MachineCDN vs Augury: Protocol-Native IIoT vs Sensor-Based Machine Health Monitoring

When manufacturing engineers evaluate predictive maintenance platforms, two fundamentally different philosophies emerge: monitor what the machine is already telling you through its PLC, or add external sensors to detect what the PLC can't see.

MachineCDN and Augury represent these two approaches in their purest forms. MachineCDN connects directly to PLCs and reads the data your machines are already generating. Augury attaches vibration and temperature sensors to rotating equipment and uses acoustic AI to detect failure patterns. Both claim to prevent unplanned downtime. Both deliver real results. But they solve different problems, require different infrastructure, and suit different manufacturing environments.

This comparison helps you understand which approach — or combination — makes sense for your operation.

What Is Augury?

Augury is an Israeli-American company founded in 2011 that specializes in Machine Health monitoring through proprietary vibration and temperature sensors. The company has raised over $200 million in funding and focuses primarily on consumer packaged goods (CPG), food and beverage, and pharmaceutical manufacturing.

Augury's core technology is its Halo sensor — a wireless vibration and temperature sensor that attaches magnetically to rotating equipment (motors, pumps, fans, compressors, gearboxes). The sensor captures vibration signatures and temperature data, which Augury's cloud-based AI analyzes to detect developing mechanical faults.

The platform identifies specific fault types:

• Bearing wear: Inner race, outer race, ball/roller defects
• Imbalance: Mass imbalance in rotating components
• Misalignment: Angular and parallel shaft misalignment
• Looseness: Structural and rotating looseness
• Lubrication: Inadequate or contaminated lubrication

Augury sells this as a managed service. Their Machine Health Experts review AI-generated alerts and provide actionable recommendations — essentially outsourcing part of your reliability engineering function.

What Is MachineCDN?

MachineCDN is an industrial IoT platform that takes a protocol-native approach to machine monitoring. Instead of adding external sensors, MachineCDN connects directly to PLCs using standard industrial protocols — Ethernet/IP, Modbus TCP, and Modbus RTU — to read the data your machines are already generating.

An edge device plugs into the PLC's Ethernet port, auto-detects the device type, and begins streaming data to the cloud over cellular connectivity within minutes. No plant network involved. No IT approvals. No sensor installation.

MachineCDN provides comprehensive manufacturing intelligence: real-time machine status monitoring, predictive maintenance with AI-powered analytics, alarm management, OEE tracking, downtime analysis with root cause categorization, energy consumption monitoring, materials and inventory tracking, spare parts management, and fleet management across multiple sites.

The Core Philosophical Difference

This comparison really comes down to a fundamental question: where does the most valuable machine data live?

Augury's position: The most critical predictive data comes from vibration signatures that PLCs don't capture. A bearing developing an inner-race defect produces a specific vibration frequency pattern weeks before any PLC-monitored parameter (temperature, current, pressure) changes. By the time a PLC catches a problem, you've already lost significant bearing life.

MachineCDN's position: PLCs already monitor dozens to hundreds of parameters — motor current, hydraulic pressure, cycle times, temperature, flow rates, spindle speeds, tool wear counters, material consumption. These parameters capture the vast majority of actionable machine intelligence. The biggest gains come from actually monitoring the data your machines already generate, not from adding more sensors.

Both positions have merit. The question is which matters more for your specific operation.

Deployment: Minutes vs Days

Augury's deployment requires physical sensor installation on each piece of rotating equipment:

1. Site assessment (1-2 weeks): Identify critical assets, determine sensor placement
2. Sensor installation (1-3 days per site): Mount Halo sensors magnetically, configure wireless connectivity
3. Baseline learning (2-4 weeks): AI needs to learn normal vibration patterns for each machine
4. Expert review setup (1 week): Configure alert routing and expert review workflows

Total: 4-8 weeks from first sensor to actionable insights on the full deployment.

Each sensor installation requires physical access to the equipment, sometimes during planned downtime. Sensor placement matters — incorrect mounting affects vibration data quality. And each sensor needs wireless network connectivity (cellular or WiFi gateway).

MachineCDN's deployment bypasses all physical installation:

1. Plug edge device into PLC Ethernet port
2. Device auto-detects PLC type and starts reading tags
3. Data streams to cloud via cellular in about three minutes
4. Configure dashboards, alerts, and maintenance schedules

Total: 3 minutes per machine, with data flowing immediately.

No physical sensor installation. No baseline learning period. No wireless network configuration. The maintenance technician who plugs in the device can be monitoring machines before lunch.

Coverage: Rotating Equipment vs Full Manufacturing Intelligence

Augury monitors rotating equipment — and it monitors it well. If your critical assets are motors, pumps, fans, compressors, and gearboxes, Augury provides deep visibility into mechanical health that goes beyond what standard PLC instrumentation captures.

However, Augury's coverage has clear boundaries:

• Only rotating equipment: Hydraulic presses, ovens, CNC machines, injection molding machines, conveyor systems (beyond the drive motor) — these are outside Augury's core monitoring capability
• Only vibration and temperature: Process parameters like pressure, flow rate, cycle time, and material consumption are not captured
• No production context: Augury tells you a bearing is degrading but doesn't know if the machine is running at 60% or 100% capacity, what product it's running, or how the degradation correlates with production conditions

MachineCDN monitors everything the PLC controls — which is the entire machine. Coverage includes:

• All machine types: CNC, injection molding, stamping, assembly, packaging, processing — anything with a PLC
• All PLC parameters: Current, pressure, temperature, cycle time, speed, position, flow, counts, tool wear
• Production context: OEE, utilization, throughput, downtime reasons, shift-based reporting
• Fleet-wide visibility: Multi-location, multi-zone management from a single dashboard
• Inventory and materials: Material tracking, hopper levels, spare parts availability
• Energy consumption: Per-machine energy monitoring for cost and sustainability tracking

The trade-off is clear: Augury goes deeper on one specific type of failure (mechanical faults in rotating equipment) while MachineCDN goes broader across all machine parameters and manufacturing operations.

AI Capabilities: Acoustic Intelligence vs Operational Intelligence

Augury's AI is specialized and genuinely impressive. Their models have been trained on millions of vibration signatures across thousands of machines. The system can:

• Identify specific fault types (bearing, imbalance, misalignment, looseness)
• Estimate remaining useful life for bearings
• Detect lubricant degradation before it causes damage
• Distinguish between urgent and watch-list conditions

This is the kind of AI that requires massive training datasets and domain expertise to build. It's not something you can replicate with a general-purpose analytics platform.

MachineCDN's AI focuses on operational intelligence — understanding machine behavior patterns and predicting operational issues:

• Threshold-based alerting with approaching and active warning levels
• Anomaly detection across all PLC parameters (not just vibration)
• Predictive maintenance scheduling based on actual machine usage patterns
• Pattern recognition for downtime precursors
• Energy consumption anomalies that indicate mechanical degradation

MachineCDN's advantage is breadth: the AI monitors everything the PLC sees, catching problems that manifest in any parameter — not just vibration. A hydraulic system losing efficiency shows up in pressure and cycle time data long before vibration changes. A CNC spindle bearing issue shows up in current draw and surface finish quality parameters. These cross-parameter insights are invisible to a vibration-only monitoring approach.

Pricing Model: Managed Service vs Platform

Augury operates as a managed service with per-sensor pricing:

• Hardware cost per Halo sensor
• Monthly subscription per monitored asset
• Includes Machine Health Expert review
• Gateway hardware for wireless connectivity
• Typical pricing: reports suggest $200-400/asset/month for the full managed service

For a plant with 100 critical rotating assets, annual costs can reach $240K-$480K — plus the operational overhead of sensor installation and maintenance.

MachineCDN operates as a self-service platform with a fundamentally different cost structure:

• Edge device cost per PLC connection (one device can monitor multiple machines on the same PLC network)
• Monthly platform subscription
• No additional per-parameter charges
• No mandatory professional services
• Cellular connectivity included

The cost-per-machine drops dramatically when machines share PLC networks, which they typically do in manufacturing environments. A single edge device can often monitor 5-20 machines, making the per-machine economics significantly more favorable than per-sensor models.

Ongoing Operations: Managed vs Self-Service

Augury provides a managed service experience. Their Machine Health Experts review AI-generated alerts and deliver actionable recommendations. This has real value:

• You don't need a vibration analysis specialist on staff
• Alert quality is high because humans filter false positives
• Recommendations include specific maintenance actions

The downside: you're dependent on Augury's team for alert interpretation. Response times depend on their queue. And the managed service cost is built into your ongoing subscription.

MachineCDN provides a self-service platform that your maintenance team owns:

• Configure your own thresholds and alert rules
• Build custom dashboards for different roles (plant manager, maintenance lead, operator)
• Manage preventive maintenance schedules directly
• Track spare parts inventory and machine parts availability
• No waiting on a third party to tell you what to do

The trade-off: your team needs to be capable of interpreting alerts and making maintenance decisions. For most manufacturing operations with experienced maintenance teams, this isn't a limitation — it's a preference. They want to own their reliability program, not outsource it.

Integration: Sensor Overlay vs Protocol-Native

This distinction matters more than most buyers realize.

Augury operates as a sensor overlay — it adds a new data layer on top of your existing infrastructure. This means:

• Augury data lives in Augury's system, separate from your PLC/SCADA data
• Correlating vibration data with production parameters requires integration work
• You're maintaining two separate data streams (PLC + Augury)
• Integration with CMMS and ERP requires API configuration

MachineCDN is protocol-native — it reads the same data your PLC is already generating:

• Machine data flows through a single system
• Production parameters and health indicators are inherently correlated
• OEE, downtime, and maintenance data live in the same platform
• No separate data streams to reconcile

Who Should Choose Which?

Choose Augury if:

• Your critical assets are rotating equipment (motors, pumps, fans, compressors)
• You need vibration analysis depth that goes beyond PLC instrumentation
• You don't have vibration analysis expertise and want a managed service
• Your primary concern is bearing and rotating element failures
• You're willing to invest in per-sensor hardware across your critical assets
• You operate in CPG or food/beverage where Augury has the deepest domain models

Choose MachineCDN if:

• You need to monitor all machine types, not just rotating equipment
• You want comprehensive manufacturing intelligence — OEE, downtime, energy, inventory
• You need fleet management across multiple locations
• IT involvement is a barrier and you need cellular-based deployment
• You want to be up and running in minutes, not weeks
• Your team prefers to own the reliability program rather than outsource it
• You need production context alongside machine health data
• Budget constraints make per-sensor managed services prohibitive

Consider Both Together if:

• You have a mix of critical rotating equipment and complex manufacturing lines
• You want Augury's vibration depth on 20-30 critical rotating assets while using MachineCDN for plant-wide operational intelligence
• Your budget supports a tiered monitoring strategy

The Practical Reality

According to Deloitte's research on predictive maintenance adoption, the most common barrier to PdM success isn't technology — it's scope. Programs that try to boil the ocean with comprehensive sensor deployments often stall under their own weight.

MachineCDN's approach — connect to existing PLC data, monitor everything, deploy in minutes — removes the deployment barrier that kills most predictive maintenance initiatives. You can start with five machines today and scale to fifty next month. Five weeks to ROI, not five months.

For manufacturers who need plant-wide visibility and predictive maintenance that works from day one, MachineCDN delivers results on a timeline that keeps projects alive.

Ready to monitor your machines without installing sensors? Book a demo and see data flowing in under five minutes.