Leveraging Digital Twins to enhance Green Public Procurement in AECO industry

The digital transition of process management and Digital Twins (DTs) are promising to bridge the gap towards Product Lifecycle Management (PLM) and revolutionize decision-making processes in AECO (Architectural, Engineering, Construction and Operation) industry. Public procurement particularly suffers of poor digitalization with ineffective processes and low adoption of Green Public Procurement (GPP) mainly due to the lack of digital and automated data-driven tools for tender evaluation. Leveraging DTs as virtual Prototypes (DTPs) could help to overcome the current discrete project performances evaluation and enable a systemic one, exploitable for bids evaluation besides performance and sustainability optimization. The research adopts a PLM view to define a methodology aimed at developing DTPs starting from the bidding BIM models. The main objective is to integrate several DTPs and an Artificial Intelligence (AI) system in the aim automatizing MEAT (Most Economic Advantageous Tender) procedure and promote GPP adoption, providing an optimal and more objective datadriven awarding system and criteria weighting. Three crucial objectives should be accomplished: (i) the definition of a replicable methodology to develop the DTPs, (ii) the definition of their informative structure and (iii) the re-engineering of tender processes to bring full digitalization and automation. This could enable more effective decisions and performance optimization, bids objective evaluation, tendering procedure streamlining, transparency and sustainability enhancement. The awarded DTP, as a truthful “As-built” developed accordingly to defined information guidelines, must be exploited as the basis for valuable DTIs to manage the whole lifecycle, optimizing DTs development costs together with operational and maintenance costs.