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Manufacturing Data Quality: The Overlooked Lever in the Cost of Quality

by | Aug 6, 2026

Summary

Manufacturing quality depends as much on trusted data as trusted processes, and improving data integrity can significantly reduce hidden quality costs, eliminate manual inefficiencies, and enable more reliable digital manufacturing initiatives.

Ask anyone what quality means and they’ll likely describe an experience: a product that works reliably, fits well, and lasts.
But that experience is not an accident. It is the outcome of hundreds of engineering decisions across design, manufacturing, and inspection — and every one of those decisions rests on data. 

When companies optimize the cost of quality, they typically focus on *what* is produced and *how*: fewer defects, tighter processes, better equipment. All valuable.

Yet the integrity of the data behind each quality decision is rarely examined with the same rigor. And here is the reality check: results are transcribed by hand. Data arrives from different systems in different formats. Some was captured incorrectly at the source — and the issue often surfaces only once it has become costly. 

Read this article in full here.

Metrologic DCS

Metrologic DCS combines best-in-class industrial metrology and dimensional engineering expertise. Metrologic Group contributes its best-in-class universal 3D metrology software, multi-sensor measurement execution, and interoperability across machines and technologies. DCS is the world leader in dimensional engineering and variation analysis. Together, these complementary capabilities create a unique, end-to-end approach to quality.

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