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