Multivariate statistical process control is a branch of industrial statistics that involve monitoring quality specification of related variables simultaneously. Quality is the most essential target for manufacturing engineers and which mostly involves more than one variable in industry,i.e., a vector of variables (that conform to specification for measurement) which may be correlated. When these quality variables are correlated then the most well-known approach for multivariate process monitoring is the Hotelling’s T-square control chart. In this research, a multivariate data in sub-groups consisting of five quality characteristics obtained from Dana Steel Company Limitedkatsina is analyzed for quality. Retrospective analysis shows that, the production process from which the data were obtained is in statistical control.