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

Alexander Zöhrer, Vincent Winter, Anika Terbuch, Paul O'Leary, Negin Khalilimotlaghkasmaei

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.
Original languageEnglish
Title of host publication Proceedings of the ISRM 15th International Congress on Rock Mechanics and Rock Engineering & 72nd Geomechanics Colloquium
Subtitle of host publicationChallenges in Rock Mechanics and Rock Engineering
Place of PublicationSalzburg
Number of pages6
ISBN (Electronic)978-3-9503898-3-8
Publication statusPublished - 9 Oct 2023

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