MAHE and GHCL develop smart solution for industrial fuel monitoring

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Prime Highlights 

  • MAHE and GHCL will develop a LIBS-based system for real-time fuel quality monitoring.  
  • AI and machine learning will help speed up fuel testing and improve operational decisions.  

Key Facts 

  • GHCL Ltd is chemical company partnering with MAHE on the industrial fuel-monitoring project.  
  • The system will use LIBS to assess the gross calorific value of carbon-based fuels on-site.  

Background 

MAHE has entered into a Memorandum of Understanding with the chemical firm GHCL Ltd to create a real-time system that would enable the determination of the quality of carbon-based fuels. 

In this regard, MAHE would be using Laser-Induced Breakdown Spectroscopy (LIBS), coupled with AI and ML, to determine the gross calorific value of the fuel. The system aims to provide faster fuel quality results than conventional laboratory testing. 

MAHE’s Manipal Institute of Applied Physics and GHCL will work together to develop the technology. The system will help assess fuel quality upon its arrival at industrial facilities, allowing companies to make quicker decisions about fuel use and operations. 

The partnership is trying to cut down the delays that come with the usual fuel testing. It could also help industries use fuel more efficiently and reduce uncertainty in their operations. 

The two organisations also plan to create intellectual property and develop the technology for wider commercial use. If successful, the solution could be adapted by other industries that depend heavily on carbon-based fuels. 

Mayuresh Hede, Operations Head at GHCL’s Sutrapada plant, said the company wants to use advanced technology to improve operational efficiency and sustainability. He added that real-time fuel analysis could strengthen quality checks and reduce the uncertainty linked to conventional testing. 

MAHE Vice Chancellor Sharath K Rao said the project shows how academic research can solve industrial problems. He said combining LIBS with AI and ML could create a solution with scientific and commercial value and support research for other energy-intensive industries.