In reality, the burden of training new staff to perform critical quality control measurements accurately is far greater than many organisations anticipate.
Manual QC depends on people, not just procedures
Unlike automated instruments, a Hegman gauge relies heavily on human judgement. Operators must visually identify the exact point where coarse particles first appear; a decision that is inherently subjective. Lighting, eyesight and in particular, experience all influence the result.
For new staff, this creates an immediate problem: you can teach the procedure in minutes, but in reality it takes years of practice before results are consistent and trustworthy.
Training time ≠competency
One of the biggest risks in QC training is assuming that “trained” means “competent.”
New operators often:
• Struggle to distinguish true particle streaks from artefacts like air bubbles or surface texture
• Apply inconsistent pressure or drawdown speed
• Interpret the same sample differently from experienced colleagues
Until experience is built, results can vary significantly, not just between operators, but for the same operator on different days. This means supervisors must spend extended periods running parallel measurements, reviewing borderline results and restricting new staff from signing off critical data. All of this adds hidden cost and slows productivity.
The business impact
The implications go beyond training time:
• Delayed sign-off for new hires
• Increased risk of inconsistent QC decisions
• Higher supervision load on senior staff
• Potential quality escapes or false rejections if judgement is off
In regulated or high-value manufacturing environments, these risks can’t simply be accepted. But eliminating them through training alone is expensive and slow.
A question worth asking
When a quality control activity is critical to product release, consistency, or customer trust, organisations need to ask:
How much of this process depends on operator experience, and how long before we truly trust the result?
For many manual measurements, the real challenge isn’t the tool, it’s the human learning curve behind it. In an industry under pressure to do more with fewer resources, automation isn’t about replacing people. It’s about removing risk, reducing training burden, and making quality truly repeatable.
Further reading >
Labman tested human operators. The results were interesting:
https://www.labmanautomation.com/blog/tidas-how-costly-is-operator-variance/
TIDAS – The automated Hegman gauge analyser:
https://www.labmanautomation.com/portfolio/products/automated-hegman-gauge-analyser/