[{"user_id":"68576","editor":[{"first_name":"Jose David Nunez","last_name":"Gonzalez","full_name":"Gonzalez, Jose David Nunez"},{"last_name":"Romay","first_name":"Manuel Grana","full_name":"Romay, Manuel Grana"}],"volume":24,"page":"91-97","_id":"67552","status":"public","conference":{"start_date":"2026-05-27","name":" 24th Industrial Simulation Conference 2026","location":"San Sebastian, Spain","end_date":"2026-05-29"},"quality_controlled":"1","citation":{"mla":"Gräßler, Iris, and Marcel Niemeyer. “COMPETENCY PROFILES FOR THE USE  OF PREDICTIVE MAINTENANCE IN SMES.” <i>24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE</i>, edited by Jose David Nunez Gonzalez et al., vol. 24, 2026, pp. 91–97.","bibtex":"@inproceedings{Gräßler_Niemeyer_2026, title={COMPETENCY PROFILES FOR THE USE  OF PREDICTIVE MAINTENANCE IN SMES}, volume={24}, booktitle={24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE}, author={Gräßler, Iris and Niemeyer, Marcel}, editor={Gonzalez, Jose David Nunez and Romay, Manuel Grana and EUROSIS-ETI}, year={2026}, pages={91–97} }","ama":"Gräßler I, Niemeyer M. COMPETENCY PROFILES FOR THE USE  OF PREDICTIVE MAINTENANCE IN SMES. In: Gonzalez JDN, Romay MG, EUROSIS-ETI, eds. <i>24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE</i>. Vol 24. ; 2026:91-97.","ieee":"I. Gräßler and M. Niemeyer, “COMPETENCY PROFILES FOR THE USE  OF PREDICTIVE MAINTENANCE IN SMES,” in <i>24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE</i>, San Sebastian, Spain, 2026, vol. 24, pp. 91–97.","apa":"Gräßler, I., &#38; Niemeyer, M. (2026). COMPETENCY PROFILES FOR THE USE  OF PREDICTIVE MAINTENANCE IN SMES. In J. D. N. Gonzalez, M. G. Romay, &#38; EUROSIS-ETI (Eds.), <i>24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE</i> (Vol. 24, pp. 91–97).","short":"I. Gräßler, M. Niemeyer, in: J.D.N. Gonzalez, M.G. Romay, EUROSIS-ETI (Eds.), 24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE, 2026, pp. 91–97.","chicago":"Gräßler, Iris, and Marcel Niemeyer. “COMPETENCY PROFILES FOR THE USE  OF PREDICTIVE MAINTENANCE IN SMES.” In <i>24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE</i>, edited by Jose David Nunez Gonzalez, Manuel Grana Romay, and EUROSIS-ETI, 24:91–97, 2026."},"language":[{"iso":"eng"}],"date_updated":"2026-10-15T14:00:01Z","publication_status":"published","intvolume":"        24","year":"2026","title":"COMPETENCY PROFILES FOR THE USE  OF PREDICTIVE MAINTENANCE IN SMES","publication_identifier":{"isbn":[" 978-9-492859-40-2"]},"corporate_editor":["EUROSIS-ETI"],"author":[{"full_name":"Gräßler, Iris","last_name":"Gräßler","orcid":"0000-0001-5765-971X","first_name":"Iris","id":"47565"},{"full_name":"Niemeyer, Marcel","first_name":"Marcel","last_name":"Niemeyer","id":"68576"}],"keyword":["Predictive Maintenance","Artificial Intelligence","Data Processing","Competencies","Role Profiles"],"type":"conference","department":[{"_id":"9"},{"_id":"152"}],"date_created":"2026-10-15T13:58:59Z","abstract":[{"text":"Predictive Maintenance is a key element of data-driven maintenance strategies in Industry 4.0. It promises improved asset availability and operational efficiency. In addition to data analytics and machine learning, simulation-based assessment and digital representations of production systems increasingly complement Predictive Maintenance by enabling the evaluation of maintenance decisions and failure risks before physical intervention. However, small and medium-sized enterprises (SMEs) often face challenges in realizing these benefits due to insufficient employee competencies across all domains. As a prerequisite, a clear understanding of competency gaps that hinder employees to use relevant key technologies such as artificial intelligence and data analytics is needed. This paper presents competency profiles that define relevant competencies for the use of simulation-based Predictive Maintenance and map these competencies to relevant roles that need them. The study is based on a systematic literature review about competencies for digitalization processes in industry focusing on maintenance and, more specifically, data technologies in maintenance. The competency profile is validated through a Delphi-Study with industry representatives assessing the identified competency levels. The results support a more holistic understanding of Predictive Maintenance and provide guidance for targeted competency development in SMEs.","lang":"eng"}],"publication":"24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE"},{"publication_identifier":{"isbn":["978-989-758-245-5"]},"author":[{"id":"58701","first_name":"Joschka","last_name":"Kersting","full_name":"Kersting, Joschka"},{"id":"42496","full_name":"Geierhos, Michaela","orcid":"0000-0002-8180-5606","first_name":"Michaela","last_name":"Geierhos"},{"last_name":"Jung","first_name":"Hanmin","full_name":"Jung, Hanmin"},{"full_name":"Kim, Taehong","first_name":"Taehong","last_name":"Kim"}],"year":"2017","title":"Internet of Things Architecture for Handling Stream Air Pollution Data","date_updated":"2022-01-06T06:51:03Z","publication_status":"published","language":[{"iso":"eng"}],"doi":"10.5220/0006354801170124","publication":"Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security","abstract":[{"lang":"eng","text":"In this paper, we present an IoT architecture which handles stream sensor data of air pollution. Particle pollution is known as a serious threat to human health. Along with developments in the use of wireless sensors and the IoT, we propose an architecture that flexibly measures and processes stream data collected in real-time by movable and low-cost IoT sensors. Thus, it enables a wide-spread network of wireless sensors that can follow changes in human behavior. Apart from stating reasons for the need of such a development and its requirements, we provide a conceptual design as well as a technological design of such an architecture. The technological design consists of Kaa and Apache Storm which can collect air pollution information in real-time and solve various problems to process data such as missing data and synchronization. This enables us to add a simulation in which we provide issues that might come up when having our architecture in use. Together with these issues, we state r easons for choosing specific modules among candidates. Our architecture combines wireless sensors with the Kaa IoT framework, an Apache Kafka pipeline and an Apache Storm Data Stream Management System among others. We even provide open-government data sets that are freely available."}],"date_created":"2018-01-31T14:45:21Z","file":[{"file_id":"19567","content_type":"application/pdf","success":1,"file_name":"IoTBDS_2017_50_final.pdf","access_level":"closed","file_size":2612566,"relation":"main_file","date_updated":"2020-09-18T09:09:27Z","date_created":"2020-09-18T09:09:27Z","creator":"jkers"}],"department":[{"_id":"36"},{"_id":"1"},{"_id":"579"}],"type":"conference","keyword":["Wireless Sensor Network","Internet of Things","Stream Data","Air Pollution","DSMS","Real-time Data Processing"],"conference":{"start_date":"2017-04-24","name":"2nd International Conference on Internet of Things, Big Data and Security (IoTBDS 2017)","location":"Porto, Portugal","end_date":"2017-04-26"},"status":"public","has_accepted_license":"1","publisher":"SCITEPRESS","_id":"1156","page":"117-124","editor":[{"last_name":"Ramachandran","first_name":"Muthu","full_name":"Ramachandran, Muthu"},{"full_name":"Méndez Muñoz, Víctor","last_name":"Méndez Muñoz","first_name":"Víctor"},{"last_name":"Kantere","first_name":"Verena","full_name":"Kantere, Verena"},{"last_name":"Wills","first_name":"Gary","full_name":"Wills, Gary"},{"last_name":"Walters","first_name":"Robert","full_name":"Walters, Robert"},{"last_name":"Chang","first_name":"Victor","full_name":"Chang, Victor"}],"ddc":["000"],"user_id":"58701","citation":{"ama":"Kersting J, Geierhos M, Jung H, Kim T. Internet of Things Architecture for Handling Stream Air Pollution Data. In: Ramachandran M, Méndez Muñoz V, Kantere V, Wills G, Walters R, Chang V, eds. <i>Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security</i>. Setúbal, Portugal: SCITEPRESS; 2017:117-124. doi:<a href=\"https://doi.org/10.5220/0006354801170124\">10.5220/0006354801170124</a>","bibtex":"@inproceedings{Kersting_Geierhos_Jung_Kim_2017, place={Setúbal, Portugal}, title={Internet of Things Architecture for Handling Stream Air Pollution Data}, DOI={<a href=\"https://doi.org/10.5220/0006354801170124\">10.5220/0006354801170124</a>}, booktitle={Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security}, publisher={SCITEPRESS}, author={Kersting, Joschka and Geierhos, Michaela and Jung, Hanmin and Kim, Taehong}, editor={Ramachandran, Muthu and Méndez Muñoz, Víctor and Kantere, Verena and Wills, Gary and Walters, Robert and Chang, VictorEditors}, year={2017}, pages={117–124} }","mla":"Kersting, Joschka, et al. “Internet of Things Architecture for Handling Stream Air Pollution Data.” <i>Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security</i>, edited by Muthu Ramachandran et al., SCITEPRESS, 2017, pp. 117–24, doi:<a href=\"https://doi.org/10.5220/0006354801170124\">10.5220/0006354801170124</a>.","short":"J. Kersting, M. Geierhos, H. Jung, T. Kim, in: M. Ramachandran, V. Méndez Muñoz, V. Kantere, G. Wills, R. Walters, V. Chang (Eds.), Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security, SCITEPRESS, Setúbal, Portugal, 2017, pp. 117–124.","chicago":"Kersting, Joschka, Michaela Geierhos, Hanmin Jung, and Taehong Kim. “Internet of Things Architecture for Handling Stream Air Pollution Data.” In <i>Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security</i>, edited by Muthu Ramachandran, Víctor Méndez Muñoz, Verena Kantere, Gary Wills, Robert Walters, and Victor Chang, 117–24. Setúbal, Portugal: SCITEPRESS, 2017. <a href=\"https://doi.org/10.5220/0006354801170124\">https://doi.org/10.5220/0006354801170124</a>.","apa":"Kersting, J., Geierhos, M., Jung, H., &#38; Kim, T. (2017). Internet of Things Architecture for Handling Stream Air Pollution Data. In M. Ramachandran, V. Méndez Muñoz, V. Kantere, G. Wills, R. Walters, &#38; V. Chang (Eds.), <i>Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security</i> (pp. 117–124). Setúbal, Portugal: SCITEPRESS. <a href=\"https://doi.org/10.5220/0006354801170124\">https://doi.org/10.5220/0006354801170124</a>","ieee":"J. Kersting, M. Geierhos, H. Jung, and T. Kim, “Internet of Things Architecture for Handling Stream Air Pollution Data,” in <i>Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security</i>, Porto, Portugal, 2017, pp. 117–124."},"file_date_updated":"2020-09-18T09:09:27Z","quality_controlled":"1","place":"Setúbal, Portugal"}]