Today’s production facilities are marvels of complexity, churning out vast quantities of data throughout their operational lifespan. To navigate this wealth of information, which is dispersed across various IT systems and databases, facilities tag their systems. These tags can be scanned by technicians on-site with mobile devices, allowing them to swiftly identify the system and access the necessary data.
As we march further into the digital era, entire production facilities are being mirrored digitally. These digital twins offer a dynamic platform for real-time data analysis, predictive forecasting, and simulation, all without impacting their physical counterparts. Platforms like FRAMENCE are at the forefront, delivering exceptional value to businesses and their technicians. Whether it’s for analyzing and monitoring facilities or enhancing production efficiency, the utility of digital twins in numerous scenarios is unparalleled.
While many digital twins provide detailed geometrical and visual representations—significantly reducing the need for physical site visits—their true potential is unlocked when they’re integrated with comprehensive measurement, technical, and process data from the systems they replicate. Traditionally, creating these integrations involves manually mapping Points of Information (PoI), a feasible but labor-intensive process even for smaller assets. This method becomes even more economically impractical for larger installations or objects with thousands to tens of thousands of tags due to the sheer volume of manual effort required.
Using high-resolution pictures to enrich digital twins
At FRAMENCE, we use the power of high-resolution pictures, which is fundamental to creating our digital twins. Beyond offering precision, the superior image quality provides a critical advantage: the ability to recognize and process visual information such as type plates, tags, and other identifiers that other digital twins might overlook. This capability enables us to identify existing tags on systems automatically, streamlining the creation of vital links (PoI) with the associated material and process data. By automating this process, we significantly reduce the manual effort involved, making it a viable solution even for extensive installations.
Reading texts with AI and OCR
Our software implements advanced AI and OCR technologies to detect any text within images—whether it’s on nameplates, object labels, or even handwritten notes. It accurately identifies these texts and positions them within the digital twin at their precise geometric locations. This functionality allows users to effortlessly search for a system by name or ID, finding and visualizing the relevant system in the digital twin within seconds.
Moreover, when systems are linked to external data sources such as ERP systems, control systems, or other databases, our platform can activate these connections using the text or IDs recognized in the images. This integration pulls data directly into the visual representation, enriching the digital twin with detailed, actionable information.
This seamless blend of high-quality imagery and robust IT tools empowers FRAMENCE users to effortlessly breathe “life” into their digital twins, making them a more dynamic and useful tool for managing and optimizing their operations.
Our method goes beyond merely identifying predefined or pre-learned tags; it’s capable of recognizing all forms of labels, type plates, and even handwritten notes. This capability significantly broadens the potential uses of our technology. For instance, operational processes can be refined using visual information extracted from the digital twin. Users have the flexibility to search for any text—such as manufacturer names—and then locate and quantify all relevant systems or installations accordingly. This approach ensures that any text-based information visible within an image is not just recognizable but also actionable, whether it’s needed today, tomorrow, or in the future.