The sustainable refurbishment of abandoned industrial sites through smart adaptive reuse strategies. A Design Criteria System (DCS) for urban regeneration of marginal contexts.

The fragmented urban structure of contemporary metropolises caused by uncontrolled expansionist phenomena, and the economic and productive crisis of the last twenty years have led to social problems and the emergence of satellite districts physically separated by unused empty places. Many urban voids in the suburbs of modern cities concern disused and abandoned industrial sites. Therefore, there is a growing necessity to formulate innovative and sustainable strategies for urban regeneration, which provide, in the preliminary design phase, intuitive and schematic information and instructions to develop future smart green cities, facilitating stakeholders’ decisions. Adaptive reuse models contribute to achieve this purpose, transforming metropolis latent resources in new and comfortable liveable and attractive sites, satisfying current community needs. These interventions allow to promote feasible refurbishment actions, converting obsolete volumes in futuristic architectures with multiple functions in order to extend building useful life. In particular, the thesis focuses on the analysis and evaluation of functional and spatial transformation potentials of five historic and contemporary dismissed industrial factories in Bari periphery, through the structuring of a weighted radio-centric multicriteria model, the Design Criteria System (DCS), which contains all the features influencing adaptive reuse processes. The data extracted from each selected case study are catalogued and enclosed in a descriptive table. The application of Decision Support Systems facilitates the classification of functional reuse alternatives hypothesized for each industrial context, evaluating their effectiveness on the basis of independent parameters. The insertion of building cataloguing table input data into the DCS structure and the identification of cause-and-effect relationships between attributes activate a process of automatic selection and characterization of the adaptive reuse strategy, extrapolating the features involved in that specific conversion circumstance and measuring the intervention feasibility coefficient (f) and risk entity (r) through the sum of the components weights highlighted. The proposed model can assist stakeholder’s choices in complex decision-making contexts and represents a consistent and original tool to preliminary assess future possible regeneration scenarios, reducing urban sprawl phenomena and displaying with intuitive flowcharts feasible conversion policies and risks that could incur during planning, construction and maintenance activities.