CASE STUDY 06

Predictive Maintenance &
Analytics AI Framework

The client aimed to predict equipment failures before they occurred. We deployed a predictive analytics framework integrating IoT, ERP, and maintenance data for intelligent decision-making.

The problem

Unplanned equipment downtime and high maintenance costs impacted reliability and performance.

Solution

How we solved it

Data Integration

01

Connected IoT sensors with ERP and maintenance systems.

AI Detection

02

Deployed models to detect anomaly and failure prediction.

Dashboards

03

Visualized performance, efficiency, and cost trends.

Team Enablement

04

Trained staff on data insights and action tracking.

Results

Delivering
measurable results

-30%

30% reduction in downtime

Real-time operational
intelligence across engineering
teams

$5.2M

$5.2M annual savings in
maintenance costs