Selected research project

The robust design & optimization of forming processes with bionic algorithms

University of Reutlingen

Iryna Kmitina2), Tatjana Popova2), Julian Litzkow1), Rolf Steinbuch2) , Ingo Neubauer1) , Ralph Bernhardt1), Gordon Huettig 3),

1) simufact  engineering

2) Reutlingen Research Institute, Hochschule Reutlingen

3) Tubex Rangendingen,


The optimization of processes/process chains in the sense of being robust, low scatter process designs, by the appropriate parameter combinations derived from simulations, is still a new field of application. The reason for this can be found in the nonlinear nature of the processes to be examined and the multitude of variables influencing them. In the field of metal forming processes, long and complicated simulations are often necessary. This is due to the many different singular steps that need to be simulated with their related component parameters, tool geometries, material properties and then the interactions of the components and tools. Furthermore, numerous local maxima can be observed.

With classical approaches, such as a full factorial DoE, a few process variables lead to a number of parameter combinations that are near impossible to handle and therefore, require an enormous computing effort. Furthermore, an optimal design (in respect to a given targeted value) is not necessarily robust against parameter variations.

To attain meaningful results within a reasonable computing time, it makes sense to employ bionic optimization procedures such as an evolutionary strategy or a particle swarm optimization. In a similar way to real populations, these strive to attain the optimum state while being able to leave local maxima.

Simufact is developing an overlay processor, based on the manufacturing of cans by extruding and deep drawing, which can compute a number of forming analyses and will suggest a number of improvements based on the given initial conditions, parameter ranges, and restrictions. Simufact is working in cooperation with the Reutlingen Research Institute (RRI) and Tubex within the framework of the ZiM project supported by AiF. The development of new production lines can then be realized in a much shorter time and with less waste. ZiM is the Central Innovation Program for Medium-sized Enterprises, AiF is the Working Group of Industrial Research Associations of Germany.

The task at hand and its solution will be illustrated with a few examples. The potential for future development will make simulations, as a means of optimization, a standard tool in can manufacturing.



With the project “Robuster Design Optimizer” (robust design optimizer), we are consistently and sustainably achieving our goal to further developments in the area of statistic-based process optimization.

Read the complete statement by Dr. Ralph Bernhardt.


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Dr. Ingo Neubauer

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Dr. Ingo Neubauer
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Phone: +49 (0)561 988 46 202

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