Systematic Process Improvement enables engineers to systematically improve the forming process. As the result of the continuously increasing geometrical complexity of stamped parts as well as the numerous applications of high-strength steels, sheet metal forming process is becoming more and more complex. Furthermore, the highly competitive market situation creates a great demand for the delivery of high quality stamped parts with an ever decreasing lead time.
It is important to identify which design parameters influence part quality and to what extent.
Systematic Process Improvement brings transparency to the forming process by showing which design parameters influence part quality and to what extent. Design parameters are those input parameters which can be adapted in part, tool and process design such as part radii, binder surface geometry, addendum geometry, use and position of drawbeads, blankholder force, lubrication, etc.
In Systematic Process Improvement, multiple stamping simulations are carried out automatically. During these simulations, design parameters are varied while engineers maintain their focus on the quality targets set for the stamped part. The quality target can be specified with regard to one or more output variables from the simulation, e.g. no wrinkles, no splits or sufficient stretching. In this way, design parameters which have the most influence on the stamped part can be identified already during the tool and process design stage, enabling engineers to make necessary adjustments, which thereby contribute to the systematic improvement of the forming process. The best selected set of design variable values results in the most feasible process. Through the better understanding of the forming process, shorter development times are achieved. As a result, engineers can address and solve key manufacturing problems before going into production by implementing Systematic Process Improvement.
Further information on Systematic Process Improvement at AutoForm:
Making its Mark
Systematic Process Improvement with Noise
Software for Sensitivity Analysis, Optimization and Robustness
AutoForm Training for Robust Process Improvement
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