Statistical Analysis & Process Capability
A retired global quality executive with 30+ years of manufacturing leadership experience who helps organizations solve difficult quality and process problems through disciplined, evidence-based methods.
What This Solves
Most organizations don’t struggle because people make mistakes — they struggle because the process is quietly doing something no one sees. Variation creeps in. Stability erodes. Capability drops. And leaders make decisions based on assumptions instead of evidence.
My statistical analysis and process capability services expose the true drivers of variation, stability, and manufacturing performance. You get clarity on:
Why defects occur
Where variation comes from
Whether the process is stable
Whether it can meet requirements consistently
What actions will actually move the needle
This isn’t about charts — it’s about giving you the confidence to make decisions that improve performance, reduce waste, and eliminate recurring problems.
My Approach
Define the process and measurement boundaries
Establish process scope, Critical-to-Quality (CTQ) characteristics, measurement requirements, and performance expectations to ensure analysis focuses on the variables that matter most.
Verify Measurement System Capability
Validate measurement accuracy, precision, and repeatability through MSA, Gage R&R, bias, linearity, and stability assessments before analyzing process performance.
Collect representative data
Gather data that reflects actual operating conditions rather than isolated or selective samples.
Analyze variation (common vs. special cause)
Separate normal process variation from significant process signals to identify where improvement efforts should be focused.
Evaluate stability using control charts
Assess process predictability and identify trends, shifts, or instability that affect performance.
Calculate capability (Cp, Cpk, Pp, Ppk)
Determine the process's ability to consistently meet specifications and customer requirements.
Identify drivers of variation
Pinpoint the specific factors contributing to instability, defects, or reduced capability using data-driven analysis.
Recommend targeted improvements
Develop practical actions that reduce variation, improve capability, and increase process performance.
Validate results with follow‑up data
Confirm that implemented improvements deliver measurable and sustainable results.
What Clients Gain
Clear understanding of process performance
Reduced variation and improved consistency
Improved process capability (Cp, Cpk, Pp, and Ppk)
Lower scrap and rework costs
Improved customer satisfaction
Better production predictability
Increased confidence in process decisions
Data-driven improvement opportunities
Stronger process control and stability
Stronger confidence in manufacturing and quality decisions
When Companies Need This
Process capability is below customer requirements
Scrap and rework levels remain high
Production results vary from shift to shift
Control charts show instability or drift
Manufacturing processes cannot consistently meet specifications
New processes require capability validation
Customer complaints indicate excessive variation
Improvement efforts are not producing measurable results