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WHICH THICKNESS MONITORING SOLUTION IS BEST FOR YOUR COMPANY?

Build Your Own vs. Mate Gauge

At a glance, building your own thickness monitoring solution can feel like the most logical step — especially for highly capable engineering teams. You already have access to sensors, a machine shop, engineers, and a line that needs measuring. It seems like a solvable problem. And in some cases — and at some companies — it is.​

But for large manufacturers — those pushing more than $1M of material annually on multi-shift, high speed lines — the risks, costs, and performance demands outgrow what DIY can reasonably handle. That’s when a basic set-up stops being good enough, and a full-system solution like Mate Gauge becomes essential.

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Build Your Own

Mate Gauge​

A fully integrated thickness monitoring system — prebuilt with precision hardware, mgOS software, PLC integration, and full lifecycle support. Designed for industrial lines, it installs fast, delivers accurate data, and requires no internal maintenance team to keep it running.

A do-it-yourself thickness monitoring system —usually a combination of off-the-shelf sensors, custom frames, and internal software. It works in theory, but scaling to production demands time, money, and long-term engineering support most teams underestimate.

Comparison at a glance

Compare the pros and cons of buying a Mate Gauge system vs. building your own thickness monitoring solution.​

Mate Gauge (Pre-Built Solution) Build Your Own (DIY System)
Risk-free accuracy: System tested, validated, and verified by subject-matter experts in real-world labs. Accuracy risk: Sensors may drift due to temperature or misalignment—without built-in auto-calibration.
Optimized system design: Robust, heat-stable, dirt-resistant scanning platforms designed for harsh industrial environments. Time-consuming integration: Custom mechanical design, environmental compensation, and testing must be built from scratch.
Lower total cost of ownership: One-time CapEx, no internal development, minimal maintenance, faster ROI. Higher TCO: Hidden internal costs, engineering delays, and future upgrades inflate long-term expenses.
Plug-and-play data access: Real-time reporting, exports, and dashboards — all standard. Limited data visibility: Often lacks logging, export tools, or structured access for operators and engineers.
Purpose-built signal processing: Clean, usable data tailored to your line. Raw outputs: General-purpose software or APIs require additional filtering and interpretation.
Robust diagnostics: Live KPI views, calibration health, and sensor drift detection. Limited system awareness: Operators may not know if the system is accurate, calibrated, or aligned.
Dedicated support team: Engineers, integrators, and service professionals ready to assist across your org. Staff-dependent: System knowledge often lives with one or two internal experts, introducing continuity risk.
Industry-tuned applications: mgOS apps are built for real manufacturing environments, not lab use. Frankenstein solutions: General-purpose tools cobbled together into a fragile ecosystem.
Future-proofed: Ongoing support for API changes, field conditions, hardware obsolescence. One-off build: Scaling, updating, or replicating across lines is slow, costly, and error-prone.
Fully documented + controlled: Manuals, diagrams, spares lists, and escalation plans included. Under-documented: Knowledge silos and version mismatches create maintenance headaches.

What many companies think is required to build their own systems is just the tip of the iceberg.


DIY builds may get you 80% of the way there with hardware, basic measurements, and a dashboard. But you don’t have a viable solution without the last 20%.