logo

Manufacturing Firm Adopts SLM-Based Predictive Maintenance

Transforming Modern Manufacturing with AI-driven Automation

arrow

Specializing in automotive components, TurboForge faced concerns related to:

1

Unexpected Equipment Failures

Heavy reliance on complex machinery, caused frequent equipment breakdowns forcing the company to halt operations and deal with machinery malfunctioning.

2

Production Delay due to Downtime

Unplanned machine failures caused delay in the delivery of finished products to customers, hampering client satisfaction.

3

Increased Maintenance Costs

Emergency repairs and unplanned maintenance led to higher-than-expected maintenance costs.

arrow
1

Installing IoT Sensors

Set sensors on critical machinery to measure essential operational parameters.

2

Integrating Sensor Data

Incorporated the data with maintenance logs to build a dataset for training the SLM and developed custom SLM to detect early signs of equipment failures.

3

Deploying the SLM Model

Seamlessly integrated the custom SLM model into the company’s maintenance management system.

4

Enabling Real-time Monitoring

Analyzed the data to ensure timely tracking of machine performance, anomaly detection and predictive alerts.

arrow

We implemented a tailored AI-enabled predictive maintenance system:

1

Data Acquisition and Integration

IoT were installed to collect real-time machinery related data and maintenance logs were integrated with sensor data to train the SLM.

2

Custom SLM Development

A lightweight SLM was developed to detect patterns of equipment failures.

3

Implementation and Rollout

The SLM was deployed across the production facilities and alerts were integrated in the existing management system to flag potential issues.

4

Continuous Monitoring and Predictive Analysis

The customized SLM predicted machine failures by analyzing incoming data and identifying possible anomalies.

arrow
25%Reduction in Unplanned Downtime

92%Accuracy Rate in Predicting Failures

15%Improvement in Production Efficiency Rate

arrow

By implementing our SLMs powered predictive maintenance, TurboForge successfully minimised equipment failures, optimised their maintenance schedules and enhanced overall productivity resulting in the company achieving full ROI within 8 months. The significant reduction in downtime and recurring maintenance costs lead to faster ROI and scalable benefits across the enterprise. This case study highlights the transformative impact of AI-powered automation in modern manufacturing.

For more information on how AI can enhance your business operations, reach out to our AI consulting experts today!

Download Case Study

Fill out the form below to get immediate access to the detailed case study PDF.

Contact us

U.S

8501 Wade Blvd. Suite 250.
Frisco, TX 75034

INDIA

320 B, Bestech Business
Towers, Sector 66, Mohali
(Chandigarh) - 160066