Commercial vehicle maker Ashok Leyland has partnered with software-as-a-service (Says) provider Syncron for predictive vehicle maintenance solutions. As part of the partnership, Syncron is integrating an anomaly detection model into Ashok Leyland Condition Monitoring Systems (CMS), a press release said on Wednesday.
This will help in having a highly effective, completely connected vehicle solution that will potentially fuse predictive analytics with more accurate and relevant prediction processing to improve product reliability, according to the release.
Alignment between Syncron's extensive experience in the automotive, service, and parts industries, and Ashok Leyland's advanced machine learning models and sensor data led the companies to work on developing an industrial IoT-enabled predictive maintenance solution for the manufacturer's extensive fleet of vehicles, the release said. "We look forward to our partnership with Syncron further enabling our reliability engineers to identify failure and degradation problems earlier, maximise uptime, and deliver the exceptional products and service our customers expect," N Saravanan, Chief Technology Officer at Ashok Leyland, said.
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In support of the partnership, Syncron has released new capabilities for Syncron Uptime that further enable manufacturers to leverage a proactive "react before failure" approach by predicting and resolving issues before downtime occurs. "As manufacturers shift from a reactive break-fix model towards a predictive and proactive one, they look to leverage data from connected products and gain actionable insights using advanced AI/ML technology," Ashok Kartham, Chief Product Officer (CPO) at Syncron, said.
"Through this partnership with Ashok Leyland, we hope to equip their customers with Syncron Uptime's powerful failure detection technology in order to get ahead of the equipment failure, thus improving product uptime and customer service satisfaction," Kartham added.
Over the next three years, Syncron and Ashok Leyland aim to scale up the number of vehicles equipped with Uptime and to use advanced machine learning and artificial intelligence tools for prognostic recommendations, as per the release
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