• acqua
• gestione
• ottimizzazione
• metodologia
• database
• indicatori

This thesis work is the result of a six-month stage experience in Paris in the "SWaG" (Smart Water Grid) research project, in collaboration between Ecole de Management Léonard de Vinci and Altran Research. Altran is a global innovation and engineering consulting firm operating in high technology and innovation consulting. The Altran Research department is composed of multisciplinary teams with the aim of building solutions to complex issues posed by ever-changing world.
The SwaG Project is part of the "Smart Factory" research and innovation program with the goal of creating tools to improve water management in industry. In order to incorporate in the future the use of smart technologies in water management, this work lays the foundation for the creation of a set of decision support tools for the evaluation and optimization of water use in industry, and for the best scenario choice when variations in processes technologies are conducted.
To do that, this work proposes a framework through which classify processes belonging to different domains into defined blocks, a database of performance indicators (KPIs) to control each part of the industry and a methodology with defined steps to address a new case study and to obtain information about how optimize each process using KPIs.