AutoForm plus r4-Incrementalplus Rapid and Accurate Simulation and Validation of the Complete Stamping Process AutoForm-ThermoSolver AutoForm-ThermoSolver Efficient Simulation of Hot Forming and Quenching Processes AutoForm-DieDesigner AutoForm-DieDesigner 3D-Die-Layout and Process Optimization AutoForm-Sigma AutoForm-Sigma Sensitivity Analysis, Optimization and Robustness AutoForm-Compensator AutoForm-Compensator Geometry Compensation of Part and Tool Based on Springback Results AutoForm-Trim AutoForm-Trim Automatic Determination of Optimum Trim Line and Blank Outline AutoForm-ProcessPlanner AutoForm-ProcessPlanner Effective Process Planning AutoForm-CostCalculator AutoForm-CostCalculator
Rapid Production Sequence Definition with Sophisticated Tool Cost Calculation AutoForm-BlankDesigner AutoForm-BlankDesigner Rapid Design of Cost-Optimized Blanks AutoForm-Nest AutoForm-Nest Cost-Optimized Nesting of Blanks AutoForm-OneStep AutoForm-OneStep Engineering Manufacturable Sheet Metal Parts AutoForm-PartDesigner AutoForm-PartDesigner Easy and Rapid Part Modifications AutoForm-DieAdviser AutoForm-DieAdviser Optimal Wear Protection AutoForm Hydroforming AutoForm Hydroforming Rapid Analysis and Simulation of Entire Hydroforming Design Chain AutoForm-DataManager AutoForm-DataManager Efficient Management of AutoForm Data AutoForm-ReportManager AutoForm-ReportManager Creating Presentation Reports of AutoForm Results AutoForm-HemPlanner AutoForm-HemPlanner Efficient Planning of Hemming Processes AutoForm-ProcessDesigner^forCATIA AutoForm-ProcessDesignerforCATIA Rapid Creation of CAD Quality Die Faces AutoForm-OneStep^forCATIA AutoForm-OneStepforCATIA OneStep Feasibility Assessment inside CATIA AutoForm-CATIA5 AutoForm-CATIA5 Direct Integration of AutoForm Software in CATIA V5 AutoForm-NX AutoForm plus r4 p-NX Direct Integration of AutoForm Software in NX EasyBlank Inventor EasyBlank Inventor Analysis of Stamped Parts Embedded within Autodesk® Inventor® Software EasyBlank EasyBlank MatForm MatForm AutoForm-Sigma® Software for Sensitivity Analysis, Optimization and Robustness The AutoForm-Sigma software module is specialized for analyzing and improving the robustness of sheet metal products and processes. It serves to improve and validate the forming process, and to reduce or eliminate part rejects. With AutoForm-Sigma, products and processes can be designed so that the resulting manufacturing process is most efficient and stable while meeting desired quality targets. The influence and sensitivity of design parameters are easily analyzed which leads to improved process know-how and shorter development times. In addition, statistical process control techniques can already be applied in the design phase, taking into account the noise and variability that are inherent in the forming process. Therefore, sheet metal formers can address and solve key manufacturing problems much before going into production, with obvious advantages. AutoForm-Sigma provides the following benefits: Shorter development and tryout times - because the forming process becomes more transparent and process know-how is improved More stable manufacturing processes during the entire production cycle - through identification of the process window Less plant downtime, fewer tool adjustments and fewer part defects - because of more robust manufacturing processes More robust manufacturing processes - through quality and process capability analyses AutoForm-Sigma is fully integrated into the AutoForm work environment. Unique on the market, it automatically analyzes and displays the results (e.g. influence, sensitivity, process capability Cpk) directly on the parts – no time consuming investigations of abstract numbers and diagrams are needed any more. No other software offers this new methodology which can be used by die face designers and engineers, without requiring years of specialized expertise. AutoForm-Sigma’s main features include: Easy definition of design parameters Automatic start of multiple simulations Statistical techniques pre-defined and ready for user application Identification of dominant design parameters Determination of influence and sensitivity of design parameters Automated process optimization Determination of noise and variability of process parameters Integration of Statistical Process Control (SPC) and simulation Identification of process window

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