Innovative, AI-powered predictive maintenance system for conveyors claimed by partners DataArt and MHS
Creating robust and economically viable state-of-the-art monitoring toolsets is a challenge across industry 4.0 companies, which use “smart factories” and the Internet of Things (IoT) to create virtual copies of physical environments to enable decentralised decision-making in real-time.
So DataArt, a global technology consultancy that designs, develops, and supports software solutions, is partnering with MHS, an integrator of intelligent material handling systems. DataArt enables the process by deploying cloud-based communication between sensors and gateways connected to conveyor equipment in order to store, analyse and visualise data, detect anomalies and trigger alerts. It uses a suite of technologies to build scalable, accessible, and cost-efficient solutions.
Suhas Hajgude, director product management at MHS said, “The DataArt team led the development of the solution from prototype to production stage. They applied their knowledge to build a cost-efficient system using the best cloud cost optimisation practices which demonstrated operational excellence from day one of rollout. The system enabled effective collaboration with our team and provided access to exploring the data and building new prediction models out of the box, without requiring teams to become familiar with the infrastructure.”
“DataArt’s experts approach every IIoT solution as a unique project as each of them is highly complex,” said Igor Ilunin, head of IoT & Automotive at DataArt. “Comprehensive real-time information provides useful data for predictive maintenance. Applying an AI approach brings this IIoT solution to the next level of maturity, providing valuable data insights and analytics. This in turn delivers to MHS the competitive advantage of increased efficiency with higher levels of operational excellence.”