---
_id: '67552'
abstract:
- lang: eng
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.
author:
- first_name: Iris
full_name: Gräßler, Iris
id: '47565'
last_name: Gräßler
orcid: 0000-0001-5765-971X
- first_name: Marcel
full_name: Niemeyer, Marcel
id: '68576'
last_name: Niemeyer
citation:
ama: 'Gräßler I, Niemeyer M. COMPETENCY PROFILES FOR THE USE OF PREDICTIVE MAINTENANCE
IN SMES. In: Gonzalez JDN, Romay MG, EUROSIS-ETI, eds. 24th INTERNATIONAL INDUSTRIAL
SIMULATION CONFERENCE. Vol 24. ; 2026:91-97.'
apa: Gräßler, I., & Niemeyer, M. (2026). COMPETENCY PROFILES FOR THE USE OF
PREDICTIVE MAINTENANCE IN SMES. In J. D. N. Gonzalez, M. G. Romay, & EUROSIS-ETI
(Eds.), 24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE (Vol. 24, 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} }'
chicago: Gräßler, Iris, and Marcel Niemeyer. “COMPETENCY PROFILES FOR THE USE OF
PREDICTIVE MAINTENANCE IN SMES.” In 24th INTERNATIONAL INDUSTRIAL SIMULATION
CONFERENCE, edited by Jose David Nunez Gonzalez, Manuel Grana Romay, and EUROSIS-ETI,
24:91–97, 2026.
ieee: I. Gräßler and M. Niemeyer, “COMPETENCY PROFILES FOR THE USE OF PREDICTIVE
MAINTENANCE IN SMES,” in 24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE,
San Sebastian, Spain, 2026, vol. 24, pp. 91–97.
mla: Gräßler, Iris, and Marcel Niemeyer. “COMPETENCY PROFILES FOR THE USE OF PREDICTIVE
MAINTENANCE IN SMES.” 24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE,
edited by Jose David Nunez Gonzalez et al., vol. 24, 2026, 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.'
conference:
end_date: 2026-05-29
location: San Sebastian, Spain
name: ' 24th Industrial Simulation Conference 2026'
start_date: 2026-05-27
corporate_editor:
- EUROSIS-ETI
date_created: 2026-10-15T13:58:59Z
date_updated: 2026-10-15T14:00:01Z
department:
- _id: '9'
- _id: '152'
editor:
- first_name: Jose David Nunez
full_name: Gonzalez, Jose David Nunez
last_name: Gonzalez
- first_name: Manuel Grana
full_name: Romay, Manuel Grana
last_name: Romay
intvolume: ' 24'
keyword:
- Predictive Maintenance
- Artificial Intelligence
- Data Processing
- Competencies
- Role Profiles
language:
- iso: eng
page: 91-97
publication: 24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE
publication_identifier:
isbn:
- ' 978-9-492859-40-2'
publication_status: published
quality_controlled: '1'
status: public
title: COMPETENCY PROFILES FOR THE USE OF PREDICTIVE MAINTENANCE IN SMES
type: conference
user_id: '68576'
volume: 24
year: '2026'
...
---
_id: '1156'
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.
author:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
- first_name: Hanmin
full_name: Jung, Hanmin
last_name: Jung
- first_name: Taehong
full_name: Kim, Taehong
last_name: Kim
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. Proceedings of the 2nd International Conference
on Internet of Things, Big Data and Security. Setúbal, Portugal: SCITEPRESS;
2017:117-124. doi:10.5220/0006354801170124'
apa: 'Kersting, J., Geierhos, M., Jung, H., & 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, & V. Chang (Eds.), Proceedings
of the 2nd International Conference on Internet of Things, Big Data and Security
(pp. 117–124). Setúbal, Portugal: SCITEPRESS. https://doi.org/10.5220/0006354801170124'
bibtex: '@inproceedings{Kersting_Geierhos_Jung_Kim_2017, place={Setúbal, Portugal},
title={Internet of Things Architecture for Handling Stream Air Pollution Data},
DOI={10.5220/0006354801170124},
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} }'
chicago: 'Kersting, Joschka, Michaela Geierhos, Hanmin Jung, and Taehong Kim. “Internet
of Things Architecture for Handling Stream Air Pollution Data.” In Proceedings
of the 2nd International Conference on Internet of Things, Big Data and Security,
edited by Muthu Ramachandran, Víctor Méndez Muñoz, Verena Kantere, Gary Wills,
Robert Walters, and Victor Chang, 117–24. Setúbal, Portugal: SCITEPRESS, 2017.
https://doi.org/10.5220/0006354801170124.'
ieee: J. Kersting, M. Geierhos, H. Jung, and T. Kim, “Internet of Things Architecture
for Handling Stream Air Pollution Data,” in Proceedings of the 2nd International
Conference on Internet of Things, Big Data and Security, Porto, Portugal,
2017, pp. 117–124.
mla: Kersting, Joschka, et al. “Internet of Things Architecture for Handling Stream
Air Pollution Data.” Proceedings of the 2nd International Conference on Internet
of Things, Big Data and Security, edited by Muthu Ramachandran et al., SCITEPRESS,
2017, pp. 117–24, doi:10.5220/0006354801170124.
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.'
conference:
end_date: 2017-04-26
location: Porto, Portugal
name: 2nd International Conference on Internet of Things, Big Data and Security
(IoTBDS 2017)
start_date: 2017-04-24
date_created: 2018-01-31T14:45:21Z
date_updated: 2022-01-06T06:51:03Z
ddc:
- '000'
department:
- _id: '36'
- _id: '1'
- _id: '579'
doi: 10.5220/0006354801170124
editor:
- first_name: Muthu
full_name: Ramachandran, Muthu
last_name: Ramachandran
- first_name: Víctor
full_name: Méndez Muñoz, Víctor
last_name: Méndez Muñoz
- first_name: Verena
full_name: Kantere, Verena
last_name: Kantere
- first_name: Gary
full_name: Wills, Gary
last_name: Wills
- first_name: Robert
full_name: Walters, Robert
last_name: Walters
- first_name: Victor
full_name: Chang, Victor
last_name: Chang
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2020-09-18T09:09:27Z
date_updated: 2020-09-18T09:09:27Z
file_id: '19567'
file_name: IoTBDS_2017_50_final.pdf
file_size: 2612566
relation: main_file
success: 1
file_date_updated: 2020-09-18T09:09:27Z
has_accepted_license: '1'
keyword:
- Wireless Sensor Network
- Internet of Things
- Stream Data
- Air Pollution
- DSMS
- Real-time Data Processing
language:
- iso: eng
page: 117-124
place: Setúbal, Portugal
publication: Proceedings of the 2nd International Conference on Internet of Things,
Big Data and Security
publication_identifier:
isbn:
- 978-989-758-245-5
publication_status: published
publisher: SCITEPRESS
quality_controlled: '1'
status: public
title: Internet of Things Architecture for Handling Stream Air Pollution Data
type: conference
user_id: '58701'
year: '2017'
...