Integrated Digital Twin Framework for Adaptive Production Planning and Control in Precast Construction

EasyChair Preprint 15176

Abstract

Precast construction faces challenges that arise from differing priorities in terms of production optimization between the production and the erection functions. Factories prefer large production batches, which does not align with the needs of erection crews for sets of varied pieces at each step in erecting a building. We propose a Digital Twin Construction framework for closed-loop monitoring and control of precast concrete production and construction. A core module in the framework performs adaptive global optimization of the system. The optimization module compiles sets of production plan parameters using planning heuristics, evaluates the plans using agent-based simulations, and then optimizes for plan parameters using a genetic algorithm. A novel utility function works to minimize production waste throughout the system, rather than seeking shortest project duration. The result has minimum cost with greatest value. Once implemented, the framework as a whole may enable automated monitoring and control in a closed loop that optimizes production plans to enhance efficiency, reduce waste, and improve coordination, ultimately streamlining the entire precast construction process.

Keyphrases: Digital Twin Construction, Lean, Optimization, Precast Construction, Production Planning and Control, adaptive production planning and control, precast concrete, project status information

@booklet{EasyChair:15176,
  author    = {Timson Yeung and Huaquan Ying and Jiyuan Li and Rafael Sacks},
  title     = {Integrated Digital Twin Framework for Adaptive Production Planning and Control in Precast Construction},
  howpublished = {EasyChair Preprint 15176},
  year      = {EasyChair, 2024}}