The AI monitors the camera feed in real time and compares workers’ actions to the acceptable behaviors defined in the use cases. For example, the system’s ML component can be trained to distinguish between someone who is wearing a hard hat and someone who is not. If the AI detects someone without the required personal protection equipment, it can send an immediate alert or flag the occurrence for future employee training.
Improving Traceability and Operations
Plataine’s AI, cloud-based, digital thread technology expands composites manufacturers’ insights into their supply chains. Through a digital twin, it creates a genealogy of every product, tracing its route from material supplier through manufacturing and inspection processes to customer delivery. It collects data from a variety of sources, including suppliers’ and manufacturers’ software, digitized paper records and internet-of-things (IoT) sensors that measure equipment conditions on the factory floor. Armed with this information, manufacturers can quickly alert affected customers if they discover defects in some material or production process.
In addition, with data on supplier pricing, location and availability of current materials all contained in the database, Plataine’s digital AI assistant can recommend the best sources for a particular component based on general or specific requirements, such as the need for a supplier that uses renewable energy. It can send alerts if a material is nearing its expiration or suggest alternative sources if some event, such as a strike, is likely to cause material delivery problems or production delays in certain areas.
This technology is available to manufacturers of every size. “You don’t have to install servers or have very robust IT operations. Everything is managed on the cloud, so there’s zero installation and zero disruption to the manufacturing process,” says Amir Ben-Assa, vice president of marketing and product strategy at Plataine.
Capitalizing on AI
The combination of cloud technology and AI offer composites manufacturers an unprecedented opportunity to reduce their costs and increase their competitive advantage.
“The more midsize manufacturers try to digitize and automate – especially in North America where labor is expensive – the more they will benefit from automation and the value that AI brings,” says Ben-Assa. “The less they rely on human power, the more profitable they are likely to be.”
The Future of Materials Selection
Understanding the underlying structure and geometry of composite fabrics is key to determining their properties and performance. Today, manufacturers must rely on extensive experimentation and testing of textile samples or high-level simulations of their properties that may not accurately reflect real world outcomes.