Quantitative decision support methodologies in asset management

Company: SMI S.p.A.

Tutor: Giuditta Pezzotta e Fabiana Pirola

This doctoral project lies within the research strand of industrial asset management throughout the entire life cycle and, in particular, focuses on the development of methods and tools aimed at optimizing asset utilization and extending the life cycle of assets (e.g., through the provision of preventive and predictive maintenance services or optimizing operational efficiency to minimize resource demand during the utilization phase), increasingly taking advantage of the opportunities provided by digitization and remote connection of assets.

In this context, SMI Spa, a manufacturer of bottling plants and packaging machines, is embarking on its digitization journey by remotely connecting its machines in order to collect data during the utilization phase with the aim of providing a predictive maintenance service to its customers.

Thus, the goal of the project is to define quantitative methods, based on the data collected from the field, for decision support related to the management of SMI products throughout their lifecycle, with particular reference to the maintenance domain.

In parallel, the project involves defining methodologies for comparing both the economic and environmental impact of different solutions offered to customers.