@inproceedings{98f8c3706aa4413b9ba75854bc11a00a,
title = "An intelligent maintenance planning framework prototype for production systems",
abstract = "The Intelligent Maintenance Planner (IMP) is designed to automate and improve maintenance processes in industrial applications. The system tracks the entire process cycle beginning with data acquisition and management, it then detects and classifies failure states, initializes maintenance cases, and selects and assigns the required resources. IMP guides maintenance work processes, by automatically providing instructions and augmented reality information. Subsequent feedback of the maintenance process and new or updated information is added to the system and used to train selection algorithms. A prototype of IMP was implemented based on an industrial SCADA system and cloud solutions for storage and machine learning capabilities. This report explains the stages of the maintenance process and provides an outline of the implementation and project results. {\textcopyright} 2017 IEEE.",
keywords = "Augmented reality, Digital storage, Learning systems, Maintenance, SCADA systems, Intelligent maintenance, Maintenance process, Maintenance work, Process cycles, Production system, Selection algorithm, System tracks, Updated informations, Information management",
author = "S. Kranzer and D. Prill and D. Aghajanpour and R. Merz and R. Strasser and R. Mayr and H. Zoerrer and M. Plasch and R. Steringer",
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year = "2017",
doi = "10.1109/ICIT.2017.7915520",
language = "English",
isbn = "978-1-5090-5321-6",
pages = "1124--1129",
booktitle = "2017 IEEE International Conference on Industrial Technology (ICIT)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",
url = "https://icit2017.org/",
}