System change COMMENT
Rutronik Elektronische Bauelemente
T
he growing complexity of global supply chains demands forward-looking and scalable solutions. Product-level traceability, real-time data acquisition and process transparency are now critical success factors. In response to these rising challenges, COMI (collective mind) and Rutronik Elektronische Bauelemente have partnered to implement a groundbreaking solution: AI- powered, camera-based goods receiving that is transforming logistics processes and
Manual processes: Time- consuming and error-prone
At Rutronik’s Eisingen logistics center, 48 workstations are dedicated solely to incoming goods. With over 100,000 electronic components and constantly changing packaging formats, manual inspection and documentation previously required data entry, inconsistent label reading and missing metadata (e.g. country of origin, lot numbers) led to discrepancies in stock, impaired traceability and increased audit risks.
Goal: Automation, accuracy and system integration
aimed to fully automate goods receiving while seamlessly integrating high-quality data into their digital logistics systems. The primary goals: reduce processing time per item, improve accuracy, increase scalability and future-proof the operation for further digitalisation.
Solution: Intelligent camera-based system with real-time AI
COMI’s system integrates industrial cameras with advanced, trainable AI models conventional OCR or scanner solutions, the AI can recognize and extract information from differently sized, shaped, or placed labels— even when partially damaged or rotated. multiple labels from various packages can be processed in a single scan, allowing workers
to handle larger volumes with less effort. Information such as serial numbers, quantities, manufacturer details and production codes are parsed, validated and directly transferred to Rutronik’s ERP and WMS systems. This ensures real-time availability of consistent, structured data across the supply chain. An intuitive visual interface allows the risk of undetected misreads.
Training with synthetic data and robust performance
One of the key innovations behind the system’s rapid deployment was the use of synthetic data. COMI trained the AI using CAD-generated scenarios, simulating thousands of potential real-world label and minimised the need for time-consuming on- site data collection and drastically shortened the system’s ramp-up period. Software updates and retraining capabilities ensure that the system can evolve alongside changing operational requirements.
Impact: Higher throughput, fewer errors and employee support
Since implementation, average inspection 10 JULY/AUGUST 2025 | ELECTRONICS FOR ENGINEERS
times have dropped by more than 50 per decreased. Employees now spend less time on repetitive, manual tasks and can focus on exception handling and process improvement. This shift supports employee satisfaction and opens up new roles in data supervision and AI-supported logistics planning.
The structured collection and storage of all relevant product information enables seamless traceability, which is increasingly demanded by industries with regulatory requirements such as automotive, medical devices and aerospace. The system also generates audit-ready documentation for each shipment, contributing to overall process compliance.
Scalability and future readiness The success of the AI solution in goods receiving is only the beginning. Thanks to its modular architecture, the system can be extended to adjacent logistics processes such as goods issue, quality checks, or internal transfers. It serves as a blueprint for companies looking to digitally transform their supply chains without replacing existing IT infrastructure.
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