Optimizing Automotive Production: AI-Driven Cooling System Enhancements
The automotive plant, known for its complex and historically grown cooling supply, partnered with etalytics to enhance the efficiency of their cooling system using our AI-driven control solutions. Through an in-depth analysis and the deployment of the etaONE platform and our etaMIND AI Suite, they unlocked significant energy savings potentials and reduced operational costs. This innovative approach not only benefits the plant but also establishes a benchmark for sustainable practices in the manufacturing sector.
Introduction
The client is a leading automotive manufacturer, known for its high-quality vehicle production. They are a multinational automotive conglomerate with various facilities. The specific site in question is a large-scale automotive plant with extensive central utility infrastructure.
Challenge
The production processes require a precise and a historically grown and complex cooling system. The numerous components involved didn’t always operate in perfect harmony, leading to inefficiencies. Significant untapped energy efficiency potentials existed, which could be harnessed through optimal control of demand, temperature, and humidity fluctuations. Addressing these challenges required a comprehensive assessment, pinpointing inefficiencies, and developing a strategic plan to maximize energy savings and operational efficiency.
Solution
When the automotive client embarked on their search for an AI-based solution to optimize their operations, etalytics’ software proved to be the perfect fit. The Control Optimization solution of our etaMIND AI Suite can be used to analyze and optimize the operation strategy. Coupled with the Energy Intelligence infrastructure of the etaONE platform and etaEDGE IIoT gateways, data acquisition is realized in real-time and the optimization control loop is closed by updating setpoints in the building control system. The provided scalability and precision precisely met their requirements.
Measures
Creation of the data infrastructure by deploying the etaONE platform, the etaEDGE IIoT gateway and the etaMIND AI suite.
Analyzing and implementing different optimization patterns
Use of the most efficient chillers
Optimal operation of the equipment at partial load
Optimized recooling of the components
Continuous hydraulic balancing in the chilled water network
Identification of faulty measuring points
Achieving more transparency through virtual measuring points
Training and deploying energy forecast models to anticipate future energy system states
Modeling of plant dynamics to achieve full transparency on the operating behavior of the components according to influencing factors
Calculation of the optimal operating strategy for the components considering both saving targets and wear minimization
Implementation of dashboards for visualization and monitoring of the system and optimizers
Ongoing monitoring of optimization results and system operation in etaONE
Success
There was significant optimization potential. By coordinating and refining the cooling system equipment’s setpoints, we saved 552 MWh/year in electrical energy, reducing emissions by approximately 239 tCO2/year.
Prospect
Ongoing refinements and improved model accuracy are expected to deliver enhanced energy efficiency. The scalable nature of these measures across the client’s production sites holds the potential for further cost and energy savings on the same site and further production sites. Together with our customer we are already expanding the scope to additional energy systems.
