Success Stories of Customers
predictive maintenance case study 0% Downtime due to lack of spares 28% Reduction in inspection of the gear boxes Early detection and prediction of gear box failure in sinter machines. These gearbox spares have long lead time. Early detection allows Tata Metaliks to take corrective action and also order gearbox spares in time. Challenges Detecting…
19% Overall reliability improvement based on increased in MTBF & Uptime Jaya Shree is the largest linen integrated facility in India. It has more than 42000 spindles and hundreds of machines – Hackling, Sliver Blending, Spinning, Power Looms (Weaving & Knitting), Dyeing and other balance of plant equipment. Jay Shree monitors conditions of bearings, gearboxes, fans…
Red Sea Gateway Terminal improved reliability of their wheeled gantry cranes with ML, AI, IoT vibration, ultrasound and temperature sensors. This case study if for maintenance managers and CIOs that want to digitize reliability to improve crane maintenance in port of industrial installations.
15 days Fast Implementation due to wireless sensors and SaaS 48% More assets under digital predictive maintenance 3x Improvement in accuracy and timely prediction of faults. 15 % reduction in unplanned downtime Reduced inspection possible for machineries installed in difficult to reach locations. Increased asset life due to reduced ware leading to capex savings Production…
36% Overall reliability improvement based on increased in MTBF & Uptime 5 Large Critical assets monitored 7 Faults Predicted 21% reduction in unplanned downtime Challenges Outcomes Solving Machinery Huddles with AI The 72+year-old company “Essel Mining & Industries Limited” was founded in 1950, it holds a legacy of innovation and growth. EMIL has expanded its…
6 weeks to full implementation 58 assets monitored 22 faults predicted 32% reduction in unplanned downtime Reduced inspection possible for machineries installed in difficult to reach locations. Increased asset life due to reduced ware leading to capex savings Production loss prevented due to reduced unplanned downtimes Reduced overall maintenance cost Reduced inspection possible for machineries…
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