Client: Leading Tire Manufacturer
Industry: Rubber Industry
Segment: Asset Performance Analytics
Solution: Predictive Analytics
Technology: .NET, SQL Server, Mobile App
About the Client
The client is an Indian multinational and the largest manufacturer of tires in India, and the fourteenth largest manufacturer in the world. The company manufactures rubber products including tyres, treads, tubes and conveyor belts, paints and toys.
Client manufactures various tires for passenger cars, two–wheelers, trucks, buses, tractors, light commercial vehicles, off–the–road tyres and aero plane tyres.
Business Challenge
With 24×7 manufacturing operations, and heavy demand, the client could not afford any down time in its manufacturing facilities. They had installed a lead acid battery bank for immediate backup in case of power outage.
The client faced challenges in maintaining the battery health on a day to day basis. Breakdowns and maintenance activities were performed in an ad-hoc manner since there was no analytics around battery failure rates.
Another challenge was predictability in the quantity of power that the battery bank could deliver when needed. This meant production slowdown in case of main power failure due to unreliable battery bank performance.
The client was looking for a solution provider with expertise to understand the unique challenges they faced. After evaluating several solution providers, the client was in discussion with AiMetric’s LARA predictive analytics platform for its next-gen features as well as highly modular build that allowed for a high degree of customization.
Solution
AiMetric implemented its innovative Battery Health Monitoring System (BHMS) platform for the client. The Predictive Battery Management Platform utilizes proven technology that is integrated with plant specific applications to provide management and operations personnel with the decision support tools necessary for battery monitoring and maintenance functions.
Real-time knowledge of battery performance, predicting failures using plant data and its impact on the cost of generation and maintenance has become critical to profitability. BHMS provides this information leveraging cutting edge Artificial Intelligence and Machine Learning models and algorithms. This provides top down visibility from the entire fleet of the enterprise down to the plant equipment level.
AiMetric’s AIBMS platform goes beyond traditional performance monitoring to meet customers’ needs and expectations in real-time visibility and monitoring. The platform enabled the client with inputs and intelligence around the following:
- Data Collection: We use data from the battery management system which is either collected by our vendor-provided hardware or uploaded to the cloud directly.
- Determination Analytics: Our determination analytics provides the current status (capacity and impedance) of the battery system down to the cell level.
- Predictive Analytics: Machine learning algorithms combine our extensive model library with live field data leading to precise predictions and subsequent optimization potential.
- Actionable Insights: Battery insights to optimize your battery lifecycles are provided to you either through a customizable user interface or by integrating the system into existing software tools.
- Driven by Necessity: Highly individual aging behavior makes it imperative to track all batteries in the field individually and create respective predictions. Historic data is essential for such predictions, making digital twins the most feasible option for battery analytics.
- Mobile Application: Intelligent mobile application to get real-time alarms notification and useful reports.
Technology
Database: MS SQL server
MES application: Microsoft.NET, Mobile Application
Benefits
- 90% Reduced downtime and increased OEE
- 30% cost savings through better battery monitoring mechanism.
- Improved end customer satisfaction.
