SURRO MCM | SURROMIND

Overview AI Machine Condition Monitoring

Sensor-driven anomaly detection for predictive maintenance and quality inspection.

Current Challenges

Operator-dependent judgment

Variability

Judgment varies by operator.

Missed Signals

Subtle vibration/noise signals are overlooked.

Reactive maintenance

Downtime Losses

Failures cause long recovery.

No Foresight

Failure timing is unpredictable.

SURRO MCM

Automated Data & AutoML

Multi-sensor data, collected and modeled automatically.

Real-Time Anomaly Detection

Subtle abnormal signals, detected across channels.

Quality Inspection

AI-standardized Pass/Fail for motors and components.

Predictive Maintenance

RUL-based schedules before failures occur.

How it Works From multi-sensor signals
to real-time predictive operations

SURRO MCM connects equipment and turns multi-sensor signals into
real-time anomaly, quality, and maintenance decisions on-prem.

1

Connect

Stream multi-sensor signals
to a unified dashboard.

2

Detect

Flag subtle deviations
against learned
normal patterns.

3

Diagnose

Identify causes and
output Pass/Fail
or RUL.

4

Evolve

Auto-label new data,
retrain with AutoML,
deploy on-prem.

Schematic Four core modules,
one unified AI architecture

SURRO MCM links four modules — data flow, anomaly detection, diagnosis & prediction, model lifecycle — into one closed AI loop.

Operation No-code AI workflow, led by field engineers

SURRO MCM guides field engineers from pipeline setup to live inference across four no-code tabs — no scripting required.

Data Management
Data Preprocessing
Model Training & Evaluation
Deployment & Application

Data Management

Set up equipment pipelines and upload raw signals.

Pipeline Setup

Define equipment lines and map sensor channels by asset.

Raw Signal Upload

Upload vibration, thermal, electrical, and CAN data in bulk.

Search & Status

Filter datasets by equipment, status, or tag from one search bar.

Data Preprocessing

Pick channels and features with live preview.

Channel Selection

Select sensor channels relevant to each target failure mode.

Feature Extraction

Generate spectrogram, FFT, and statistical features with no code.

Live Preview

See preprocessing changes instantly as you adjust each component.

Model Training & Evaluation

Run AutoML and track live training progress.

AutoML Run

Start model training with one click, without scripting.

Live Progress

Track loss, accuracy, and ETA in real time during training.

Performance Report

Selects the most suitable model for field deployment based on evaluation results.

Deployment & Application

Deploy trained models on-prem and run live inference.

On-Prem Deployment

Deploy the selected model to the field server in one step.

Live Inference

Run the model on incoming sensor streams and view results in real time.

Result Review

Review inference results and trigger retraining when drift is detected.

Key Features Four capabilities,
one industrial AI platform

SURRO MCM combines high-resolution detection, unseen-defect sensing, no-code AutoML,
and RUL-based maintenance for practical industrial AI operation.

High-Resolution
Anomaly Detection

Ensemble deep models on multi-channel waveform and spectrogram — 96% accuracy.

Unseen Failure Sensing

Unsupervised autoencoders flag undefined defects — 100% on 8 rare classes.

No-Code AutoML

Auto-label, train, and deploy on-prem — no scripting, no tuning.

RUL-Based Preventive Maintenance

Real-time RUL turns vibration, current, and thermal signals into preventive service windows.

References Proven outcomes across
real industrial environments

SURRO MCM delivers site-specific outcomes across four industries — automotive, railway, home appliance motors, and water & chemical.

Automotive Fault Diagnosis
Railway Equipment Monitoring
Home Appliance Motor QC
Water & Chemical Infrastructure

Automotive Fault Diagnosis

Acoustic-based diagnosis replaces technician hearing — 96% ensemble accuracy.

Ensemble Accuracy 96%

Technician Hearing Replacement

Railway Equipment Monitoring

Always-on monitoring where manual inspection is impossible — RUL-driven preventive service.

RUL Always-On Monitoring

Home Appliance Motor QC

Acoustic-based diagnosis replaces technician hearing — F2 1.0 ensemble accuracy.

F2-score 1.0 End-of-Line QC

Water & Chemical Infrastructure

Acoustic-based diagnosis replaces technician hearing — −30% ensemble accuracy.

−30% Slurry Deviation

8 Rare Classes Caught