More scrap on Monday morning than on Wednesday: coincidence or a measurable problem?
Production is running, processes are defined – and yet quality fluctuates. Scrap rates suddenly increase even though, at first glance, nothing has changed. Perhaps defects occur more frequently after a shift change, following a machine shutdown, or at certain times of the day.
Coincidence? Possibly. More likely, however, a relevant influencing factor has not yet been identified or properly measured.
This is exactly where professional measurement and testing comes into play. Data alone does not create transparency. What matters is measuring the right parameters using the right methods and interpreting the results in the context of the entire process.
Typical influencing factors may include:
Temperature and humidity
Material properties and batch variations
Tool wear
Machine condition and machine settings
Forces, pressures, torques or vibrations
Process and cycle times
Start-up and warm-up phases
Operator influences
Upstream or downstream process steps
And much more
The key question is therefore not simply:
“What data do we have?”
But rather:
“Which physical and process-relevant parameters do we need to measure in order to reliably identify the root cause of the problem?”
More data is not automatically the solution
Modern production systems already collect large amounts of data. What matters, however, is not how much is measured, but whether the right parameters are being measured.
This requires an appropriate measurement strategy: Which physical parameters are relevant to the problem? Where and with what level of accuracy should they be measured? And what correlations exist between measurement values and quality deviations?
Only by combining measurement methodology, data analysis and engineering expertise can individual measurement values be transformed into actionable process knowledge.
This enables root causes to be identified systematically, processes to be stabilised, and scrap and rework to be reduced – resulting in significant cost savings.
At cross-ING, our Measurement & Testing experts support companies in defining the right parameters and measurement methods, interpreting data from a technical perspective, and translating the findings into concrete optimisation measures.
Because what matters is not how much you measure – but what you learn from it.
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