Sheetmetal Forming Analysis

AI-FORM: AI-Based Interactive Multi-Objective Optimization for Sheet Metal Forming

AI-FORM, developed by C3P Engineering Software International Co., Ltd., is the first AI-based interactive multi-objective optimization software specifically designed for sheet metal forming. With over 20 years of industry expertise, it provides an end-to-end solution for the stamping industry, covering:

• 3D part DFM (Design for Manufacturing) analysis
• Quotation & blank sheet engineering
• Step-by-step die face design guidance
• Knowledge-Based Engineering (KBE)
• Advanced FEM simulations
• AI-driven automatic optimization

As industrial demands grow, stamping processes and products become increasingly complex. While CAD/CAE technologies and parallel computing have reduced simulation time, optimizing designs for the best solution remains a key challenge. AI-FORM addresses this with geometry-driven optimization, enabling rapid evaluation of multiple design alternatives to shorten product cycles and enhance quality.

Case Study 1: Oil Panel Stamping Optimization

Initial Challenge

Complex shape with uneven drawing depth caused serious wrinkles and cracks during stamping.

[Initial simulation showing defects]

Project Background

The oil panel's saddle feature required optimization of:

• Blank sheet size
• Holding force
• Drawbead shape/dimensions

Traditional trial-and-error CAE methods proved too slow and inefficient.

Optimization Strategy

[Schematic of input parameters]

Key variables selected:

• Blank sheet dimension (offset)
• Drawbead location/length (DB1, DB2)
• Drawbead restrain force

Optimization Criteria

• Maximum thickness in saddle region (wrinkle detection)
• Metal flow via blank sheet sensor
• FLD cumulative value at part top (rupture prediction)

Two-Phase Approach

Phase I: Design of Experiments (DOE)

Identified feasible process window

Phase II: Particle Swarm Optimization (PSO)

Precisely located optimal parameters

[Parallel coordinates plot of PSO results]

Optimal Solution Found

• Blank sheet offset: 21-63mm
• Drawbead length: 50-89mm
• Resistance force coefficient: 0.29-0.4

[Final simulation showing defect-free result]

Case Study 2: CAD-Driven Optimization for Cracking

Initial Challenge

Complex geometric features caused forming difficulties, leading to cracking issues in both simulation and physical try-out.

[Initial simulation/try-out showing cracks]

Project Background

Key challenges addressed:

• High forming difficulty in regions far from material entrance
• Need to balance wrinkles and rupture through material storage
• Limitations of traditional manual modification approaches

Optimization Approach

1 Blank Shape Improvement

Optimized initial blank configuration

2 Design of Experiments (DOE)

[ParaCAD model of die face]

Parametric design of critical dimensions:

• Key heights H1 and H2
• Friction factor optimization
• Drawbead force adjustment

3 Optimal Working Window

Identified parameter ranges for quality production:

• Friction factor: 0.04 to 0.05
• H2: -55.0 to 30.0
• H1: -42 to -10
• Drawbead force: 0.01 to 0.05

[Variable influence proportion diagram]

Final Results

[Mass production results and thickness distribution]

Achieved crack-free production within optimized parameter windows

Key Success Factors

• CAD-driven parametric optimization
• Systematic DOE approach
• Precise identification of major/minor influencing factors
• Quantified safe operating windows