Client Profile: LTTS’ (L&T Technology Services Limited) client is a leading manufacturer of gas and diesel engines for marine propulsion. The client leases engines to various marine and freight carriers across the globe and is responsible for maintaining these engines.
Objective: To ensure optimum utilization of their leased equipment, the client was looking for a digital solution that would help them monitor the engine health eﬀectively and pre-empt faults, to schedule planned maintenance, and ensure minimum downtime.
LTTS’ decades of experience working with heavy engines combined with its expertise in developing predictive maintenance solutions were well known to the client owing to their successful ongoing engagement. This made LTTS the partner of choice to develop the digital solution for engine performance optimization.
Challenges: Each engine is equipped with various sensors that typically collect more than 500 signal points data. The signal points were uploaded to a central cloud system without any further analysis. This led to a data piling of more than 1000 TB per engine. Without data analysis, the engines were serviced only after a breakdown. This meant that signiﬁcant damage had already resulted in part erosion, which in turn led to an increased maintenance cost and a reduced engine life. Reactive maintenance also resulted in signiﬁcant downtime leading to revenue loss for the customer.
After gauging the challenges and analyzing the existing data, LTTS proposed a two-pronged solution.
1. Analytics at the edge: Instant analysis at the edge to provide warnings and notiﬁcations to monitor and maintain operational parameters within optimum limits, preventing part and engine damage
2. Overall engine monitoring: Sensor data and logs after each trip were transferred to the data center for analysis and Condition-based Monitoring (CBM)
The solution incorporated collection and sharing of real-time data from the engine control system and sensors with edge gateway for analytics; in-house edge analytics solution, Avertle, for instant warning; a feedback loop to identify and report anomalies to the vessel operator along with suggestions for countermeasures; Cybersecurity standard - IEC 62443 and IEC 27001; and periodic data transfer to a centralized data center for analysis and CBM.
Tangible Benefits: The solution can identify anomalies well in advance – at least 45 minutes before they become apparent, and can send the notiﬁcation to the operator along with necessary recommended actions. With predictive analytics and CBM, the engines were serviced well in advance, reducing the critical servicing cost by at least 30 percent.