Where quality meets data

Making quality visible in real time, not just reportable at month-end.

Most quality systems live in binders and spreadsheets that get reviewed once a month. I design KPI dashboards and IIoT-enabled monitoring systems that put defect rates, process capability and audit readiness in front of the people who can act on them — daily.

Focus areas

Four categories of system work

01

Energy optimisation

Monitoring dashboards for kiln and utility energy consumption against production output.

02

Materials & process control

Live tracking of process parameters against control limits — the digital version of an SPC chart.

03

Predictive maintenance

Condition-based monitoring concepts that shift maintenance from reactive to predictive.

04

Machine vision QC

Exploring vision-based inspection to catch surface and dimensional defects earlier in the line.

Sample view

What a quality operations dashboard looks like

An illustrative mock-up — the real dashboards are tailored to each factory's process and data availability.

Quality operations — factory floor viewLive
96.4%
First-pass yield
1.8%
Defect rate
91%
CAPA on-time closure
3
Open NCRs
Implementation approach

Phased, not big-bang.

Dashboard and IIoT rollouts fail when they try to digitise everything at once. I sequence implementation across roughly 30 months — starting with the highest-leverage, lowest-friction data source, proving value, then expanding scope.

Phase 1 — FoundationManual KPI dashboard
Phase 2 — AutomationSensor / IIoT integration
Phase 3 — PredictionPredictive maintenance
Phase 4 — VisionMachine-vision QC

Want a KPI dashboard your management team will actually open?

Let's talk about what data you already have and what a Phase 1 build could look like.

Discuss a build