Making decisions and managing competences in complex systems is a challenging task to accomplish. Specifically, the process industry is known for its complexity and sensitivity to critical procedures. Recent disasters like the ‘‘Deepwater Horizon” (2010, 11 fatalities), BP Texas City (2005, 15 fatalities), and AZF Toulouse (2001, 29 fatalities), clearly showed the risk to which we are all exposed. The increasing complexity of processes, due to the simultaneous escalation of automation, optimisation and intensification processes (followed to face globalisation challenges), are moving the attention to the management of abnormal situations, which are even more complex in nature and frequent. This increasing complexity, coupled with the fact that abnormal situations may lead to irreversible losses, is imposing the adoption of adequate approaches and tools that allow for better learning and properly managing abnormal situations. The paper presents a simulation-enabled, experiment-based approach that can be used to prevent and manage risk through competencies management. More specifically, the paper presents the results of the first experiment campaign performed in a Plant Simulator (PS), the first known in the process industry domain, and shows the efficacy of using Immersive Virtual Environments (IVE) both to make decisions and to train teams (not just single operators). The experiment results presented in the paper show the effectiveness of IVE to increase the competencies and train operators and managers. In addition, they explain how conveniently the data collected by means of the PS can be used for making daily decisions to better prevent and manage risks.
|Data di pubblicazione:||2016|
|Titolo:||The Plant Simulator as viable means to prevent and manage risk through competencies management: Experiment results|
|Autori:||Luigi, Golzio; Simone, Colombo|
|Digital Object Identifier (DOI):||10.1016/j.ssci.2015.11.021|
|Appare nelle tipologie:||Articolo su rivista|
I documenti presenti in Iris Unimore sono rilasciati con licenza Creative Commons Attribuzione - Non commerciale - Non opere derivate 3.0 Italia, salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris