Dony Susandi
Industrial Engineering Department, Universitas Majalengka, Majalengka, Indonesia

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Journal : international journal of advanced science computing and engineering

Enhancing Material Quality Control in Construction: A Data-Driven Approach Using PDCA and DMAIC Dony Susandi; Lia Milana; Dinda Ulzanah Nurislamiyati
International Journal of Advanced Science Computing and Engineering Vol. 8 No. 2 (2026)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.8.2.300

Abstract

Quality control is a critical aspect of construction projects, ensuring that materials and implementation align with established standards. This study focuses on the quality control of ready-mix concrete used in the capping beam lining works of the Cipelang Irrigation Modernization Project. Initial observations indicated that some concrete materials did not meet the required compressive strength, potentially compromising structural integrity and durability. To address these concerns, the study applied PDCA and DMAIC methodologies to systematically monitor and enhance material quality. Compressive strength tests were performed in accordance with ASTM C39 and BS EN 12390-3 standards, covering specimen preparation, curing, and testing procedures. Additionally, Statistical Process Control (SPC) techniques, including control charts, were utilized to identify variations in mix composition and implement necessary corrective actions. A deeper analysis using Failure Mode and Effect Analysis (FMEA) revealed that quality issues stemmed from three primary factors: human resources, materials, and methodologies. Through corrective measures, the study achieved significant improvements in concrete quality. The hammer test results showed an increase of 42 kg/cm² (~26.25%), while the compressive strength test results improved by 68.17 kg/cm² (~40%). These enhancements reduced material defects, minimized rework, and ensured adherence to project quality requirements. By adopting a structured, systematic approach, this study presents a scalable quality control framework applicable to similar construction projects. The findings contribute to safer, high-quality, and sustainable infrastructure by optimizing material performance and reducing quality inconsistencies.