TY - GEN

T1 - Application of hybrid machine learning based quality control in daily site management

AU - Zöhrer, Alexander

AU - Winter, Vincent

AU - Terbuch, Anika

AU - O'Leary, Paul

AU - Khalilimotlaghkasmaei, Negin

PY - 2023/10/9

Y1 - 2023/10/9

N2 - This paper presents a system that combines KPI with autoencoders to implement a hybrid machine learning system. The goal here is to investigate workflows which permit the site manager to use the hybrid machine learning systems as a decision support tool. The workflows are explained by means of case studies, demonstrating the application of the hybrid system to detect both element as well as site related quality issues. In addition to that, the detection of anomalies regarding execution efficiency assist the project manager to optimize the sequence of work on site.

AB - This paper presents a system that combines KPI with autoencoders to implement a hybrid machine learning system. The goal here is to investigate workflows which permit the site manager to use the hybrid machine learning systems as a decision support tool. The workflows are explained by means of case studies, demonstrating the application of the hybrid system to detect both element as well as site related quality issues. In addition to that, the detection of anomalies regarding execution efficiency assist the project manager to optimize the sequence of work on site.

M3 - Conference contribution

SP - 569

EP - 574

BT - Proceedings of the ISRM 15th International Congress on Rock Mechanics and Rock Engineering & 72nd Geomechanics Colloquium

CY - Salzburg

ER -