Develop a data-driven approach under the integration of 4D visualization and process mining to simulate, diagnose and predict real-world construction execution

Abstract

In a dynamic shift toward the digitalization of the construction industry, this research heralds a novel data-centric methodology that merges the innovative realms of 4D simulation with process mining to enhance, predict, and analyze the execution phases of construction projects. This pioneering study stands at the forefront of construction project management, offering a sophisticated tool designed to streamline project execution by enabling managers to simulate project workflows, identify potential pitfalls, and foresee critical project parameters including timelines, resource distribution, and potential risks. At its core, the methodology integrates a time-enriched 3D model with the meticulous analysis of project management data through advanced data mining techniques. This approach not only aims to refine the prediction and management of construction risks but also to optimize project execution, thereby elevating the efficiency and output of construction endeavors. The research is structured to unfold in meticulously planned stages, focusing on the synthesis of 4D models with data mining processes, the crafting of predictive algorithms, and their validation in real-world settings. Through this strategic timeline, the research aspires to validate each component of the proposed method, ensuring its efficacy and applicability in the broader construction sector. Furthermore, by bridging the gap between temporal simulation and process analysis, this study is poised to contribute valuable insights and open new avenues for innovation within both the academic sphere and the construction industry at large.