Automation and information approaches to support maintenance and production management in the construction industry

The construction industry is a wide industrial sector ranging from the design and management of major infrastructures, such as bridges, to civil dwelling construc- tion. It is worldwide acknowledged as a fundamental driving sector for the Gross Domestic Product, but it is also among the less performing and delayed ones in the adoption and exploitation of technological improvements. These limitations are inducing stakeholders to borrow and integrate many enhancements from other indus- trial fields into the sector. This digitalization trend is spreading through the entire life cycle of the construction process and identifying a challenging approach because of the paradigm shift needed from physical to cyber-physical systems. The Industry 4.0 concept boosted this trend so that both in the academy and in the construction industry it has been specified as Construction 4.0. It borrows from the Industry 4.0 the adoption of many key enabling technologies such as Internet of Things, Artificial Intelligence and Additive Manufacturing. This thesis investigates specifically this technological integration, focusing on the application of such enabling technologies in the construction field and considering different stages in the life cycle in vary- ing infrastructure typologies. Starting from a literature investigation on "holistic" intelligent systems in Intelligent Buildings construction, in a Digital Twin fashion, the influence and the application of enabling technologies and related operative ICT tools such as Internet of Things and Big Data are studied, from a perspective of the whole constructions’ life cycle. The maintenance phase of major infrastruc- tures is studied concerning structural safety and fault detection, by developing a method to detect damages in railway steel truss bridges via artificial intelligence. An innovative additive manufacturing technology for high-rise constructions is then presented. It consists of an improvement with a custom extruder of standard tower crane technology, while the whole system is driven by an artificial intelligence agent. We conclude that Construction 4.0 is still at its embryonic stage. More advanced results are obtainable for the operation and maintenance management of existing infrastructures because of the already mature approach related to sensorization and data analysis. Innovation in the design/construction phase remains more challenging, because of the need for a completely new paradigm and industrial innovations in many different fields.