Dr. Chiller - Immersive AR Framework for First-Level Maintenance Support (CHILLER)

Lead
The Dr. Chiller project transforms industrial equipment into intelligent, connected assets. By combining an embedded Digital Twin with Augmented Reality (AR) and Artificial Intelligence (AI), the project enables predictive maintenance and guided on-site support. This innovative approach reduces unplanned downtime and empowers personnel to resolve complex technical faults independently.

Background
Industrial maintenance currently faces significant challenges due to a shortage of skilled personnel and reactive service processes that lead to costly production interruptions. Many companies struggle with limited transparency regarding the condition of their machines throughout their lifecycle. Existing support tools, such as manuals or standard Augmented Reality (AR) applications, often provide only static instructions that do not react to the actual state of the machine. Dr. Chiller addresses these gaps by creating a direct, real-time link between physical industrial assets and their digital representations.

Objectives
The primary goal of the project is to develop a scalable ICT (Information and Communication Technology) framework that improves service quality and energy efficiency. Specific objectives include:

• Reducing Downtime: The solution targets a reduction of unplanned machine downtime.
• Faster Repairs: Mean time to repair (MTTR) is expected to decrease through improved diagnostics.
• Workforce Support: Using AR-guided workflows, less experienced staff can perform safe and effective first-level maintenance.
  Standardization: Implementing an Asset Administration Shell (AAS) ensures that device data is accessible and secure according to modern Industry 4.0 standards.
• Sustainability: Continuous monitoring aims to improve energy efficiency.

 
Approach
The project advances the technology from laboratory prototypes to a system validated in real industrial environments. The approach integrates several technical layers:

• Embedded Gateway: An industrial-grade hardware gateway is developed to implement the Asset Administration Shell (AAS) directly on the machine. 
• Edge AI: Lightweight Artificial Intelligence (AI) models are embedded into the gateway to detect anomalies and assess machine conditions locally. 
• Dynamic AR Interaction: A state-aware AR application is created that responds to live machine data to provide real-time troubleshooting guidance. 
• Industrial Validation: The framework is tested and refined over several months on industrial chiller installations to ensure robustness and market readiness. 
• Service Innovation: The technical foundation enables new business models, such as "Cooling as a Service" (CaaS), where customers pay for performance rather than equipment ownership.