Lotte Construction is moving to strengthen on-site competitiveness by overhauling its quality control system that covers the entire construction process from design to execution and completion. The plan is to shift the quality control paradigm from a focus on "post-response" management to a "prevention-first" approach that resets standards for every step and runs them on a digital and artificial intelligence (AI) basis.
To that end, Lotte Construction recently created a companywide "defect reduction TFT." The TFT includes core organizations such as the CS institutional sector, the building construction institutional sector, the mechanical and electrical institutional sector, and the Technology Research Institute, and performs tasks centered on "reestablishing the basics" and "data-based management" so that the same standards apply across all stages of design–construction–completion and quality remains consistent across sites. Lotte Construction first revamped its technical standards based on the standard specifications. To make them easy to apply in the field, it supplemented the bidding and site briefing standards and specified detailed guidelines at a practical level so that consistent standards are applied from design through construction and quality inspections.
AI-based quality control technology will also be introduced in earnest. AI will analyze on-site inspection data collected via mobile and web to identify the likelihood of major quality issues in advance. As data that were previously managed individually are accumulated in one place, it has become possible to automatically predict risk factors by site and recurring defects. The inspection method is also standardized based on an "integrated checklist," which is expected to increase the reliability of inspection results and greatly reduce quality gaps between sites. All results are shared with those in charge in real time, leading to immediate action.
Management processes for the completion stage and beyond will also be further reinforced. Lotte Construction is building a system that integrates management of construction history and quality data. In particular, it introduced a virtuous-cycle "feedback loop" in which AI analyzes data generated throughout the process and feeds the results back into the technical standards, ensuring continuous quality improvement.
A Lotte Construction official said, "The core of this quality control overhaul is not just beefing up inspections but establishing standards that actually work in the field and operating them precisely with data and AI," adding, "We are focused on the fact that strengthening the basics ultimately leads to the best quality."
Going forward, Lotte Construction plans to roll out, step by step, technical standard updates, integrated quality inspection operations, advanced AI-based analysis, and a completion documentation management system. It also intends to keep developing a field-centered quality control system by operating an on-site quality experience center and strengthening "hands-on practical training" for staff and assistant managers.