PROJECT MANAGEMENT BASICS FOR 3D CONCRETE PRINTING: TIME CALCULATION STANDARDS FOR DESIGN AND TECHNOLOGICAL PREPARATION AND QUALITY ASSURANCE

Abstract

This research establishes the first comprehensive project management framework for 3DCP through quantitative standards for design preparation, technological setup, and quality management. Based on systematic analysis of construction projects completed during 2023-2025 by "Geopolimer" LTD (Kharkiv, Ukraine), we developed mathematical models for time estimation incorporating perimeter length, geometric complexity, and feature count parameters. Regression analysis of project data enabled formulation of predictive equations: design preparation time accounts for base setup, perimeter-dependent modeling, and complexity coefficients (complex curved surfaces with architectural details). Technological preparation time integrates G-code generation, trajectory verification per meter, and build step validation. A systematic complexity classification system evaluates four geometric factors: curved surfaces percentage, architectural detail count, protruding elements, and internal cavity complexity, enabling quantitative risk assessment and resource allocation decisions. The framework incorporates a three-level quality management system with standardized defect classification (aesthetic, attention-required, critical) defining acceptance criteria for crack dimensions, surface porosity, and structural integrity. Trajectory verification methodology enables proactive defect identification, detecting 85-90% of potential issues before production begins. Economic analysis demonstrates 8-12% rework cost avoidance, 15‒20% preparation time savings, and 5‒10% schedule compression, with return on investment achieved within 0.5‒1.5 months. Case study validation on a 174 m² residential structure demonstrates framework effectiveness: calculated preparation time of 45.1 hours versus actual 47.2 hours. The framework facilitates 3DCP transition from experimental technology to predictable industrial process, enabling evidence-based project planning, systematic risk management, and competitive market positioning. Future research directions include expansion to additional printer types, integration with Building Information Modeling workflows, real-time computer vision quality monitoring, and long-term performance tracking for continuous standard refinement.