10059393FactoryTw.inClosedLaunchpadInnovate UKactoryTw.in will combine 6 state-of-the-art IDTs to generate digital twins enabling manufacturing SME to optimise productivity, energy consumption and customer delivery performance. A brief summary of the complementary technologies are as follows: 1. Digital Twin creation in XR: * Capturing a factory shop-floor and rendering it in 3D using 360° VR cameras and photogrammetry equipment viz. Laser scanners. * Integrated with full 6-degrees-of-freedom interactivity, working across platforms viz. VR, mobile, desktop and online. * Building use-cases for training, data visualization, process and operational visualization and control of factories remotely. 2\. XR-based collaboration platform in a Metaverse * Leveraging the digital twin, allowing multiple users to enter the Metaverse and collaborating in real-time over the internet with full 6-degrees-of-freedom interactivity. * Aiding the multi-user collaboration with full sync of text, voice, sound and interactions over the internet. * Allowing spectator views for viewers to access the Metaverse and engage via the platform of their choice viz. VR, mobile, desktop and online. * Integrating granular analytics within the platform defining user behaviour in the Met-averse. * Plug and play MES scheduler & SFDC solution 3\. Next Generation Manufacturing Execution System * APIs to integrate with disparate ERP systems * Integrated Shop Floor Data Capture * Digital backbone to integrate the IIOT sensors, computer vision and AI scheduler.\` 4\. IIOT sensors * Providing scalable, rapid-to-deploy and super low-cost sensors 5\. Computer vision AI * Digitalising human activities and operations providing critical SFDC and scheduling inputs * Automating the digital inspection of components to generate granular quality history and traceability 6\. Production optimisation AI * AI Scheduling will be focused on customer OTIF (on-time in full) delivery but also balanced against optimising productivity (Overall Equipment Effectiveness (OEE)) and minimising energy consumption * SMEs can optimise scheduling scenarios based on diagnostic analyics and continuous predictive AI feedback loop * Capturing diagnostic data and insight from experienced production planners combined with machine learning algorithms to continually refine planning data and forecast schedules. Together, these innovative technologies will form a game-changing virtual representation of a company's factory -- at significantly lower cost and within a few days rather than several months. This project will combine real-time data captured from IIOT sensors, shop floor data capture and computer-vision system, underpinned by dynamic AI-enabled scheduler, all fully integrated and embedded within a digital-twin demonstrator of a LCR-based manufacturing SME. The visibility created by the platform will also help to drive improved collaboration across supply-chains, enabling OEMs to see more clearly the challenges at suppliers' sites, and vice-versa.