Twin: Digital Twins for Predictive Maintenance & Factory Optimisation
Unplanned downtime costs manufacturers billions, yet maintenance remains reactive. Twin is a digital twin orchestration platform that enables factories to simulate, predict, and optimise operations in real-time. By integrating IoT data, AI-powered diagnostics, and machine learning, it helps manufacturers prevent failures, improve efficiency, and reduce costs with a scalable, software-first approach.
THEME
Advanced Manufcaturing
The Problem
Manufacturers rely on outdated, reactive maintenance strategies, leading to costly downtime, inefficiencies, and production delays. Without predictive insights, businesses cannot optimise machine performance, energy use, or failure prevention, creating unnecessary waste and lost revenue.
The Solution
Twin creates digital replicas of factory operations, integrating IoT sensor data, AI-driven analytics, and predictive modelling to identify inefficiencies before they occur. This allows manufacturers to reduce downtime, extend equipment lifespan, and improve overall production efficiency—all while cutting costs.
Market Opportunity
The digital twin market is expected to exceed £40 billion by 2030, driven by demand for AI-powered factory automation. With manufacturers prioritising smart, data-driven decision-making, Twin is positioned to reshape the future of industrial production.
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