Automation for advanced manufacturing has reached its limits due to human biological limitations as well as the need for repetitive, standardized workflows. Deep learning AI is necessary to automate dynamic, non-standard workflows so as to enable true autonomous manufacturing.
The product owner has developed an AI controller capable of connecting to manufacturing equipment non-intrusively, through low-level hardware interfaces (e.g. VGA, HDMI, USB), without any modifications or software installation to the existing system. Inside the controller is a powerful manufacturing AI agent that emulates both human judgment and behaviour, capable of fully autonomizing all operations as well as forecast equipment health. With incremental learning capabilities, it can generate new insights for equipment as well as process optimization. Factories can also use this product for intelligent remote control and monitoring (RCM) through their command-and-control platform. Unlike other command centers, this platform need not be manned by subject domain experts. Instead, only an engineer is required to ensure all AI agents are online.
The technology solution has been piloted and successfully deployed within notable semiconductor manufacturers. The technology owner is seeking collaboration opportunities with other advanced manufacturing industries, such as aerospace or medical devices, looking to leverage on smarter autonomous manufacturing and OEM equipment manufacturers looking to explore leveraging on AI capabilities into their existing and future equipment for a more competitive edge.
This product combines advancements in AI, software, and hardware as illustrated below:
AI Agent
Hardware
Software
The technology solution can be used for any manufacturing processes (e.g. advanced or precision engineering) that benefits from the utilisation of AI capabilities. These applications include:
The further need for improving productivity and development of AI functionalities enable industrial automation to take a further step. More advanced AI models can now enable further emulation of human judgement and processes on the production floor, shifting from repetitive industrial automation to true autonomy. With more complex and faster workflow requiring immediate responses, there is industrial shift from slower cloud computing to faster edge computing execution. Lastly, legacy equipment currently deployed can now leverage on AI functionalities to further enhance operational efficiency, resulting in an improvement in Overall Equipment Effectiveness (OEE).
The technology solution achieves true autonomy in dynamic workflows with any equipment through simple plug-and-play form factor, using advanced computer vision, insight generation and deep learning. This eliminates the need for expert human judgement and technical expertise required to operate and manage. The non-intrusive hardware uses low-level interfaces for connectivity, avoiding the need for long and complex downtime for equipment modification and software installation. With edge computing and easy integration to downstream and upstream processes, the AI agent is able to coordinate across workflows, optimising operations to occur seamlessly without expert monitoring. Lastly, it provides reliable machine performance insights based on current operational data, focusing on proactive and positive maintenance strategies rather than historical failures.
