The ability to use a simulation program with the aim to make a general balance on a plant, starting just from raw data and process knowledge, is an ambitious and attractive goal, In this context, we will propose a general formulation for the estimation problem in the framework of the simultaneous modular simulator. As raw data are corrected to satisfy mass and energy balances and some parameters are computed to give a diagnostic on the performance of unit operations, the estimation consists both in data reconciliation and in parameter identification. It follows that the numerical problem is a minimization of a Least Square objective function. Constraint minimization is performed with an infeasible path strategy which solves the optimization problem and the process convergence at the same level, with a NonLinear Programming code. The confidence intervals computation, on parameters and on corrected values of measurements, is also discussed. A flash loop flowsheet has been chosen as an illustrative simple example which gives a better understanding of the theoretical aspects.