Quality engineers help manufacturing teams identify and solve the underlying causes of production problems through data analysis.

By using statistical tools to uncover root causes, their work connects the principles of methodologies such Six Sigma and Lean Manufacturing. Here is how:

They work with control charts to find process changes

Control charts track measurements over time and distinguish between normal variation and actual process changes. Quality engineers use these charts to:

• Identify when a process shifts from its normal pattern
• Determine if a problem is random or systematic
• Document when process improvements take effect
• Establish stable baselines for future comparison

When a machine starts producing parts with increasing variation, control charts show the pattern before measurements exceed specification limits, allowing teams to address issues before they get worse.

They quantify process performance with capability analysis

Capability analysis compares process performance to specification requirements. Cpk and Ppk values measure how consistently a process meets targets. Quality engineers apply these metrics to:

• Determine if process improvements actually increased consistency
• Quantify the gap between current performance and requirements
• Predict defect rates based on process behavior
• Compare performance across different production lines

A manufacturing line with low capability scores will continue to produce defects regardless of operator vigilance or inspection efforts, pointing to the need for underlying process improvements.

They prioritize improvement with pareto analysis

Pareto analysis applies the 80/20 principle to manufacturing issues. Quality engineers use this tool to:

• Rank defect types by frequency or cost
• Focus resources on the most significant problems
• Track if solutions actually reduce the targeted defects
• Prevent teams from chasing minor issues while major ones persist

When a factory faces multiple quality issues, Pareto analysis prevents teams from superficially addressing small problems instead of fixing the bigger, more important ones.

Quality engineers use data to spot problems early, measure how well processes are working and focus on fixing the biggest issues. But finding patterns is just the first step. In next month’s blog, we’ll look at how they dig deeper to uncover the real causes of defects using problem-solving tools, experiments and data models— making long-term improvements.