The problem of dimensional accuracy data analysis in automobile assembly operations is considered. The data are measured via Optical Coordinate Measuring Machines (OCMM's), and issues of multivariate modeling, analysis, reduction (sensor number and location determination) and quality control are addressed. The study is based upon a novel multivariate time series analysis framework that accounts for both spatial cross correlation and serial autocorrelation. Its effectiveness is demonstrated via actual and simulated plant data.