Low-Cost Predictive Maintenance Solution in Foundry Software

Enhanced Asset Efficiency is under development phase for Rotating Asset monitoring at Amma Alloys Indian MSMEs, particularly foundry industries, facechallenges like equipment failures and operational disruptions that hinder productivity. This project focuses on deploying an affordable IoT based predictive maintenance solution for critical rotating assets in a green sand-casting foundry, where continuous operation is vital to minimize unplanned downtime and maintenance expenses. By tracking key parameters and identifying anomalies in advance, these industries can streamline maintenance schedules, enhance equipment reliability, and maintain steady production, leading to greater efficiency and cost savings. The proposed solution is applicable to all MSMEs having rotating assets. Development and site trials are under progress and pilot deployment to be carried out at Amma Alloys by the mid of the Year.

“Each fault in the asset generates a unique signature in the raw data of the key parameters like vibration, temperature and noise levels, allowing for early detection and proactive maintenance before failures occur. This can reduce the unplanned downtime, lower maintenance costs, improve equipment reliability, extend asset lifespan, and enhance operational efficiency”.

Dr. Ranganathan Srinivasan

Adjunct Professor Dept. of Chemical Engineering, IIT-Madras

Key Features of the Project

This solution is proposed with an objective that the MSMEs should easily adapt to the predictive maintenance strategies, prioritizing the ease of use and integration and real-time applicability. Key features include:

Predictive Triggered Preventive Strategy: Overcomes the demerits of reactive and preventive maintenance like unplanned downtime and wastage of resources by scheduling maintenance based on the asset’s condition thereby no disruptions take place in the production.

Fault Detection & Severity Determination: Provides timely alarms and alerts for scheduling maintenance once the fault is detected depending on the severity of the fault which helps to plan the downtime and stock the inventory accordingly.

IoT based Cost-Effective Solution: Utilizes low-cost IoT devices and sensors, with the complete predictive maintenance solution implementable within a budget of 3 to 5 lakhs, considering the MSME has approximately 10 critical rotating assets.