How Quality Engineers Use Data to Address Root Causes in Manufacturing, Part 2

Last month, we explored in How Quality Engineers Use Data to Address Root Causes in Manufacturing, Part 1 how quality engineers identify patterns through control charts, capability analysis and Pareto charts. Part Two examines how they connect these patterns to underlying causes.

They Structure Problem-Solving with Root Cause Analysis 

Structured problem-solving tools like fishbone diagrams and 5-Why analysis help organize information from multiple sources. Quality engineers use these methods to:

• Examine problems from multiple perspectives (machine, method, material, measurement)
• Move past immediate symptoms to underlying causes
• Document the logical progression from effect to cause
• Involve knowledge from various departments

For example, when products fail in the field, these tools help trace issues back through assembly, component manufacturing, design, and material selection to find the true origin of the failure.

They test cause-effect relationships with designed experiments

Design of Experiments (DOE) methodically tests which factors affect outcomes. Quality engineers employ this approach to:

• Test multiple factors simultaneously
• Quantify the impact of each variable on quality
• Identify interactions between different factors
• Replace opinions with evidence-based conclusions

When teams disagree about what causes quality problems, DOE provides objective evidence about which factors actually matter, preventing cycles of trial-and-error fixes.

They model relationships with statistical regression

Regression analysis establishes mathematical relationships between process inputs and outputs. Quality engineers apply these models to:

• Predict how changes in process settings will affect quality
• Distinguish correlation from causation
• Optimize process parameters for best results
• Account for multiple variables simultaneously

By modeling relationships mathematically, teams can target the specific process parameters that most directly influence product quality.

They connecting data to root causes

The core value of quality engineering lies in connecting manufacturing data to the fundamental causes of problems. This systematic approach:

• Prevents repeated occurrences of the same issues
• Moves beyond temporary fixes to permanent solutions
• Helps teams distinguish between symptoms and causes
• Builds process knowledge that improves future designs

In organizations that successfully implement Six Sigma and Lean Manufacturing principles, quality engineers provide the analytical bridge between data collection and effective action. Their work turns the principle of addressing root causes into practical reality on the factory floor.