Contribution to the estimation of uncertainties in assembly operations assisted by 3D metrology

Abstract

Jig -based assembly is a method widely used in the automotive and aerospace industries. Among its advantages, its robustness and its metrological performance (good repeatability) can be mentioned. In addition, even non-specialists can use it; the components are immobilized using stops before finalizing the assembly. Finally, quality is guaranteed through certification of the fixture used. On the other hand, the disadvantages are numerous. In addition to the significant cost of manufacturing and calibrating these jig, they are intended for a specific use; as soon as there is a modification or an alteration of the model or the components, costly modifications must be carried out. For approximately two decades, the development of 3D measurement systems has been impressive. Today, we have access to technologies that allow the simultaneous tracking of a set of targets (>30) within the workspace (up to 100×100 m) with good accuracy (<0.5 mm @ 95%). The principle of jigless assembly (Jigless Assembly) exploits the capabilities of 3D measurement equipment (e.g., iGPS, laser tracker…) to position and orient components according to the required specifications. The idea is therefore to propose a new assembly method, referred to as “Metrology-Assisted Assembly” (MAA), which is intended as an alternative to jig-based assembly. MAA will offer very good flexibility, which can translate into productivity gains. However, for industrial deployment, it is necessary to resolve a technological barrier, which is the quality assurance of the assembly that will be obtained by MAA. Indeed, it is necessary to estimate and document the uncertainty inherent to an assembly operation carried out using MAA. Thus, the main question is to develop an approach to quantify the uncertainty associated with the result obtained by MAA on a critical characteristic (KC)? The main objective of this thesis is the development of a general methodology to estimate the uncertainty of a metrology-assisted assembly operation using an iGPS system.

Date	12 Jan 2026
Original language	American English
Awarding Institution	École de technologie supérieure
Supervisor	Antoine Tahan (Supervisor), Louis Rivest (Co-supervisor) & Sasan Sattarpanah Karganroudi (Co-supervisor)