Top 7 Real-World DOE Case Studies in Automotive, Aerospace & Manufacturing

Why case studies?

Seeing DOE applied on real parts and processes is what turns the math into money. These seven representative cases show how teams framed problems, chose designs, ran analyses, and translated results into process changes.

1) Automotive Paint Shop — Cutting Orange Peel & Dirt Nibs

Problem: Visible surface defects after top-coat.
Design: 2^(7–3) fractional factorial → confirmatory central composite design (CCD).
Factors: Flash time, booth humidity, atomizing air, fluid flow, gun-to-panel distance, line speed, bake profile.
Analysis: Pareto + normal plots of effects; interaction plots; RSM for curvature.
Outcome: New paint window with tighter humidity + flash controls; SOP checklist.
Transferable lesson: Screen broadly, then switch to RSM to dial in finish quality.

2) Aerospace Composite Cure — Reducing Porosity

Problem: Excess voids/porosity post-autoclave.
Design: Definitive Screening Design (DSD) for continuous factors.
Factors: Ramp rate, vacuum integrity, dwell pressure, dwell time, vent path, layup moisture conditioning.
Analysis: Sparse models with quadratic terms; ridge analysis for optima.
Outcome: Robust cure recipe less sensitive to small vacuum leaks.
Transferable lesson: DSDs expose curvature early without a big run count.

3) Precision Machining — Stabilizing Hole Positional Tolerance

Problem: Positional out-of-tolerance under tool wear.
Design: Split-plot (hard-to-change = fixture strategy; easy-to-change = feeds/speeds/coolant).
Factors: Fixture clamping pattern (whole-plot), spindle speed, feed per rev, tool coating, coolant type.
Analysis: Mixed-effects model honoring whole-plot structure; variance components.
Outcome: New clamping + speed/feed window that maintains true position over tool life.
Transferable lesson: Use split-plot when setup changes are costly.

4) Injection Molding — Warpage & Short Shots on a Thin-Wall Part

Problem: Deformation and incomplete fill.
Design: Taguchi L18 (screen) → CCD (optimize).
Factors: Melt temp, mold temp, injection speed, holding pressure/time, venting, gate size, screw back-pressure.
Analysis: S/N ratios for robustness; RSM surface + contour plots to balance warpage vs shorts.
Outcome: Gate redesign + pressure/time window; scrap and rework significantly reduced.
Transferable lesson: Taguchi for rugged screening, then RSM to reconcile competing CTQs.

5) Electronics Assembly — Solder Joint Reliability

Problem: Intermittent opens after thermal cycling.
Design: Plackett–Burman (screen) → 2^k factorial on top contributors.
Factors: Paste type, stencil thickness, peak reflow temp, soak time, conveyor speed, pad finish, nitrogen flow.
Analysis: Half-normal effects; interaction heatmaps; Weibull on life data.
Outcome: Paste/stencil/reflow combo that lifts first-pass yield and cycling life.
Transferable lesson: Cheap screening first; validate interactions before locking profiles.

6) Chemical Process — Yield Variability in a Batch Reaction

Problem: Wide lot-to-lot yield.
Design: Central composite design with center-points.
Factors: Catalyst loading, solvent ratio, pH, temperature, hold time.
Analysis: Quadratic model; canonical analysis; overlay plots to map feasible high-yield region.
Outcome: Narrowed recipe + in-process pH control; SPC limits updated.
Transferable lesson: Overlay contour plots help communicate “safe operating envelopes.”

7) Metal Forming — Springback on a High-Strength Steel Bracket

Problem: Dimensional drift after forming.
Design: Mixture-process DOE (composition + process factors).
Factors: Alloy content ratios (mixture), blank holder force, draw bead height, lube type, forming speed.
Analysis: Mixture-process interaction model; desirability optimization for angle + flatness.
Outcome: Adjusted lube/force strategy and spec window to tame springback.
Transferable lesson: When both recipe and process matter, use mixture-process models.

How to replicate these wins on your line

  1. Frame the CTQ (metric, spec, and failure cost).

  2. Pick a design for your constraints (screening vs RSM, split-plot for hard-to-change factors).

  3. Balance discovery and confirmation (screen → optimize → confirm runs).

  4. Codify the window (SOPs, control plans, SPC limits).

  5. Lock learning (pre-flight checklists, guardrails in MES).

Want guided practice?

If you’d like to reproduce these patterns on your parts, Excedify’s DOE Training walks you through screening → modeling → optimization with assignments and a free preview:
https://www.excedify.com/