FIG Peer Review Journal


Proposed 4.0 Industrial Management System for daily operations that poses point cloud assets with annotated real-time sensory measurements and utilizes unsupervised alert logic (11297)

Ion-Anastasios Karolos, Stylianos Bitharis, Vasileios Tsioukas, Christos Pikridas, Sotirios Kontogiannis, Theodosios Gkamas and Nikolaos Zinas (Greece)
Mr. Ion-Anastasios Karolos
Aristotle University of Thessaloniki
Dept. of Geodesy and Surveying
Corresponding author Mr. Ion-Anastasios Karolos (email: ikarolos[at]

[ abstract ] [ paper ] [ handouts ]

Published on the web 2022-05-16
Received 2022-01-07 / Accepted 2022-04-22
This paper is one of selection of papers published for the FIG Congress 2022 in Warsaw, Poland in Warsaw, Poland and has undergone the FIG Peer Review Process.

FIG Congress 2022 in Warsaw, Poland
ISBN n/a ISSN 2308-3441


The safety and enforcement of preventive maintenance procedures specifically for equipment in large industrial infrastructures is a matter of major importance in particular, in the Oil and Gas industry. Historically, industrial maintenance operations were executed only when strictly necessary. However, maintenance processes are stochastic, dynamic, and complex in industrial manufacturing environments. Nowadays, the maintenance paradigm is changing, and industrial maintenance is now understood as a strategic factor and a profit contributor to ensuring productivity in industrial systems. An important parameter to satisfy this point is the production of digital twins which can be derived through accurate and detail survey. In this paper, a holistic industry 4.0 solution towards industrial maintenance is presented. The study focuses on the oil refinery industry and present their proposed maintenance system architecture, system implementation, technical and basic functional characteristics. The current study took place at Hellenic Petroleum facilities in Northern Greece.
Keywords: Professional practice; Laser scanning; Engineering survey; Security of tenure; laser scanning; 3D point cloud; geometrical info; maintenance; Oil and Gas Industry 4.0 Management Systems; Data mining; IoT; Machine Learning;