An integrated BIM framework for schedule-aware construction waste management in building renovation projects

Abstract

Renovation projects generate volatile and activity-dependent construction waste flows, yet current modelling approaches remain predominantly static, relying on material-based coefficients detached from construction sequencing. Although Building Information Modelling (BIM)enhances quantity traceability, most applications fail to capture daily variability, peak formation and renovation-specific mechanisms such as packaging waste and demolition-related volumetric behaviour. This study addresses these limitations by developing an integrated BIM framework that embeds activity-level waste estimation within scheduling logic to support time-dependent operational planning. A schedule-aware BIM framework was developed and operationalised through the Circular Intelligent Waste Engine (CIWE). BIM-derived quantities were mapped to renovation activities, linked to productivity-based sequencing logic and integrated with waste intensities and demolition coefficients. The framework was applied to a multi-residential case study comprising three renovation strategies with increasing intervention depth. Waste performance was analysed at scenario, activity and temporal levels using cumulative, peak and labour-normalised indicators. Results indicate that operational waste burden is governed primarily by schedule compression and activity concurrency rather than renovation depth alone. The baseline scenario generated 50,664 dm3 of waste with a peak intensity of 377.7 dm3/day, whereas the deep renovation scenario reduced cumulative waste to 33,736 dm3 and peak intensity to 136.2 dm3/day. Distributed sequencing reduced daily volatility and stabilised logistics demand despite increased system complexity. Activity-level analysis further showed that envelope works dominate cumulative waste volume, while installation-intensive systems alter waste composition through packaging-driven flows. By embedding construction waste forecasting within production planning logic, the framework enables proactive peak identification, sequencing optimisation and improved logistics coordination, particularly in occupied and spatially constrained renovation projects. Unlike static BIM-based estimation approaches detached from construction sequencing, this study advances construction waste management by embedding waste forecasting within production planning logic. By reframing construction waste in renovation projects as a schedule-dependent management variable, the framework extends existing BIM-based approaches beyond static estimation.