See patterns across units
Look beyond a single passing or failing value.
Process drift & SPC
Can we see a process changing before the next quality review?
Give engineers a view of measured behavior and configured statistical signals, so they can investigate a developing pattern while its production context is still available.
A practical path from evidence to action
- Capture measurementsAttribute, unit and process context
- Inspect the trendSelected population and recipe limits
- Review statistical signalsConfigured SPC rules
- Investigate and respondEngineer-reviewed process action
Separate limits from behavior
Distinguish an acceptance requirement from a statistical signal.
Keep the investigation grounded
Follow the signal back to its recorded context.
Passing results can still deserve a closer look.
A measurement can remain within specification while its behavior changes. IntelliTrack™'s trend and SPC views help your team examine a sequence of measurements and configured signals, rather than waiting for a summary of rejects to raise the question.
How it works in IntelliTrack™
Use a meaningful population and inspect the signal.
Define the measurement
Capture the attribute consistently with the relevant product, equipment, recipe and units.
Review the trend and limits
Select an appropriate population and time window. Compare the measured behavior with the applicable specification and statistical context.
Investigate the exception
Use configured SPC signals and notifications to focus review. Confirm data quality and process context before changing the process.
Illustrative manufacturing scenario
A press-fit measurement moves gradually toward a limit.
Individual assemblies still pass, but the measured force pattern changes. Engineering reviews the trend alongside the recipe and production window to decide whether the pattern needs a setup check, additional sampling or another investigation.
Attribute trend
What you can inspectOrdered measurements and the selected population.
Your team's decisionDecide whether the comparison is meaningful and representative.
Recipe specification limits
What you can inspectThe defined acceptance limits for the process context.
Your team's decisionDetermine whether measured results meet the requirement.
SPC signals
What you can inspectStatistical rule signals for the configured evaluation.
Your team's decisionInvestigate special behavior without assuming it proves the cause.
Give the workflow the context it needs.
- Define representative sampling, consistent units and appropriate product/equipment populations. Mixed processes and missing measurements can distort the interpretation.
- Specification limits and statistical control limits serve different purposes. Review the basis for both with the people responsible for the process.
- Notification evaluation and a chart can use different data windows. The SPC signal stream uses its configured baseline since the relevant recipe change; a displayed chart may show only the latest selected values.
Practical questions
What to know before you start.
Is SPC the same as checking whether a value passes its limits?
No. Specification checks compare a result with an acceptance requirement. Statistical process control examines patterns in a series of results. A statistical signal can warrant review even when individual values remain in specification.
Will a signal automatically adjust a recipe?
No. Signals support awareness and investigation. Recipe changes still follow your engineering review and approval process.
Why might a notification not match the chart I just opened?
Check the product, attribute, recipe and data windows. Notification evaluation can use a different baseline from the chart's selected latest values. Compare the same context before drawing a conclusion.
Can SPC guarantee we will detect every defect early?
No. Its usefulness depends on the measurements, sampling, configured rules and the type of failure. It complements process knowledge and quality controls; it does not guarantee defect prediction.
What do we need for a useful demonstration?
Bring representative measurement history, its units and sampling method, plus the applicable specification limits. A known stable period and a known process change make a useful comparison.
Bring an attribute that deserves closer attention.
We can inspect its units, sampling, recipe limits and time window, then work through the signals your team would want to investigate.