Lotte Construction Shifts Quality Control to Prevention-First Model Using AI
Lotte Construction is overhauling its quality control system to catch defects before they occur rather than respond after the fact. The company created a companywide task force to standardize processes across design, construction, and completion stages using data and artificial intelligence.
The shift moves away from reactive inspections toward a prevention-first approach. A defect reduction task force now includes the customer service, building construction, mechanical and electrical divisions, and the Technology Research Institute. The team is reestablishing baseline standards and implementing data-driven management across all sites.
Standardizing Technical Specifications
Lotte Construction first revised its technical standards to make them practical for field application. The company added detailed guidelines to bidding documents and site briefings so the same standards apply from design through final inspection.
An integrated checklist now standardizes how inspections are conducted. This reduces variability between sites and increases the reliability of inspection results.
AI Analysis Identifies Risk Patterns
AI systems will analyze inspection data collected through mobile and web platforms to predict major quality issues before they develop. As data previously managed separately flows into one system, the AI can automatically flag risk factors by site and identify recurring defects.
Inspection results are shared with responsible staff in real time, enabling immediate corrective action. The system eliminates gaps in quality standards between different construction sites.
Continuous Improvement Through Feedback Loops
Lotte Construction is building a system that integrates construction history and quality data. An AI-powered feedback loop analyzes data generated throughout the construction process and feeds findings back into technical standards, creating a cycle of continuous improvement.
The company plans to roll out technical standard updates, integrated quality inspection operations, advanced AI analysis, and a completion documentation management system in phases. It will also operate an on-site quality experience center and expand hands-on training for staff and assistant managers.
A company official said the core of the overhaul is not simply increasing inspections but establishing standards that work in the field and operating them precisely with data and AI. "Strengthening the basics ultimately leads to the best quality," the official said.
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