This paper deals with an application of partial least squares (PLS) methods to an industrial terephthalic acid (TPA) manufacturing process to identify and remove the major causes of variability in the product quality. Multivariate statistical analyses were performed to find the major causes of variability in the product quality, using the PLS models built from historical data measured on the process and quality variables. It was found from the PLS analyses that the variations in the catalyst concentrations and the process throughput significantly affect the product quality, and that the quality variations are propagated from the oxidation unit to the digestion units of the TPA process. A simulation-based approach was addressed to roughly estimate the effects of eliminating the major causes on the product quality using the PLS models. Based on the results that considerable amounts of the variations in the product quality could be reduced, we have proposed practical approaches for removing the major causes of product quality variations in the TPA manufacturing process.