IndiaManufacturing2026 – ongoingSiemens India
Predictive chiller optimisation at Kalwa campus
Siemens used predicted cooling demand to optimise a chiller at Kalwa
Problem
Cooling demand at Siemens' Kalwa campus varied with weather and building occupancy. Chiller operation needed to account for those changes.
Approach
Siemens operated a system that predicted demand using weather data, past occupancy and seat bookings. Its India executive described the chiller application as an operating example of AI in building management.
Results
No published figures
Takeaway
Seat bookings supplied an advance signal of cooling demand. Siemens reported tangible savings without disclosing a project-specific figure.
Categories
- Size
- Large enterprise
- Industry
- Manufacturing
- Business function
- Production and quality
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and MLOptimization
- Adoption
- Built in-house
- Goal
- Cost savings
- Evidence
- Company's own claim
Sources
Source summaries
Siemens India executive Robert Demann described a running chiller optimisation system at Kalwa. He said it predicted cooling demand from weather and occupancy information and delivered savings, without quantifying them.
Full details are in the original sources.