Aller au menu Aller au contenu
Product-Process Design
Laboratory of Grenoble for sciences of conception, optimisation and production
Product-Process Design
Product-Process Design
< >

> GSCOP_Research > GSCOP_CPP

Identification and simulation of manufacturing defects


The research presents methodologies to identify and simulate manufacturing defects in three-dimension. The methodologies have been developed based on the previous works, such as the MMP (Model of Manufactured Part) simulation method presented by F. Villeneuve and F. Vignat, and the double measurement method is presented by S. Tichadou.In this thesis, the first proposed method based on the Small Displacement Torsor (SDT) concept is presented for identification of manufacturing defects. This method allows distinguishing the machining defects and positioning defects of a batch of parts during a process plan. The results obtained in this method represent geometric dimension errors of machined parts. In addition, we applied the parameterization method, which is usually used to analyze form defects of a part measured on a CMM with hundreds of measurement points, to complete the analysis of the form defects with a restricted number of measurement points (10 points on each machined surface). Even though this number appears to be low, the modes of the form defects are almost obtained (comber, undulation, twist, etc).Because of the important role of the positioning defect in the quality of a product during manufacturing, we then propose two simple indicators for evaluating the global quality of a fixture.Furthermore, we developed a model for simulating positioning defects of a workpiece fixed on a three-jaw chuck. The model is a combination of three methods: design of experiments, finite element simulation, and Monte Carlo simulation. Three factors, which are assumed to be the most important in positioning defects, are used in this model. Based on the simulated results, the influences of these factors are estimated. The results obtained from simulations can be expressed by form of distributions or statistical parameters. These allow using simulation of tolerance analysis based on Monte Carlo simulation.Finally, a model is developed based on MMP for tolerance analysis. This model allows us to verify a given process plan with functional tolerances of the machined part by determination of a number of machined parts out of tolerance zones or determine functional tolerances of a batch of machined parts based on a given process plan (without functional tolerances) and a number of rejected parts per million.

PhD Student: Minh hien BUI 
Grenoble University, 2008
Directors: François VILLENEUVE and Alain SERGENT (SYMME)
Partnership: SYMME Laboratory, Annecy

Link to the manuscript


Date of update February 26, 2015

Univ. Grenoble Alpes