METODOLOGÍA DINÁMICA DE GESTIÓN MEDIANTE CONTROL ESTADÍSTICO DE RIESGOS APLICADO A LA REALIZACIÓN DE PROYECTOS DE ELEVADA INCERTIDUMBRE.

Abstract

Unexpected events or precursors in systems with high variability, can trigger sequences that generate failures, errors, incidents and accidents, with personal, material and environmental repercussions, in projects with high uncertainty, carried out in facilities and chemical process plants or production facilities of natural gas and oil, as well as in general in projects that have a high risk component. Quantitative methods perform risk assessment by associating them with activity and process, in specific scenarios; but one disadvantage of this treatment is not to update the risk situation according to the evolution and execution of the project in order to anticipate and avoid it. Dynamic methods of risk assessment take advantage of obtaining information on events and data generated during execution, in order to update the probabilities of error, using, as tools, the Bayesian inference and Monte Carlo - Markov methods. This work proposes a model to carry out the project management based on this methodology and through the application of Statistical Risk Control (SRC) in order to visualize its evolution associated with each process and to be able to act accordingly.