Smart Building Use Case: Smart Facility Management
The digital twin paradigm is coming to the forefront of Smart Facilities Management in order to reduce costs and increase efficiencies, to reduce time spent with outages and component failures and to reduce overall greenhouse gas emissions. Complex simulations help Facilities Managers model and predict outcomes and effects certain stimuli will have on the facility. This process can start at the construction phase and continue right through the usage stage to the refurbishment stage. For example, intelligent digital twins allow SF Managers to analyse the building’s dynamic response to changes in occupation, weather, energy consumption, asset and space usage (including not only the needs from office complex, but also from dynamic manufacturing cells for Industry 4.0, with challenging, dynamic, and ever-changing interactions among robots, devices and operators). The business information model value chain ranges from basic analysis, preliminary and design planning to construction and operations. Ideally, the digital twin should be synchronized with the real business status, readjusting the properties of the simulated environment and the parameters of the digital assets to overcome performance gaps. By bringing together different aspects of digital twin applied to facility management: devices in building, structural components (static data as floor plans, assets, devices, machines…) and dynamic data (performance data, time series data, crowd/person behaviours…) and applying V&V and continuous integration techniques together with Machine Learning, the gap between real and digital environments will be reduced, and the different phases: Product design, Construction and Performance will be supported by credible digital twins. For this, key players and interested parties will be taken into account, and a real facility will be used as reference for the demonstrator. As an outcome of this, the UPSIM framework, with CI, ML and V&V capabilities for Digital Twin will be demonstrated for the facility domain (generating a copy of a physical facility, including a 3D model combined with dynamic data to allow easy-to-understand visualization and analysis), focusing in predictive maintenance and cost reductions. Through the application of predictive maintenance algorithms, smart simulations can indicate the need for building maintenance or upgrades based on the actual usage patterns of the building and model -trough what-if scenarios implemented in the digital twins- how best to implement those changes in real life to ensure minimal costs and disruptions. From predicting the real-time effects of complex HVAC system changes to allowing for remote diagnostics (without the need for costly and disruptive on-site visits), more intelligent simulation techniques can speed up facility management and reduce costs and harmful emissions in the process.