Plug Gauge Automatic Measurement

Background

S Company, a global leader in high-end bicycle components, ranks among the top private-label suppliers in the premium market. Their product lines include drivetrains, suspension systems, wheelsets, and electronic shifting systems.
With a dual structure of in-house production and supplier collaboration, S Company imposes strict requirements on internal thread dimensions and fit tolerances. Across both their own facilities and supply chain, plug gauges are widely used for incoming and in-process inspections to ensure assembly quality and on-time delivery.

Challenges

l   Difficulty in Quantifying and Tracing Plug Gauge Wear
Effective diameter checks still rely on three-line gauges, which require 10–15 minutes per gauge and depend heavily on technician experience. This manual process makes it hard to quantify wear, leading to compromised internal thread quality and increased labor and gauge consumption.

l   High Calibration and Dispute Costs
Disputes with suppliers over tap quality often require third-party gauge calibration. This takes 3–4 weeks and incurs high costs, delaying production and increasing risk.

l   Unclear Decision-Making
Operators cannot easily determine whether a plug gauge should be scrapped or reused. This leads to overuse or premature disposal, increasing costs and the potential for failure.

Solution Automated Optical Measurement with USDV’s TIMI System

S Company deployed the USDV TIMI optical measurement system, enabling automated, high-precision inspection for plug and thread gauges.

Key Capabilities

• 360° non-contact rotary measurement using telecentric imaging and automated rotation platform.
• Full-thread parameter: pitch diameter, major/minor dia., thread pitch, and angle — replacing three-line gauge operations.
• Plug gauge lifecycle database: Automatically logs measurement data by serial number.
• Wear trend analytics: Tracks usage and wear over time, enabling predictive maintenance.

Results

Quality Manager Feedback

“We upgraded plug gauges from simple pass/fail tools to quantifiable, predictive assets — now quality decisions are based on data, not guesswork.”

Value Highlights

• Transformed manual inspection into automated, data-driven quality assurance.
• Reduced calibration costs and shortened decision cycles.
• Improved traceability, consistency, and production confidence.