01 Positive impact on manufacturing

■ Higher efficiency and productivity

With advanced technologies such as AI, iot and robotics, companies can optimize production processes and reduce downtime, thereby increasing overall efficiency. This optimisation allows human workers to focus on more complex, value-added activities, resulting in increased productivity.

■ RET620 Better quality control

Ai-driven quality control systems can easily analyze large amounts of data in real time to better detect defects and specification deviations. In addition, iot sensors can continuously monitor production parameters, thereby identifying potential quality problems early and reducing the likelihood of defective products reaching consumers.

■ Higher security

Collaborative robotics and AI-driven predictive maintenance systems help identify and mitigate safety hazards in manufacturing environments. In addition, AR and VR technologies provide immersive training experiences and virtual simulations that provide a safe environment for workers to practice performing dangerous tasks.

■ Lower cost

Ai-driven optimization and predictive maintenance help minimize downtime, extend equipment life, and reduce maintenance costs. In addition, Additive Manufacturing can produce spare parts and custom parts on demand, reducing inventory costs and eliminating the need for massive warehousing.

■ Sustainable Manufacturing

RET620 Use AI algorithms and iot technology to monitor systems to optimize resource use and improve energy efficiency, thereby reducing environmental impact. At the same time, additive manufacturing technology can significantly reduce waste generation compared to traditional manufacturing methods, leading the development of production methods in a more sustainable direction.

02 Application Scenarios

Under the new age industry, mass customization of products is possible, and highly agile and adaptable production systems can meet changing customer preferences and market demands. Technologies such as exoskeletons, AR, VR, AI, big data, and digital twins are expected to bring significant value to manufacturing over the next decade. Sustainability will also be a central issue as these technologies are used to optimize resource use, reduce waste and build more resilient supply chains.

Here are some of the key technologies related to the new age industry and their applications:

■ Collaborative robot

Collaborative robots are designed to work side by side with humans to increase productivity and safety. They excel at performing tasks that are physically demanding, repetitive, tiring or dangerous, adapting to different production processes and working in concert with human workers.

■AI and machine learning

AI and machine learning algorithms can analyze vast amounts of data to optimize production processes, predict equipment failures, and enhance quality control. Ai-driven predictive maintenance can identify potential equipment failures ahead of time, reducing downtime and lowering maintenance costs. In addition, machine learning algorithms can optimize production planning, inventory management, and supply chain logistics to increase resource allocation efficiency and reduce waste.