Remote equipment maintenance

DrSignal has introduced AR (Augmented Reality) remote equipment maintenance technology to improve production efficiency and ensure the smooth operation of automated cell preparation equipment. This technology not only enhances the precision of equipment maintenance but also significantly reduces maintenance time. Through AR technology, technicians can remotely connect to the digital twin monitoring system, allowing real-time monitoring of equipment status and data. When equipment issues arise, they can use AR glasses or tablet computers to directly view the actual equipment while accessing relevant fault messages and repair guidance. This remote AR maintenance approach not only reduces the need for technicians' on-site inspections but also enables faster and more accurate repairs, thereby reducing the risk of production interruptions, improving production efficiency, and ensuring the quality of cell production.

AR Equipment education and training

Through AR technology, education and training can be conducted in a more vivid and interactive manner, teaching individuals how to operate and maintain the company's automated cell preparation equipment. This method of education and training accelerates the learning process for personnel, enabling them to more efficiently master these highly complex devices.

AR remote equipment education and training provide employees with a more modern and efficient learning method, aiding in enhancing their understanding and mastery of equipment. This approach helps elevate the skill level of personnel and reduces potential risks during the training process, such as equipment damage or operational errors.

Synchronous virtuality and reality monitoring

We have achieved highly precise monitoring of production equipment using synchronous virtuality and reality technology, bringing significant advantages to production operations. This advanced monitoring method allows us to track the operational status of various production equipment at all times, thereby enabling us to predict potential issues before they occur. This predictive maintenance approach enables us to conduct necessary repairs and maintenance in advance, thereby reducing the risk of downtime and production costs.