MechAIQ

AI-Powered Engineering Intelligence for Industrial Machine Reliability

AI-powered Diagnostics and Prognostics for Industrial Machinery

MechAIQ builds intelligent machine health monitoring systems that combine vibration sensing, AI-driven diagnostics, and prognostics to predict failures before breakdown occurs — helping industries significantly reduce downtime, maintenance costs, and operational losses.

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Our Vision

We are building the next generation of industrial intelligence systems that transform raw machine performance data into actionable diagnostics, prognostics, and maintenance decisions.

Real-Time Monitoring

Continuous machine vibration data acquisition and live operational health tracking.

AI Diagnostics

Automatic detection of bearing faults, imbalance, misalignment, looseness, and gear anomalies with definite confidence levels.

Predictive Prognostics

Remaining useful life estimation and failure forecasting for rotating equipment.

Cloud Dashboard

Remote machine monitoring with secure analytics dashboards and health reports.

Custom Sensor Integration

Plug-and-play deployment with vibration, acoustic, and process sensors.

Industrial Intelligence

Data-driven maintenance planning to reduce downtime and optimize asset life.

How it works

  1. Sensor installation on target machinery
  2. Live data collection and edge processing
  3. AI-based fault diagnosis engine
  4. Remaining useful life prediction
  5. Actionable maintenance recommendations

PHM Workflow

Our predictive health monitoring workflow combines sensor data acquisition, AI-based diagnostics, and prognostics to generate actionable maintenance intelligence.

PHM workflow

SEE WHAT YOUR MACHINE IS SAYING TO YOU.

DETECT THE SIGNAL. FIND THE FAULT. SAVE THE PRODUCTION.

Monitor the complete drive train, inspect the bearing sensors, read the time waveform, FFT and spectrogram, and identify the developing fault before production stops.

🏭 SAVE THE MACHINE

A simulation of machine-health monitoring, vibration diagnostics and maintenance decision-making

🏆 SCORE0
LEVEL1 / 3
⚙ CURRENT MACHINE

Gearbox Drive

MACHINE TRAIN & SENSOR LAYOUT
1BEARING 1
(DE)
2BEARING 2
(NDE)
3BEARING 3
(INBOARD)
4BEARING 4
(OUTBOARD)
MOTOR
COUPLING
B1
B2
GEARBOX
B3
B4
PUMP / LOAD
2.6 mm/s
3.1 mm/s
3.4 mm/s
3.8 mm/s
ACTIONS
① BEARING 1 (DE)2.6 mm/s
② BEARING 2 (NDE)3.1 mm/s
③ BEARING 3 (INBOARD)3.4 mm/s
④ BEARING 4 (OUTBOARD)3.8 mm/s
AVERAGE BEARING TEMP68.2°C
MOTOR CURRENT17.2A
TIME WAVEFORM (BEARING 4 - OUTBOARD)
Raw vibration signal from Bearing 4
FFT (FREQUENCY SPECTRUM) - CURRENT WINDOW
Single FFT of the current time window
TIME vs FREQUENCY vs AMPLITUDE (SPECTROGRAM)
2D representation: X = time, Y = frequency band, color = amplitude • 0–250 Hz shown

WHAT IS THE PROBLEM?

FAULT HINTS (As Fault Progresses)

Early-stage faults are subtle. Trends and frequency content are key.
Bearing defects show energy at specific high frequencies.
Misalignment shows strong 1X with harmonics (2X, 3X...).
Unbalance shows strong 1X with little to no harmonics.
LEVEL OBJECTIVE: Identify the correct fault before time runs out and prevent failure.
Start monitoring. The machine will not wait forever.

Use Cases

Rotating Equipment

Motors, pumps, compressors, driveshafts, engine cranks, gears, bearings.

Condition Monitoring

Continuous asset health analytics for industrial plants.

Failure Prevention

Early warning system to avoid catastrophic breakdowns.

Contact

Schedule a product walkthrough or discuss a pilot deployment.

Email: hello.mechaiq@gmail.com

Alternate Email: hello_mechaiq@outlook.com

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