Syncron partnerswith Ashok Leyland to propel Industrial IoT Transformation for predictive vehiclemaintenance.
Syncron, the largest privately-owned leader inintelligent SaaS solutions dedicated to Service Lifecycle Management (SLM), hasannounced its partnership with Ashok Leyland. Alignment between Syncron’sextensive experience in the automotive, service, and parts industries and AshokLeyland’s advanced machine learning models and sensor data led the companies towork on developing an industrial IoT-enabled predictive maintenance solutionfor the manufacturer’s extensive fleet of vehicles.
As a part of the partnership, Syncron isintegrating an anomaly detection model into Ashok Leyland Condition MonitoringSystems (CMS) for a highly effective, completely connected vehicle solutionthat will potentially fuse predictive analytics with more accurate and relevantprediction processing to improve product reliability.
In support of the partnership, Syncron hasreleased new capabilities for Syncron Uptime that further enable manufacturersto leverage a proactive ‘react before failure’ approach by predicting and resolvingissues before downtime occurs. Additionally, Syncron Uptime now goes beyondaggregating and analyzing data to offer a personalized recommendation for issueresolution by domain experts.
“In a highly competitive market where vehicleuptime and total cost of ownership are critical to both sales and customertrust, our priority is to develop innovative ways to improve the customerexperience through digital transformation that includes early resolution ofpotential failures,” says Dr. N Saravanan, Chief Technology Officer, AshokLeyland. “We look forward to our partnership with Syncron further enabling ourreliability engineers to identify failure and degradation problems earlier,maximize uptime, and deliver the exceptional products and service our customersexpect.”
Newfunctionality under development:
VirtualSensor Framework: To capture a complete picture of equipmentperformance, new formula-based Virtual Sensors with advanced machine learning(ML) Model predictions and anomaly alerts have been added.
DataValidation: Increasing the accuracy of ML predictions,Syncron Uptime now includes a data validation framework through which datascientists can accept or reject values.
AggregationAlgorithm: Applying the right aggregation strategies issignificant to enabling efficient anomaly and failure prediction analysis. Uptimenow picks the most critical data for in an aggregated view for anomalyanalysis.
Rule-BasedData Filter: Data scientists can use rule-based filtering tocontrol the noise from non-operational equipment and enable more accurate,relevant prediction processing.
PredictionWindow: Users can now visualize the major contributorsto high anomaly scores in sensor readings and automatically perform root causeanalysis to gain meaningful insights from prediction windows.
“As manufacturers shift from a reactivebreak-fix model towards a predictive and proactive one, they look to leveragedata from connected products and gain actionable insights using advanced AI/MLtechnology,” says Ashok Kartham, Chief Product Officer (CPO), Syncron. “Throughthis partnership with Ashok Leyland, we hope to equip their customers withSyncron Uptime’s powerful failure detection technology in order to get ahead ofthe equipment failure, thus improving product uptime and customer servicesatisfaction.”
Over the next three years, Syncron and AshokLeyland aim to scale the number of vehicles equipped with Uptime and to useadvanced machine learning and artificial intelligence tools for prognosticrecommendations and allow service and parts functions to leverage data forproactive maintenance.
“In a highly competitive market where vehicleuptime and total cost of ownership are critical to both sales and customertrust, our priority is to develop innovative ways to improve the customerexperience through digital transformation that includes early resolution ofpotential failures.”
