Predictive Maintenance for Fleet Managers

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About

The client is a leading provider of GPS fleet tracking and management solutions that help businesses optimize their operations, reduce costs, and enhance safety. Their solutions leverage advanced GPS technology, cloud-based software, and data analytics to provide businesses with real-time visibility into their operations. With features like vehicle tracking, driver behaviour monitoring through video telematics, maintenance management, and fuel efficiency tracking, they are committed to innovation and customer satisfaction, and aim to continue driving innovation in the fleet management industry.

Challenges

As fleets contain various car makes for numerous use cases, different datasets for different car makes, the real-time vehicle data that client receives from the partners is very complex and utilizing it for reporting and analysis becomes even more challenging. Fleet managers often come across situations where there is overlap between vehicle schedules and breakdowns because of maintenance issues, making the service not very reliable. Client’s fleet management solutions needed to gear up with app components that help them in operational efficiency of the fleets and prevent maintenance issues.

Featured services

Automated Application Process

Ensures higher productivity and efficiency with a significant reduction in spent time.

Data Integration and Consolidation

The process of consolidation which earlier used to take a weeks’ time can now be executed within hours.

Consolidated Reporting

Significant improvement in workforce productivity and business performance on account of automation of data consolidation and analytics.

Improved performance

Significant improvement in workforce productivity and business performance on account of automation of data consolidation and analytics.

Solution

Kanerika’s team came up with an AI enabled vehicle breakdown prediction model that forecasts when the vehicle is due for maintenance, through analysing data from various sources such as sensor data from the vehicle, maintenance records, and driving patterns etc.
The model learns patterns and relationships from the smart, real time and historical data of the vehicle and indicates the probability of vehicle malfunctioning.
The mobile application based on the developed prediction model sends alerts to the driver/ maintenance personnel/ fleet manager about vehicle maintenance(mechanical, electrical, fuel issues etc) and driver behaviour etc., to take preventative measures in avoiding breakdowns, major repairs, and unexpected downtime. In addition, the connected vehicle model also helps develop a timesheet/schedule for optimum fleet management.

Business Impact:

Predictive analytics in the automotive industry has the potential to improve efficiency, reduce costs, and optimize production processes, as well as improve the overall driving experience by identifying and addressing issues before they happen.

1. Predictive Maintenance (Reduced cost on repairs): The model helped schedule maintenance and repairs before a breakdown occurs, preventing unexpected downtime and costly repairs. This can also help in reducing overall maintenance costs.
2. Improved Safety (Improves driver satisfaction): By predicting and preventing breakdowns, AI-based vehicle breakdown prediction can also improve the safety of vehicles on the road by reducing the likelihood of accidents caused by mechanical failures.
3. Optimize Fleet Management (Optimize vehicle utilization/performance): By identifying patterns and trends in vehicle breakdowns, helping fleet managers make informed decisions about vehicle replacement and maintenance schedules, Optimum fleet management was achieved.
4. Real-time Monitoring: Real-time monitoring of vehicle data to predict the breakdown in advance helped achieve better fleet performance.
5. Warranty Management: AI-based vehicle breakdown prediction can help in managing warranty claims by identifying patterns in breakdowns that may indicate manufacturing defects, improving the warranty process, and reducing the costs of warranty claims.
6. Improve Customer Service: By predicting and preventing breakdowns, AI-based vehicle breakdown prediction can also improve customer service by reducing the downtime and inconvenience caused by breakdowns.
7. Eliminating the risk of human error

Why Kanerika?

Kanerika is a leading global IT consulting company offering innovative solutions & services for businesses. Kanerika focuses on data integration, analytics, process automation and cloud management as core areas apart from custom product development. ISO 27701 certified and SOC II compliant Kanerika processes ensure the quality, predictability and partnerships. Kanerika’s technology and process expert teams have been helping its global clients with development and automation using agile methodologies.