Author:
Shah Ghazanfar Ali,Polette Arnaud,Pernot Jean-Philippe,Giannini Franca,Monti Marina
Abstract
AbstractThis paper addresses the way a simulated annealing-based fitting strategy can be enhanced by leveraging a sensitivity analysis able to characterize the impact of the variations in the parameters of a CAD model on the evolution of the deviation between the CAD model itself and the point cloud of the digitized part to be fitted. The principles underpinning the adopted fitting algorithm are briefly recalled. The applied sensitivity analysis is described together with the comparison of the resulting sensitivity evolution curves with the changes in the CAD model parameters imposed by the simulated annealing algorithm. This analysis suggests several possible improvements that are discussed. The overall approach is illustrated on the fitting of single mechanical parts but it can be directly extended to the fitting of parts’ assemblies. It is particularly interesting in the context of the Industry 4.0 to update digital twins of physical products and systems.
Publisher
Springer International Publishing
Reference10 articles.
1. Lu, Y.: Industry 4.0: a survey on technologies, applications and open research issues. J. Ind. Inf. Integr. 6, 1–10 (2017)
2. Falcidieno, B., Giannini, F., Léon, J.-C., Pernot, J.-P.: Processing free form objects within a product development process framework. In: Advances in Computers and Information in Engineering Research, pp. 317–344 (2014)
3. Shah, G.A., Polette, A., Pernot, J.-P., Giannini, F., Monti, M.: Simulated annealing-based fitting of CAD models to point clouds of mechanical parts’ assemblies. To appear in Engineer with Computers (2020). https://doi.org/10.1007/s00366-020-00970-8
4. Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P.: Optimization by simulated annealing. IBM Research Report RC 9355, Acts of PTRC Summer Annual Meeting (1982)
5. Iooss, B., Lematre, P.: A review on global sensitivity analysis methods. In: Uncertainty Management in Simulation-Optimization of Complex Systems, pp. 101–122. Springer (2015)