A Model to Predict the Construction Schedule of High-rise Building Projects Using Minimal Project Information

Construction involves the design and assembly of immovable, site-specific structures, often delivered through temporary teams. The construction industry faces ongoing pressure to provide cost-effective, sustainable solutions. Many construction projects experience significant delays due to prediction errors at the initial phases of the project, and case-based reasoning (CBR) could offer an effective method for estimating and predicting accurate construction schedule to reduce delays. While CBR has been used to forecasting construction delays, research on applying it to construction schedules is limited. This study focuses on developing a CBR-based methodology to predict construction schedule in residential high-rise construction, using equal weighting across various attributes (a "feature counting" approach). The predicted schedules are compared to observed data to assess model accuracy and reliability. A framework for continuously capturing and applying lessons learned can help future projects better anticipate and control project schedules. Though the overall prediction accuracy is not exceptionally high, the models demonstrate improved reliability with larger case databases. Further research is still needed to refine and address practical implementation challenges.