Dimensional management in metal assembly process validation: A multivariate approach

Managing dimensional issues in the sheet metal assembly process during the initial stages of the production launch involve a series of complex decisions. This dissertation provides a series of methodologies that address the multivariability of components and assemblies and their relationship.; In the first paper, a statistical process control methodology for the stamping process is presented. The methodology uses a combination of Hotelling T2 multivariate charts and Individual/Moving Range univariate charts. The multivariate charts are used to monitor the stability of groups of checkpoints simultaneously and to identify those particular ones that have a critical contribution to out of control signals. The Individual charts are then used to follow up and monitor those critical checkpoints more closely.; The second paper, addresses the issue of modeling the relationships between stamping components and their subsequent assemblies using a slow build approach to plan and carry out dimensional studies. The proposed data analysis methodology is based on the partial least squares regression methodology to identify significant characteristics in a highly collinear and multivariate setting with a relatively small number of parts.; A methodology for tolerance revision and adjustments is presented in the third paper. This is a very important outcome of the process validation in which the process variation is estimated using a limited number of die sets and parts. The power of the methodology is compared to that of other common practices.