B.Tech in Smart Manufacturing & Industrial Intelligence Application Form at UPES 2027

The B.Tech in Smart Manufacturing & Industrial Intelligence is built on the philosophy of ‘Atoms to Bits’—where every physical manufacturing activity (machines, materials, shopfloors and supply chains) is paired with a digital intelligence layer that can sense, analyse and improve performance continuously. Over 4 years (8 semesters) and 160 credits, the program develops digitally native manufacturing engineers who don’t just operate automated systems but design the “brain” behind modern factories—using data, AI and simulation to make production smarter, safer and more sustainable.

Students build a strong base in manufacturing systems and processes, then progress into automation, robotics and controls, supported by Industrial AI and analytics for real-time decision-making. A defining emphasis is on digital twins and simulation, enabling production lines to be modelled and optimised virtually before changes are made on the shopfloor. The curriculum also covers IIoT, edge and cloud manufacturing for connected operations and predictive maintenance, along with operations strategy, supply chain thinking and sustainability. By graduation, learners are ready for Industry 4.0/5.0 roles where manufacturing becomes intelligent, adaptive and human-centric.

Interested students must meet the following minimum eligibility criteria for admission to the B.Tech program in Smart Manufacturing and Industrial Intelligence: Minimum 50% marks in Classes X and XII. with 50% in PCM (Physics/Chemistry and Mathematics) in Class XII.

This program aligns with the future of manufacturing: smart and autonomous factories, AI-driven inspection and predictive maintenance, digital twins as day-to-day operational tools, IIoT with edge AI, sustainable/net-zero manufacturing, manufacturing analytics platforms, and industrial cybersecurity. Graduates won’t just 'run machines'—they’ll architect the future factory by combining manufacturing understanding with AI-led decision systems.

Typical roles include:

Smart Manufacturing / Industrial Intelligence Engineer (smart factory systems, process optimisation, digital operations)
Industrial AI / Manufacturing Data Engineer (AI models for quality, predictive maintenance, production analytics)
Automation & Controls Engineer (controls, robotics integration, cobots, intelligent automation)
Digital Twin & Simulation Engineer (virtual commissioning, scenario modelling, throughput and reliability improvement)
Operations / Supply Chain Analytics Specialist (planning, optimisation, sustainability-linked operations)