Case studies: Real solutions, real results
Discover how ML4Industry helps companies transform their machine data into actionable insights, leading to reduced downtime and significant cost savings.
Use Case: Decoding motor health using audio signals
The high cost of silence
Unexpected downtime from motor issues hits hard. Relying on subjective listening is unreliable, and deep data analysis is often slow, complex, and requires specialist tools few have readily available.
Your simple start: sample audio data
You provide sample .wav audio files from relevant motors along with basic context (conditions, IDs). ML4industry securely ingests this and initiates the analysis.
What we discovered (Rapidly)
- ✅Healthy motors vs. propeller faults: Successfully distinguished across multiple motors.
- ⚠️Bearing Faults: Models failed –
- 💡Key Features: Audio texture & pitch patterns (MFCCs/Spectral) identified.
- 📊Readiness Score: Medium-Low (Comprehensive diagnosis requires action).
Your path forward
- (Priority):Gather diverse bearing fault audio (Motors M1, M2, M3)
- (Option):Build high-accuracy healthy/propeller detector now
- (Alternative):Explore anomaly detection for initial screening
Valuable insights in minutes, not months
- Speed: Critical insights delivered far faster than traditional analysis.
- Clarity: Plain English findings & roadmap, no technical guesswork.
- Low-Risk: Identified major roadblocks before large project investment.
- Partnership: Collaborative approach ideal for innovators (Pioneer Program).
