Manufacturing / Industrial10 weeks
Predictive Maintenance & Quality Control 2.0
Client: Precision Manufacturing Inc.
Predict equipment failures and detect microscopic defects in real time to minimize downtime and improve yield.
The Challenge
Precision Manufacturing Inc. needed to predict equipment failures before they occur and automatically detect microscopic defects in production lines to minimize downtime and ensure quality. The challenge was to reduce unplanned downtime and improve product quality across high-throughput production lines.
Key Challenges:
- Predict equipment failures before they occur to minimize downtime
- Detect microscopic defects in real-time during production
- Reduce unplanned downtime across high-throughput production lines
- Improve product quality yield and reduce waste
Without predictive maintenance and quality control, the company faced frequent unplanned downtime, high defect rates, increased costs, and reduced production efficiency.
Our Solution
- Unified AI platform combining IoT sensor data with computer vision
- Time-series forecasting models predicting equipment failures
- Real-time computer vision inspection detecting microscopic defects
- IoT sensor integration providing continuous equipment monitoring
- Automated alerting system for maintenance scheduling
- Quality control automation reducing human error
Technology Stack
TensorFlowPyTorchCNNsLSTMIoT CoreApache SparkTensorFlow Serving
Client Testimonial
"Slashed unplanned downtime by 55% and increased quality yield by 25%."
— Head of Operations, Precision Manufacturing Inc.