Reducing scrap variation in agricultural equipment manufacturing

Challenge

Scrap rate on a critical weld joint rose from 2% to 7% over two weeks. Production pressure made a full line stop unacceptable without data-backed direction.

How they worked it

1. Opened a 5W2H quality alert to define the tooling-change symptom, affected joint, and containment scope before line trials. (5W2H Builder)
2. Ran Exploration Cascade to split weld-process vs. pre-weld setup paths, then Chi-Square to confirm scrap differed by fixture zone. (Exploration Cascade, Chi-Square Test)
3. Completed attribute MSA on visual weld-defect calls so defect maps reflected process variation, not inspector disagreement. (Attribute MSA Study)
4. Updated PFMEA for fixture clamp sequence and re-baselined the control plan with the winning weld settings. (PFMEA / DFMEA Lite, Control Plan Builder)

Approach

1. Mapped defect locations on the weld joint to validate the fixture-zone contrast from Chi-Square.
2. Ran SPC on pre-weld gap and post-weld penetration to see which feature drifted first.
3. Designed a small factorial DOE on amperage, travel speed, and fixture clamp force.
4. Exported the investigation package for supplier chargeback and ongoing SPC monitoring.

Tools used

• 5W2H Builder
• Exploration Cascade
• Chi-Square Test
• Attribute MSA Study
• Defect Location Map
• SPC Workbench
• DOE Tool
• PFMEA / DFMEA Lite
• Control Plan Builder

Outcome

Scrap returned to baseline within one production week. PFMEA and control-plan updates captured the fixture learnings and supported supplier chargeback without a line shutdown.

Illustrative workflow based on common agriculture equipment quality patterns — not a specific customer engagement.