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Quality Control

Quality Control Dashboards

Inspection and process data turned into live SPC dashboards — quality control moves from a monthly audit into a real-time signal the line can act on.

Power BISPCControl ChartsDMAIC
Quality Control Dashboards — illustrative photography

The challenge

Quality was reviewed after the fact. Defects were counted in a monthly spreadsheet, control charts were drawn by hand, and by the time a trend was visible the process had already produced a batch of scrap. Nobody could tell, in the moment, whether the line was in control.

The process

End to end — how data moves from source to decision.

Inspection Data
Gauges, checks, scrap logs
SPC Engine
X̄-R, control limits
Capability
Cpk / DPMO
QC Dashboard
Live control state

Our approach

How we structured the work.

01
Connected inspection capture — manual checks and gauge output — into one governed dataset instead of a monthly re-key.
02
Implemented the SPC maths properly: X̄-R charting with correctly calculated control limits, not fixed tolerance bands mislabelled as control.
03
Added capability and DPMO tracking so quality could be spoken about in the same statistical language across every line.
04
Surfaced it all on a control-room dashboard that shows, right now, whether each characteristic is in or out of control.

What the reporting looks like

An illustrative view of the dashboards this engagement produces. All figures are sample data for illustration only — not client results.

Quality Control — SPC Dashboard
Sample data · illustrative
99.1%
First-pass yield
↓ DPMO
Trend down
1.62
Cpk
Live
Control state

X̄ control chart (with UCL / LCL)

Defect Pareto

SurfaceDim.AssyLabelOther

Outcome

What changed
Operators and quality engineers see the control state live. Out-of-control signals are caught while the batch is still running, and capability is tracked continuously instead of reconstructed at month-end.

Related work

Other engagements with a similar shape.

Process × Intelligence

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