In the bustling world of building management, where maintenance schedules can often feel like a game of whack-a-mole, a new research breakthrough is promising to bring some much-needed order. Edoardo De Santis, a researcher from the DICEA Department at Sapienza University of Rome, has developed a novel framework that optimizes scheduled maintenance on operational buildings, potentially saving businesses significant time and money.
De Santis’s research, published in the Journal of Civil Engineering and Management (which translates to “Civil Engineering and Management” in English), focuses on the often-overlooked but critical aspect of building management: operation and maintenance (O&M). “Maintenance is not just about fixing things when they break,” De Santis explains. “It’s about preserving the quality of the building throughout its life, keeping costs within acceptable limits, and minimizing disruptions to daily operations.”
The challenge lies in the sheer variety of maintenance tasks, each with its own optimal frequency, cost, and duration. From replacing air conditioning filters to restoring structural elements, these tasks can disrupt building operations if not managed efficiently. De Santis’s solution? Grouping tasks within reasonably close time frames to schedule preventive maintenance plans while respecting their frequency.
The optimisation model developed by De Santis is a game-changer. It identifies the best time range for grouping O&M tasks, ensuring that tasks are performed at the most cost-effective time. By penalising deviations from the optimal period, the model minimizes disruptions and maximizes efficiency. “This is not just about scheduling tasks,” De Santis says. “It’s about creating a system that learns and adapts, ensuring that maintenance is carried out in the most efficient way possible.”
The framework is integrated within a microservice-based architecture, seamlessly linking an input database and a Building Information Model (BIM), orchestrated using Dynamo for Revit. This integration allows for a more holistic approach to building management, where data and models work together to optimize maintenance schedules.
The commercial impacts of this research are significant, particularly for the energy sector. Buildings are responsible for a substantial portion of global energy consumption, and inefficient maintenance can lead to increased energy usage and higher costs. By optimizing maintenance schedules, De Santis’s framework can help reduce energy consumption, lower costs, and minimize disruptions, making it a valuable tool for building managers and energy providers alike.
The research also has broader implications for the future of building management. As De Santis notes, “This is just the beginning. The integration of optimisation techniques and BIM tools opens up new possibilities for efficient O&M management. We are moving towards a future where buildings are not just structures, but intelligent systems that learn and adapt to their environment.”
In the end, De Santis’s research is a testament to the power of innovation in solving real-world problems. By bringing order to the chaos of building maintenance, he is paving the way for a more efficient, cost-effective, and sustainable future. And for building managers and energy providers, that future can’t come soon enough.