BIM-Enabled Workflow Automation for Construction Productivity in Civil Engineering Projects: A Systematic Review of Applied Evidence

Abstract

Purpose: Construction projects still experience productivity losses caused by fragmented data, manual quantity processing, delayed progress reporting, and reactive quality control. This review evaluates how BIM-enabled workflow automation improves construction productivity compared with conventional construction

Methods/Design: A systematic literature review was conducted using a PRISMA-informed screening procedure. From 457 Scopus records, 36 studies were selected and synthesized thematically across pre-construction optimization, scheduling and progress monitoring, safety and quality assurance, and lifecycle-oriented digital integration.

Findings: The evidence indicates that BIM-enabled workflows improve productivity by automating quantity take-off, cost estimation, schedule visualization, progress tracking, defect detection, and operational feedback. Reported improvements include 33.33% manpower reduction in bar bending schedule preparation, 34.4% scheduling accuracy improvement, and progress detection accuracy of 89.1% in automated monitoring workflows.

Practical Implication: The review provides an applied evidence map for construction managers seeking to prioritize BIM automation investments while accounting for interoperability, model quality, and organizational readiness.