Design optimization


Complex dynamics of global markets force companies to adopt new ways in order to increase competitiveness. The multidisciplinary approach has proven to be crucial in developing more competitive and successful products. The designer simultaneously is obliged to consider multiple perspectives in order to determine the optimal solution when tackling extremely complex issues. Engineers are required to achieve the right compromise in terms of product features to optimize the product performance, manufacturing cost and manufacturing lead-time. This optimization process is often manual and does not allow a comprehensive understanding of what the main problem is, leading to the choice of solutions that are potentially suboptimal. Furthermore, objective functions often cannot be expressed through the use of simple algebraic relations which require the use of specific software for their evaluation. Moreover, a step-by- step approach to identify the right combination of design criteria is a time and cost consuming process. Therefore, the automation of the optimization process, based on the integration of CAD, CAE and Design for Cost (DfC) software, is essential to increase the product quality and to facilitate and accelerate the identification of the best configuration.
In this context, the research activity aims to develop a methodology that allows, through the effective integration of different design and simulation tools, the product multi-objective optimization considering also manufacturing time and cost. The CAD system is the main actor of this process since it is able to interconnect both the CAE software and the DfC software for the specific analysis. Moreover, thanks to the possibility of parameterizing the geometric model, it is possible to use an optimization tool that enables to vary design criteria in an automated way, allowing the analysis of numerous configurations and the identification of the optimal one, without any interaction with designers.


The activities are carried out in the Virtual Prototyping laboratory


  1. P. Cicconi, V. Castorani, M. Germani, M. Mandolini, and A. Vita, “A multi-objective sequential method for manufacturing cost and structural optimization of modular steel towers,” Engineering with Computers, Jan. 2019.
  2. P. Cicconi, D. Landi, and M. Germani, “An Ecodesign approach for the lightweight engineering of cast iron parts,” The International Journal of Advanced Manufacturing Technology, vol. 99, no. 9–12, pp. 2365–2388, Sep. 2018.
  3. P. Cicconi, R. Raffaeli, M. Marchionne, and M. Germani, “A model-based simulation approach to support the product configuration and optimization of gas turbine ducts,” Computer-Aided Design and Applications, vol. 15, no. 6, pp. 807–818, Apr. 2018.
  4. V. Castorani, P. Cicconi, M. Mandolini, A. Vita, and M. Germani, “A method for the cost optimization of industrial electrical routings,” Computer-Aided Design and Applications, vol. 15, no. 5, pp. 747–756, Mar. 2018.
  5. M. Nardelli, P. Cicconi, R. Raffaeli, and M. Germani, “SUPPORTING DESIGN TASKS THROUGH CONSTRAINT SATISFACTION TOOLS,” Proceedings of the DESIGN 2018 15th International Design Conference, 2018.
Scientific Manager
Working group