IPA Blog

When “Non-Conformance” Becomes the Norm: How One Manufacturer Broke the Cycle

Written by Sologic | 1 Feb 2026, 10:30 PM

Quality issues don’t just cost time — they erode confidence.

A manufacturing plant was struggling with repeated non-conformances (NCRs) in its final inspection process. Each report pointed to a similar defect: improperly assembled components that didn’t meet specification.

Every time it happened, the team acted quickly — repaired the parts, tightened supervision, and reminded staff to be more careful.

But the defects kept coming back.

It wasn’t until they applied Root Cause Analysis (RCA) that they discovered the issue wasn’t about attention — it was about system design.

The Problem

The NCRs involved minor misalignments during component assembly. These were simple to rework, but frequent enough to cause costly delays and frustration on the shop floor.

Production management assumed it was a training or workmanship issue. After all, the parts were being handled by experienced technicians — and errors seemed random.

But “random” problems are rarely random.

The RCA Process

Using Sologic’s 5-step methodology, the investigation began by collecting data from recent NCRs — when they occurred, who was involved, which shift, which part number, and what equipment was in use.

Mapping these details in a cause-and-effect diagram revealed an interesting pattern:

Most of the errors were traced to a specific workstation and a particular batch of tooling used during assembly.

When the team examined the tools more closely, they found wear and tolerance drift that made perfect alignment nearly impossible — even for skilled operators.

The Root Causes

The investigation identified three underlying issues:

  • Tool wear undetected – No formal inspection schedule existed for that particular jig.
  • Documentation gap – The assembly procedure didn’t specify exact tolerance limits or inspection intervals.
  • Cultural assumption – Operators were expected to “feel” when something was off, rather than verify through measurement.

In short, the process relied on tribal knowledge instead of documented control.

The Corrective Actions

The solutions focused on prevention, not correction:

  • Introduced scheduled jig inspections with tolerance tracking.
  • Updated work instructions with clear visual aids and measurement criteria.
  • Standardised training so all operators followed the same verified process.

The result? NCR frequency dropped by more than 80% within two months — and confidence in the process returned.

The Lesson

Every NCR is feedback. It’s your process telling you that something doesn’t fit — literally or figuratively.

When teams use structured RCA instead of guesswork, they stop chasing symptoms and start improving systems.

That’s the real goal of Root Cause Analysis — not just to close a report, but to prevent the next one from ever happening.

Final Thought

If you’re logging the same problems month after month, you don’t need more reports — you need better reasoning. Structured RCA turns non-conformance into non-recurrence.

 

Read the example problem here:

Manufacturing NCR Example Problem https://www.sologic.com/en-au/resources/example-problems/manufacturing-ncr