A global automotive manufacturer operated critical process environments, including clean rooms and paint shops, where temperature and relative humidity (RH) had to remain within defined operating limits. Separate heating and cooling systems, low-efficiency legacy assets, highly variable ambient conditions, and dynamic thermal loads made it challenging to maintain stable process conditions while optimizing energy consumption.
Variations in temperature, humidity, and other psychrometric conditions, including wet-bulb and dew-point temperature could push operating conditions beyond acceptable limits, contributing to process rejections and higher energy consumption. The organization needed a more intelligent approach to asset selection and operation one that could dynamically respond to changing environmental and process conditions while maintaining required comfort and process parameters.
Industrial AI & Machine Learning
Real-Time Analytics
AI-Driven Decision Algorithms
VFD-based control
Water Source Heat Pump
Air Source Heat Pump / Hybrid Chiller
AHUs & ASUs
A global automotive manufacturer needed to maintain precise temperature and humidity conditions across clean-room, paint-shop, and other critical process environments. Existing systems relied on individual heating and cooling assets, including low-efficiency legacy equipment, while ambient conditions could vary from 0°C to 52°C, making consistent process control challenging.
Dynamic thermal and cooling loads, combined with changing ambient conditions, made it difficult to consistently maintain temperature and RH within defined limits, contributing to process rejections and higher energy consumption. The organization needed an intelligent control approach capable of dynamically selecting and operating the optimal combination of assets, maintaining required process conditions, improving energy efficiency, and enabling remote monitoring of operational performance.
Bosch SDS implemented an AI-enabled industrial climate and process management solution combining real-time analytics, intelligent asset selection, and automated heating and cooling control.
The AI-enabled approach shifted manufacturing climate management from static equipment operation to dynamic, data-driven control. By continuously responding to changing environmental and process conditions, the solution helped maintain required temperature and humidity levels, optimize asset utilization, and provide remote visibility into operational performance.
Dynamic temperature control
Optimized HVAC asset utilization
Automated heating & cooling control
Improved process consistency
Remote KPI visibility
More stable humidity management
Improved energy efficiency
Intelligent asset selection
Reduced risk of process rejection
Smarter operational decision-making
Bosch SDS combined Industrial AI, machine learning, real-time analytics, and domain engineering to move climate and process management beyond conventional rule-based control. The solution dynamically evaluates operating conditions and determines how heating, cooling, AHUs, ASUs, and heat-pump systems should operate.
By connecting AI-based decision-making with the physical manufacturing environment, Bosch SDS created a more adaptive operating model – helping maintain critical process conditions, improve energy efficiency, and provide remote visibility into operational performance.
