This paper presents a methodology to develop multivariate loss functions to measure the operational loss of process facilities. The proposed methodology uses loss functions to provide a model for operational loss due to deviation of key process characteristics from their target values. Having estimated the marginal loss functions for each monitored process variable, copula functions are then used to link the univariate margins and develop the multivariate loss function. The maximum likelihood evaluation method is used to estimate the copula parameters. Akaike's information criterion (AIC) is then applied to rank the copula models and choose the best fitting copula. A simulation study is provided to demonstrate the efficiency of the copula estimation procedure. The flexibility of the proposed approach in using any form of the symmetrical and asymmetrical loss functions and the practical application of the methodology are illustrated using a separation column case study. (C) 2015 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.