India’s top ranked B-school NITIE to reduce academia-industry gap in supply chain logistics

 

MUMBAI : One of India’s top-ranked B-School – National Institute of Industrial Engineering (NITIE) has embarked upon bridging the academia-industry gap in the field of supply chain and logistics as part of the endeavour to reduce logistics cost in Asia’s third largest economy.

At a stakeholder meet held at NITIE campus on Thursday, industry experts spoke about the need for skill upgradation to address the last mile needs.

Going beyond green ports and green shipping, stakeholders at the meeting aired their views on reducing carbon emission norms using new age tools like artificial intelligence and machine learning where shipping vessels can move around without waiting to change the fuel.

Experts were also unanimous that the supply chain was the blood vessel in the entire ecosystem and called for a need to look at logistics as a process rather than a mere transport system keeping in mind the huge post pandemic opportunity that can be foreseen with the shift in manufacturing from China to India.

To begin with the Mumbai-based B-school with its campus in Powai, will commence with a Certificate Program in Warehouse Management from April 23 that will be spread over six weeks and 30 hours, said Prof. Manoj Tiwari, Director, NITIE, that was ranked 12th among B-Schools of India as per NIRF 2021 rankings.

The certificate course will be held under auspices of the recently established Center of Excellence in Logistics & Supply Chain Management for capacity creation and skill development. The Center will carry out collaborative research projects with industries at national and international, joint diploma programs, short term certificate courses among many more, Prof. Tiwari added.

The Center of Excellence will act as a driving force to train and launch top quality programs to disseminate advanced knowledge and promote Digitisation, Analytics, and IoT Application and Decision Support Systems through Artificial Intelligence and Machine Learning applications and Digital Twin and Control towers, to strengthen the monitoring and analysis of complex logistics operations.

 

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