OptimaFlow

DFSS

Design for Six Sigma - building quality into products and processes

Not Started - Planned

AI Query Interface

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Core Principles

Robust processes and designs

Design for Six Sigma methodology

Quality Function Deployment (QFD)

Prevention over detection

Design Review Completion

45%

+8.0%

Target: 90%

50%

Predicted: 62%75% confident

New Product Quality Score

85%

+5.5%

Target: 95%

89%

Predicted: 89%78% confident

Process Capability (Cpk)

1.33Cpk

+0.1%

Target: 1.67Cpk

80%

Predicted: 1.45Cpk80% confident

Real-Time Events & Alerts
1

OPPORTUNITY

low

...

Design Optimization Potential

Generative AI analysis of Product Z design suggests alternative geometry reducing material cost by 8% with no performance compromise.

Impact: Annual material savings of $67K on Product Z alone. Methodology applicable to 12 other products.

Recommended Action: Engineering review of AI-generated design. Prototype and test 5 samples. If validated, update design spec for next production run (Q2 2026).

Explainability: AI explored 5,800 design variations. Recommended design maintains all critical dimensions, passes FEA stress analysis, and simplifies manufacturing (DFM score: 87/100).

RL Score: 73%

AI Confidence: 84%

AI-Powered Improvement Opportunities

Total Potential: $642K/year

Generative Design with AI

Impact: high

Effort: high

$245K/yr

6-8 months

87% AI confidence

Use generative AI to explore thousands of design alternatives based on constraints, automatically optimizing for manufacturability, cost, and quality.

RL Recommendation: Start with next new product design. Define constraints clearly (cost, weight, strength). Run parallel track with traditional design for comparison.

Predictive Reliability Modeling

Impact: high

Effort: high

$198K/yr

5-7 months

89% AI confidence

ML models that predict product failure modes and reliability metrics during design phase, reducing field failures by 60% before production.

RL Recommendation: Train on 10 years of warranty/failure data. Start with highest-failure product families. Validate predictions against accelerated life testing.

Design for Manufacturability Scorer

Impact: medium

Effort: medium

$112K/yr

4-5 months

91% AI confidence

Real-time DFM scoring system that evaluates CAD designs and provides immediate feedback on manufacturability, assembly ease, and cost drivers.

RL Recommendation: Integrate with CAD software. Train on historical DFM issues from production. Alert designers when score drops below 75/100.

Automated QFD Analysis