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Advanced Condition Monitoring Sensor with Sixdime Hertzor

sixdime Hertzor is a high-resolution, 6-axis condition monitoring sensor engineered to detect machine vibrations, anomalies, and early signs of failure. Designed for predictive maintenance, Hertzor monitors acceleration, velocity, and angular displacement in real time, helping industries reduce maintenance costs and extend equipment life.

Sixdime MES

Why Choose Sixdime Hertzor

Built for predictive maintenance applications, sixdime Hertzor leverages advanced AI-enabled diagnostics and high-resolution 6-axis sensing to prevent unplanned downtime and extend equipment life.

Its wireless design, easy deployment, and support from MELSS maintenance & automation expertise make it ideal for industrial equipment, CNC machines, motors, pumps, conveyors, and other critical assets.

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Prevents unplanned downtime by detecting faults early
Advanced AI-enabled diagnostics for predictive maintenance
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Wireless design enables minimal wiring and easy deployment
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Improves machine reliability and performance across assets

How sixdime Hertzor Works

sixdime Hertzor continuously monitors machine vibrations, velocity, and angular displacement in real time. Embedded Edge AI models detect anomalies and predict failures, providing actionable insights for predictive maintenance and minimizing unplanned downtime.

1

High-Resolution Sensing

6-axis sensors capture acceleration, velocity, and displacement, detecting imbalance, misalignment, bearing wear, and lubrication issues with precision.

2

Edge AI/ML Analytics

Embedded anomaly detection models predict failure patterns locally, reducing dependency on cloud processing and enabling real-time actionable insights.

3

Wireless Connectivity

WiFi and BLE connectivity allows remote monitoring, configuration, and integration with predictive maintenance dashboards.

Key Features

Real-time production and OEE dashboard

High-Resolution Vibration Sensing

6-axis acceleration, velocity, and displacement measurement for accurate machine diagnostics.

Digital batch and material traceability

Edge AI/ML Analytics

Embedded anomaly detection predicts failure patterns and enables predictive maintenance.

Automated Industry 4.0 workflows

Wireless Connectivity

WiFi and BLE support for remote monitoring, configuration, and integration with dashboards.

Smart inventory and material tracking

Industrial Design

IP52 polycarbonate enclosure with operating range –10°C to 80°C for harsh industrial environments.

Smart inventory and material tracking

Configurable Sampling

Customizable sampling intervals from 1 Hz to 6 kHz and data intervals of 5–30 minutes.

Technical Specifications

Sensing Temperature

10°C to 80°C

Acceleration Range

±2g | ±4g | ±8g | ±16

Angular Velocity

±125 to ±2000 dps

Product

Data Interface

WiFi (IEEE 802.11 b/g/n )

Sensor Operating Voltage

24V / 1A DC

Polycarbonate

50 X 52 X 35 mm (IP52)

Applications

sixdime Hertzor is suitable for a wide range of industrial equipment, enabling predictive maintenance and condition monitoring across multiple assets.

Motors, pumps, compressors
Spindles, conveyors, fans
Rotating & reciprocating equipment
CNC machines & production lines
Heavy machinery & industrial equipment

See It in Action – sixdime Hertzor

Watch how the sixdime Hertzor condition‑monitoring sensor detects machine vibrations, analyzes anomalies with Edge AI, and helps you avoid unexpected downtime.1

Case Studies

Transforming Operations Across Industries: Real Success Stories with sixdime MES

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The need for traceability

How can manufacturers ensure that every product meets quality standards and remains compliant with industry regulations? The answer lies in robust traceability systems. By tracking each stage of the production process, companies can quickly pinpoint and resolve problems, efficiently recall affected products, and confidently demonstrate compliance during audits.

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Factory Automation

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Ensure Predictive Maintenance Across Your Machines

Leverage sixdime Hertzor to detect early faults, minimize downtime, and improve machine reliability with AI-enabled condition monitoring.

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