Siemens and Procter & Gamble (P&G), one of the world’s largest consumer goods manufacturers, are expanding the deployment of an AI-based quality inspection solution across P&G’s manufacturing operations worldwide. The system inspects products in real time during production, delivers comprehensive inspection coverage at full line speed, and helps improve quality consistency. Depending on the product, scrap rates have been reduced by 10 to 20%.
The Visual Inspection Cockpit (VIC) is used in high-speed consumer goods manufacturing where products consist of delicate, textured materials that naturally shift, stretch or wrinkle at high production speeds. Traditional vision systems often require extensive reconfiguration when materials, packaging designs or production environments change. By using Industrial AI, VIC can adapt more effectively to these variations and maintain inspection performance across a broad range of products.
Developed jointly by Siemens and P&G, the solution combines P&G’s deep learning models with Siemens’ Industrial Edge computing platform, industrial PCs powered by Nvidia GPUs, and AI hardware and software. Siemens supports the industrial computing infrastructure, software scaling capabilities and long-term operation of the system across production sites.
“Our Industrial AI and Industrial Edge capabilities deliver what high-speed production demands: full inspection accuracy for thousands of products per minute, scalable from a single line to a global footprint. This collaboration demonstrates what we mean when we say we are making industrial AI real,” says Rainer Brehm, chief operations officer for automation and chief technology officerbat Siemens Digital Industries.
“We engineered this solution to solve a myriad of industry challenges that traditional vision systems could not touch. These include ccurate characterisation of overlapping components, the subtlety of low-contrast defects, the complexity of highly decorated products and packaging, tight time coordination, and real-time PLC integration with single-product reject at high production rates with continuous inspection,” says Paul Thomas, director of machine vision and applied AI at Procter & Gamble.
VIC analyses live camera images in real time and inspects every product passing through the production line. Unlike conventional rule-based vision systems, the AI-based approach can handle a wide range of product variations without the need for frequent reprogramming. The solution includes the Visual Inspection Engineering Tool which enables plant engineers to configure, train and update inspection models directly without requiring dedicated data science resources. This makes quality control more flexible and easier to maintain in complex production environments.
Inspection results are processed close to the production equipment on Siemens’ Industrial Edge and integrated directly into manufacturing operations. The system can automatically trigger actions such as alerts or the removal of defective products from the production line. Quality data can also be collected and analysed over time, helping production teams identify trends and support continuous improvement efforts.
VIC is part of Siemens’ broader machine vision and industrial AI portfolio which includes the Industrial AI Suite. These solutions are delivered as standardised applications on the Industrial Edge platform. Together, they provide a consistent framework for deploying AI-based solutions at scale, regardless of whether the AI model is a custom development or Siemens-owned.
Because VIC is delivered as a reusable Industrial Edge application, new deployments can be commissioned five to ten times faster than traditional bespoke vision systems. With established infrastructure, DevOps processes and integration patterns, P&G; can replicate the solution across plants, products and inspection scenarios with minimal overhead. The inspection data feeds into P&G’s broader digital manufacturing ecosystem, providing real-time visibility into process stability and continuous improvement opportunities.
For more information contact Siemens South Africa, [email protected], www.siemens.co.za
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