4.0 environment for ethical business.

The model is a first of its kind, which shows the strategic implementation of Industry 4.0 philosophy mathematically to fulfil the Make-in-India initiatives at low environmentally-sustainable cost. It currently considers various industrial costs such as set-up, energy consumption, sensor, maintenance, installation, calibration, and transmission cost. The model also takes care of industrial constraints such as production capacity, inventory and demand.  

“The model is tested computationally with large sets of data for multi-product in a multi-time period manufacturing environment and validates the implementation of the model for the traditional manufacturing industries,” Singh said.