Skip to Main content Skip to Navigation
Journal articles

An extended framework for knowledge modelling and reuse in reverse engineering projects

Abstract : Reverse engineering is when a real part is analysed in detail in order to create a numerical or virtual model. Reverse engineering allows for multiple redesign possibilities, including changes in the material, the shape and the parameters of the part. Reverse engineering is mostly a manual activity for companies and is thus time consuming. Indeed, measurements must be done in scanned files in order to fit sketches on a mesh and to finally rebuild the computer-aided design/bill of material. This manual process is acceptable when reverse engineering is exceptional. But it is considered as a non-value task when reverse engineering is routine. This non-value task could be automated, at least partially. To make it possible, a capitalization of the company’s part catalogue is a necessary step to proceed. The use of this capitalization can then drive the reverse engineering tasks to enable faster redesign possibilities. The aim of this contribution is thus to propose a knowledge model to support reverse engineering activities in order to integrate the reversed parts quickly into the new product’s detailed design. An extended knowledge framework based on the core product model is proposed, and a use case is shown to validate the feasibility of the proposal of the reverse engineering methodology called PHENIX
Document type :
Journal articles
Complete list of metadata
Contributor : Farouk Belkadi <>
Submitted on : Tuesday, February 26, 2019 - 6:16:45 PM
Last modification on : Tuesday, January 5, 2021 - 4:26:08 PM



Alexandre Durupt, Matthieu Bricogne, Sébastien Remy, Nadège Troussier, Harvey Rowson, et al.. An extended framework for knowledge modelling and reuse in reverse engineering projects. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, SAGE Publications, 2018, pp.095440541878997. ⟨10.1177/0954405418789973⟩. ⟨hal-02050035⟩



Record views