---
_id: '12785'
abstract:
- lang: eng
text: Due to the demographic aging of society, the demand for skilled caregiving
is increasing. However, the already existing shortage of professional caregivers
will exacerbate in the future. As a result, family caregivers must shoulder a
heavier share of the care burden. To ease the burden and promote a better work-life
balance, we developed the Digital Case Manager. This tool uses machine learning
algorithms to learn the relationship between a care situation and the next care
steps and helps family caregivers balance their professional and private lives
so that they are able to continue caring for their family members without sacrificing
their own jobs and personal ambitions. The data for the machine learning model
are generated by means of a questionnaire based on professional assessment instruments.
We implemented a proof-of-concept of the Digital Case Manager and initial tests
show promising results. It offers a quick and easy-to-use tool for family caregivers
in the early stages of a care situation.
article_number: '1215'
author:
- first_name: Paul
full_name: Wunderlich, Paul
id: '52317'
last_name: Wunderlich
- first_name: Frauke
full_name: Wiegräbe, Frauke
id: '76510'
last_name: Wiegräbe
- first_name: Helene
full_name: Dörksen, Helene
id: '46416'
last_name: Dörksen
citation:
ama: Wunderlich P, Wiegräbe F, Dörksen H. Digital Case Manager-A Data-Driven Tool
to Support Family Caregivers with Initial Guidance. INTERNATIONAL JOURNAL OF
ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH. 2023;20(2). doi:10.3390/ijerph20021215
apa: Wunderlich, P., Wiegräbe, F., & Dörksen, H. (2023). Digital Case Manager-A
Data-Driven Tool to Support Family Caregivers with Initial Guidance. INTERNATIONAL
JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 20(2), Article
1215. https://doi.org/10.3390/ijerph20021215
bjps: Wunderlich P, Wiegräbe F and Dörksen H (2023) Digital Case Manager-A
Data-Driven Tool to Support Family Caregivers with Initial Guidance. INTERNATIONAL
JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 20.
chicago: Wunderlich, Paul, Frauke Wiegräbe, and Helene Dörksen. “Digital Case Manager-A
Data-Driven Tool to Support Family Caregivers with Initial Guidance.” INTERNATIONAL
JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 20, no. 2 (2023). https://doi.org/10.3390/ijerph20021215.
chicago-de: Wunderlich, Paul, Frauke Wiegräbe und Helene Dörksen. 2023. Digital
Case Manager-A Data-Driven Tool to Support Family Caregivers with Initial Guidance.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 20, Nr.
2. doi:10.3390/ijerph20021215,
.
din1505-2-1: 'Wunderlich, Paul ; Wiegräbe, Frauke ; Dörksen,
Helene: Digital Case Manager-A Data-Driven Tool to Support Family Caregivers
with Initial Guidance. In: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH
AND PUBLIC HEALTH Bd. 20. Basel, MDPI (2023), Nr. 2'
havard: P. Wunderlich, F. Wiegräbe, H. Dörksen, Digital Case Manager-A Data-Driven
Tool to Support Family Caregivers with Initial Guidance, INTERNATIONAL JOURNAL
OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH. 20 (2023).
ieee: 'P. Wunderlich, F. Wiegräbe, and H. Dörksen, “Digital Case Manager-A Data-Driven
Tool to Support Family Caregivers with Initial Guidance,” INTERNATIONAL JOURNAL
OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, vol. 20, no. 2, Art. no. 1215,
2023, doi: 10.3390/ijerph20021215.'
mla: Wunderlich, Paul, et al. “Digital Case Manager-A Data-Driven Tool to Support
Family Caregivers with Initial Guidance.” INTERNATIONAL JOURNAL OF ENVIRONMENTAL
RESEARCH AND PUBLIC HEALTH, vol. 20, no. 2, 1215, 2023, https://doi.org/10.3390/ijerph20021215.
short: P. Wunderlich, F. Wiegräbe, H. Dörksen, INTERNATIONAL JOURNAL OF ENVIRONMENTAL
RESEARCH AND PUBLIC HEALTH 20 (2023).
ufg: 'Wunderlich, Paul/Wiegräbe, Frauke/Dörksen, Helene: Digital Case Manager-A
Data-Driven Tool to Support Family Caregivers with Initial Guidance, in: INTERNATIONAL
JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 20 (2023), H. 2.'
van: Wunderlich P, Wiegräbe F, Dörksen H. Digital Case Manager-A Data-Driven Tool
to Support Family Caregivers with Initial Guidance. INTERNATIONAL JOURNAL OF ENVIRONMENTAL
RESEARCH AND PUBLIC HEALTH. 2023;20(2).
date_created: 2025-04-14T13:39:52Z
date_updated: 2025-06-25T13:11:41Z
department:
- _id: DEP5023
- _id: DEP5000
doi: 10.3390/ijerph20021215
external_id:
isi:
- '000918039900001'
pmid:
- '36673969'
intvolume: ' 20'
isi: '1'
issue: '2'
keyword:
- machine learning
- healthcare
- case management
- caring
- multi-label classification
language:
- iso: eng
place: Basel
pmid: '1'
publication: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
publication_identifier:
eissn:
- 1660-4601
issn:
- '1661-7827 '
publication_status: published
publisher: MDPI
quality_controlled: '1'
status: public
title: Digital Case Manager-A Data-Driven Tool to Support Family Caregivers with Initial
Guidance
type: scientific_journal_article
user_id: '83781'
volume: 20
year: '2023'
...
---
_id: '13015'
abstract:
- lang: eng
text: food are discarded annually, with a worldwide total exceeding 1.3
billion tonnes. A significant contributor to this issue are consumers throwing
away still edible food due to the expiration of its best-before date. Best-before
dates currently include large safety margins, but more precise and cost effective
prediction techniques are required. To address this challenge, research was conducted
on low-cost sensors and machine learning techniques were developed to predict
the spoilage of fresh pizza. The findings indicate that combining a gas sensor,
such as volatile organic compounds or carbon dioxide, with a random forest or
extreme gradient boosting regressor can accurately predict the day of spoilage.
This provides a more accurate and cost-efficient alternative to current best-before
date determination methods, reducing food waste, saving resources, and improving
food safety by reducing the risk of consumers consuming spoiled food.
article_number: '1347'
author:
- first_name: Paul
full_name: Wunderlich, Paul
id: '52317'
last_name: Wunderlich
- first_name: Daniel
full_name: Pauli, Daniel
id: '75850'
last_name: Pauli
orcid: '0000-0003-0860-4696 '
- first_name: Michael
full_name: Neumaier, Michael
id: '77059'
last_name: Neumaier
- first_name: Stephanie
full_name: Wisser, Stephanie
id: '76627'
last_name: Wisser
- first_name: Hans-Jürgen
full_name: Danneel, Hans-Jürgen
id: '12231'
last_name: Danneel
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
- first_name: Helene
full_name: Dörksen, Helene
id: '46416'
last_name: Dörksen
citation:
ama: Wunderlich P, Pauli D, Neumaier M, et al. Enhancing Shelf Life Prediction of
Fresh Pizza with Regression Models and Low Cost Sensors. Foods. 2023;12(6).
doi:10.3390/foods12061347
apa: Wunderlich, P., Pauli, D., Neumaier, M., Wisser, S., Danneel, H.-J., Lohweg,
V., & Dörksen, H. (2023). Enhancing Shelf Life Prediction of Fresh Pizza with
Regression Models and Low Cost Sensors. Foods, 12(6), Article 1347.
https://doi.org/10.3390/foods12061347
bjps: Wunderlich P et al. (2023) Enhancing Shelf Life Prediction of
Fresh Pizza with Regression Models and Low Cost Sensors. Foods 12.
chicago: Wunderlich, Paul, Daniel Pauli, Michael Neumaier, Stephanie Wisser, Hans-Jürgen
Danneel, Volker Lohweg, and Helene Dörksen. “Enhancing Shelf Life Prediction of
Fresh Pizza with Regression Models and Low Cost Sensors.” Foods 12, no.
6 (2023). https://doi.org/10.3390/foods12061347.
chicago-de: Wunderlich, Paul, Daniel Pauli, Michael Neumaier, Stephanie Wisser,
Hans-Jürgen Danneel, Volker Lohweg und Helene Dörksen. 2023. Enhancing Shelf Life
Prediction of Fresh Pizza with Regression Models and Low Cost Sensors. Foods
12, Nr. 6. doi:10.3390/foods12061347,
.
din1505-2-1: 'Wunderlich, Paul ; Pauli, Daniel ; Neumaier,
Michael ; Wisser, Stephanie
; Danneel, Hans-Jürgen ; Lohweg,
Volker ; Dörksen, Helene:
Enhancing Shelf Life Prediction of Fresh Pizza with Regression Models and Low
Cost Sensors. In: Foods Bd. 12. Basel, MDPI (2023), Nr. 6'
havard: P. Wunderlich, D. Pauli, M. Neumaier, S. Wisser, H.-J. Danneel, V. Lohweg,
H. Dörksen, Enhancing Shelf Life Prediction of Fresh Pizza with Regression Models
and Low Cost Sensors, Foods. 12 (2023).
ieee: 'P. Wunderlich et al., “Enhancing Shelf Life Prediction of Fresh Pizza
with Regression Models and Low Cost Sensors,” Foods, vol. 12, no. 6, Art.
no. 1347, 2023, doi: 10.3390/foods12061347.'
mla: Wunderlich, Paul, et al. “Enhancing Shelf Life Prediction of Fresh Pizza with
Regression Models and Low Cost Sensors.” Foods, vol. 12, no. 6, 1347, 2023,
https://doi.org/10.3390/foods12061347.
short: P. Wunderlich, D. Pauli, M. Neumaier, S. Wisser, H.-J. Danneel, V. Lohweg,
H. Dörksen, Foods 12 (2023).
ufg: 'Wunderlich, Paul u. a.: Enhancing Shelf Life Prediction of Fresh Pizza
with Regression Models and Low Cost Sensors, in: Foods 12 (2023), H. 6.'
van: Wunderlich P, Pauli D, Neumaier M, Wisser S, Danneel HJ, Lohweg V, et al. Enhancing
Shelf Life Prediction of Fresh Pizza with Regression Models and Low Cost Sensors.
Foods. 2023;12(6).
date_created: 2025-06-24T13:25:13Z
date_updated: 2025-06-25T13:13:13Z
department:
- _id: DEP5023
- _id: DEP1308
doi: 10.3390/foods12061347
external_id:
isi:
- '000967890400001'
pmid:
- '36981272'
intvolume: ' 12'
isi: '1'
issue: '6'
keyword:
- Plant Science
- Health Professions (miscellaneous)
- Health (social science)
- Microbiology
- Food Science
language:
- iso: eng
place: Basel
pmid: '1'
publication: Foods
publication_identifier:
eissn:
- 2304-8158
publication_status: published
publisher: 'MDPI '
status: public
title: Enhancing Shelf Life Prediction of Fresh Pizza with Regression Models and Low
Cost Sensors
type: scientific_journal_article
user_id: '83781'
volume: 12
year: '2023'
...
---
_id: '4780'
author:
- first_name: Andreas
full_name: Bunte, Andreas
id: '58885'
last_name: Bunte
- first_name: Paul
full_name: Wunderlich, Paul
id: '52317'
last_name: Wunderlich
- first_name: Natalia
full_name: Moriz, Natalia
id: '44238'
last_name: Moriz
- first_name: Peng
full_name: Li, Peng
id: '58937'
last_name: Li
- first_name: Andre
full_name: Mankowski, Andre
id: '51482'
last_name: Mankowski
- first_name: Antje
full_name: Rogalla, Antje
id: '66617'
last_name: Rogalla
- first_name: Oliver
full_name: Niggemann, Oliver
id: '10876'
last_name: Niggemann
citation:
ama: 'Bunte A, Wunderlich P, Moriz N, et al. Why Symbolic AI is a Key Technology
for Self-Adaption in the Context of CPPS. In: 24nd IEEE International Conference
on Emerging Technologies and Factory Automation (ETFA). Zaragoza, Spain; 2019.'
apa: Bunte, A., Wunderlich, P., Moriz, N., Li, P., Mankowski, A., Rogalla, A., &
Niggemann, O. (2019). Why Symbolic AI is a Key Technology for Self-Adaption in
the Context of CPPS. In 24nd IEEE International Conference on Emerging Technologies
and Factory Automation (ETFA). Zaragoza, Spain.
bjps: Bunte A et al. (2019) Why Symbolic AI Is a Key Technology for
Self-Adaption in the Context of CPPS. 24nd IEEE International Conference on
Emerging Technologies and Factory Automation (ETFA). Zaragoza, Spain.
chicago: Bunte, Andreas, Paul Wunderlich, Natalia Moriz, Peng Li, Andre Mankowski,
Antje Rogalla, and Oliver Niggemann. “Why Symbolic AI Is a Key Technology for
Self-Adaption in the Context of CPPS.” In 24nd IEEE International Conference
on Emerging Technologies and Factory Automation (ETFA). Zaragoza, Spain, 2019.
chicago-de: 'Bunte, Andreas, Paul Wunderlich, Natalia Moriz, Peng Li, Andre Mankowski,
Antje Rogalla und Oliver Niggemann. 2019. Why Symbolic AI is a Key Technology
for Self-Adaption in the Context of CPPS. In: 24nd IEEE International Conference
on Emerging Technologies and Factory Automation (ETFA). Zaragoza, Spain.'
din1505-2-1: 'Bunte, Andreas ; Wunderlich, Paul ; Moriz,
Natalia ; Li, Peng ; Mankowski, Andre ; Rogalla,
Antje ; Niggemann, Oliver:
Why Symbolic AI is a Key Technology for Self-Adaption in the Context of CPPS.
In: 24nd IEEE International Conference on Emerging Technologies and Factory
Automation (ETFA). Zaragoza, Spain, 2019'
havard: 'A. Bunte, P. Wunderlich, N. Moriz, P. Li, A. Mankowski, A. Rogalla, O.
Niggemann, Why Symbolic AI is a Key Technology for Self-Adaption in the Context
of CPPS, in: 24nd IEEE International Conference on Emerging Technologies and Factory
Automation (ETFA), Zaragoza, Spain, 2019.'
ieee: A. Bunte et al., “Why Symbolic AI is a Key Technology for Self-Adaption
in the Context of CPPS,” in 24nd IEEE International Conference on Emerging
Technologies and Factory Automation (ETFA), 2019.
mla: Bunte, Andreas, et al. “Why Symbolic AI Is a Key Technology for Self-Adaption
in the Context of CPPS.” 24nd IEEE International Conference on Emerging Technologies
and Factory Automation (ETFA), 2019.
short: 'A. Bunte, P. Wunderlich, N. Moriz, P. Li, A. Mankowski, A. Rogalla, O. Niggemann,
in: 24nd IEEE International Conference on Emerging Technologies and Factory Automation
(ETFA), Zaragoza, Spain, 2019.'
ufg: 'Bunte, Andreas et. al. (2019): Why Symbolic AI is a Key Technology
for Self-Adaption in the Context of CPPS, in: 24nd IEEE International Conference
on Emerging Technologies and Factory Automation (ETFA), Zaragoza, Spain.'
van: 'Bunte A, Wunderlich P, Moriz N, Li P, Mankowski A, Rogalla A, et al. Why Symbolic
AI is a Key Technology for Self-Adaption in the Context of CPPS. In: 24nd IEEE
International Conference on Emerging Technologies and Factory Automation (ETFA).
Zaragoza, Spain; 2019.'
date_created: 2021-02-02T08:08:34Z
date_updated: 2023-03-15T13:49:55Z
department:
- _id: DEP5023
language:
- iso: eng
place: Zaragoza, Spain
publication: 24nd IEEE International Conference on Emerging Technologies and Factory
Automation (ETFA)
status: public
title: Why Symbolic AI is a Key Technology for Self-Adaption in the Context of CPPS
type: conference
user_id: '68554'
year: 2019
...
---
_id: '12803'
abstract:
- lang: eng
text: The increasing amount of alarms and information for an operator in a modern
plant becomes a significant safety risk. Although the notifications are a valuable
support, they also lead to the curse of overloading with information for the operator.
Due to the huge amount of alarms it is almost impossible to separate the crucial
information from the insignificant ones. Therefore, new procedures are required
to reduce these alarm floods and support the operator to minimize the safety risk.
One approach is based on learning a causal model that represents the relationships
between the alarms. This allows alarm sequences that are causally implied to be
reduced to the root cause alarm. Fundamental element of this approach is the causal
model. Therefore in this work, different probabilistic graphical models are considered
and evaluated on the basis of appropriate criteria. A real use case of a bottle
filling module serves as a benchmark for how well they are suitable as a causal
model for the application in alarm flood reduction.
author:
- first_name: Paul
full_name: Wunderlich, Paul
id: '52317'
last_name: Wunderlich
- first_name: Nemanja
full_name: Hranisavljevic, Nemanja
id: '62376'
last_name: Hranisavljevic
citation:
ama: Wunderlich P, Hranisavljevic N. Comparison of Different Probabilistic Graphical
Models as Causal Models in Alarm Flood Reduction. (Aalto University, Finland,
Tampere University, Finland, Finnish Society of Automation, Finland, eds.). IEEE;
2019:1285-1290. doi:10.1109/indin41052.2019.8972251
apa: Wunderlich, P., & Hranisavljevic, N. (2019). Comparison of Different Probabilistic
Graphical Models as Causal Models in Alarm Flood Reduction. In Aalto University,
Finland, Tampere University, Finland, & Finnish Society of Automation, Finland
(Eds.), 2019 IEEE 17th International Conference on Industrial Informatics (INDIN)
(pp. 1285–1290). IEEE. https://doi.org/10.1109/indin41052.2019.8972251
bjps: 'Wunderlich P and Hranisavljevic N (2019) Comparison of Different
Probabilistic Graphical Models as Causal Models in Alarm Flood Reduction,
Aalto University, Finland, Tampere University, Finland, and Finnish Society of
Automation, Finland (eds). [Piscataway, NJ]: IEEE.'
chicago: 'Wunderlich, Paul, and Nemanja Hranisavljevic. Comparison of Different
Probabilistic Graphical Models as Causal Models in Alarm Flood Reduction.
Edited by Aalto University, Finland, Tampere University, Finland, and Finnish
Society of Automation, Finland. 2019 IEEE 17th International Conference on
Industrial Informatics (INDIN). [Piscataway, NJ]: IEEE, 2019. https://doi.org/10.1109/indin41052.2019.8972251.'
chicago-de: 'Wunderlich, Paul und Nemanja Hranisavljevic. 2019. Comparison of
Different Probabilistic Graphical Models as Causal Models in Alarm Flood Reduction.
Hg. von Aalto University, Finland, Tampere University, Finland, und Finnish Society
of Automation, Finland. 2019 IEEE 17th International Conference on Industrial
Informatics (INDIN). [Piscataway, NJ]: IEEE. doi:10.1109/indin41052.2019.8972251,
.'
din1505-2-1: 'Wunderlich, Paul ; Hranisavljevic, Nemanja ; Aalto
University, Finland ; Tampere University,
Finland ; Finnish Society of Automation,
Finland (Hrsg.): Comparison of Different Probabilistic Graphical Models
as Causal Models in Alarm Flood Reduction. [Piscataway, NJ] : IEEE, 2019'
havard: P. Wunderlich, N. Hranisavljevic, Comparison of Different Probabilistic
Graphical Models as Causal Models in Alarm Flood Reduction, IEEE, [Piscataway,
NJ], 2019.
ieee: 'P. Wunderlich and N. Hranisavljevic, Comparison of Different Probabilistic
Graphical Models as Causal Models in Alarm Flood Reduction. [Piscataway, NJ]:
IEEE, 2019, pp. 1285–1290. doi: 10.1109/indin41052.2019.8972251.'
mla: Wunderlich, Paul, and Nemanja Hranisavljevic. “Comparison of Different Probabilistic
Graphical Models as Causal Models in Alarm Flood Reduction.” 2019 IEEE 17th
International Conference on Industrial Informatics (INDIN), edited by Aalto
University, Finland et al., IEEE, 2019, pp. 1285–90, https://doi.org/10.1109/indin41052.2019.8972251.
short: P. Wunderlich, N. Hranisavljevic, Comparison of Different Probabilistic Graphical
Models as Causal Models in Alarm Flood Reduction, IEEE, [Piscataway, NJ], 2019.
ufg: 'Wunderlich, Paul/Hranisavljevic, Nemanja: Comparison of Different Probabilistic
Graphical Models as Causal Models in Alarm Flood Reduction, hg. von Aalto University,
Finland/Tampere University, Finland, Finnish Society of Automation, Finland, [Piscataway,
NJ] 2019.'
van: 'Wunderlich P, Hranisavljevic N. Comparison of Different Probabilistic Graphical
Models as Causal Models in Alarm Flood Reduction. Aalto University, Finland, Tampere
University, Finland, Finnish Society of Automation, Finland, editors. 2019 IEEE
17th International Conference on Industrial Informatics (INDIN). [Piscataway,
NJ]: IEEE; 2019.'
conference:
end_date: 2019-07-25
location: 'Helsinki, Finland '
name: 17th IEEE International Conference on Industrial Informatics (INDIN)
start_date: 2019-07-22
corporate_editor:
- Aalto University, Finland
- Tampere University, Finland
- Finnish Society of Automation, Finland
date_created: 2025-04-16T06:29:04Z
date_updated: 2025-06-26T13:38:06Z
department:
- _id: DEP5023
doi: 10.1109/indin41052.2019.8972251
keyword:
- probabilistic graphical model
- causal model
- alarm flood reduction
- Bayesian network
- Markov chain
- restricted boltzmann machine
- automata
language:
- iso: eng
page: 1285-1290
place: '[Piscataway, NJ]'
publication: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN)
publication_identifier:
eisbn:
- 978-1-7281-2927-3
isbn:
- 978-1-7281-2928-0
publication_status: published
publisher: IEEE
status: public
title: Comparison of Different Probabilistic Graphical Models as Causal Models in
Alarm Flood Reduction
type: conference_editor_article
user_id: '83781'
year: '2019'
...
---
_id: '4327'
abstract:
- lang: eng
text: In ever changing world, the industrial systems become more and more complex.
Machine feedback in the form of alarms and notifications, due to its growing volume,
becomes overwhelming for the operator. In addition, expectations in relation to
system availability are growing as well. Therefore, there exists strong need for
new solutions guaranteeing fast troubleshooting of problems that arise during
system operation. The approach proposed in this study uses advantages of the Asset
Administration Shell, machine learning, and human-machine interaction in order
to create the assistance system which holistically addresses the issue of troubleshooting
complex industrial systems.
author:
- first_name: Dorota
full_name: Lang, Dorota
id: '68941'
last_name: Lang
- first_name: Paul
full_name: Wunderlich, Paul
id: '52317'
last_name: Wunderlich
- first_name: Mario
full_name: Heinz, Mario
id: '68913'
last_name: Heinz
- first_name: Lukasz
full_name: Wisniewski, Lukasz
id: '1710'
last_name: Wisniewski
- first_name: Jürgen
full_name: Jasperneite, Jürgen
id: '1899'
last_name: Jasperneite
- first_name: Oliver
full_name: Niggemann, Oliver
id: '10876'
last_name: Niggemann
- first_name: Carsten
full_name: Röcker, Carsten
id: '61525'
last_name: Röcker
citation:
ama: 'Lang D, Wunderlich P, Heinz M, et al. Assistance System to Support Troubleshooting
of Complex Industrial Systems. In: 14th IEEE International Workshop on Factory
Communication Systems (WFCS). Piscataway, NJ: IEEE; 2018. doi:10.1109/WFCS.2018.8402380'
apa: 'Lang, D., Wunderlich, P., Heinz, M., Wisniewski, L., Jasperneite, J., Niggemann,
O., & Röcker, C. (2018). Assistance System to Support Troubleshooting of Complex
Industrial Systems. In 14th IEEE International Workshop on Factory Communication
Systems (WFCS). Piscataway, NJ: IEEE. https://doi.org/10.1109/WFCS.2018.8402380'
bjps: 'Lang D et al. (2018) Assistance System to Support Troubleshooting
of Complex Industrial Systems. 14th IEEE International Workshop on Factory
Communication Systems (WFCS). Piscataway, NJ: IEEE.'
chicago: 'Lang, Dorota, Paul Wunderlich, Mario Heinz, Lukasz Wisniewski, Jürgen
Jasperneite, Oliver Niggemann, and Carsten Röcker. “Assistance System to Support
Troubleshooting of Complex Industrial Systems.” In 14th IEEE International
Workshop on Factory Communication Systems (WFCS). Piscataway, NJ: IEEE, 2018.
https://doi.org/10.1109/WFCS.2018.8402380.'
chicago-de: 'Lang, Dorota, Paul Wunderlich, Mario Heinz, Lukasz Wisniewski, Jürgen
Jasperneite, Oliver Niggemann und Carsten Röcker. 2018. Assistance System to Support
Troubleshooting of Complex Industrial Systems. In: 14th IEEE International
Workshop on Factory Communication Systems (WFCS). Piscataway, NJ: IEEE. doi:10.1109/WFCS.2018.8402380,
.'
din1505-2-1: 'Lang, Dorota ; Wunderlich, Paul ; Heinz,
Mario ; Wisniewski, Lukasz
; Jasperneite, Jürgen ; Niggemann,
Oliver ; Röcker, Carsten:
Assistance System to Support Troubleshooting of Complex Industrial Systems. In:
14th IEEE International Workshop on Factory Communication Systems (WFCS).
Piscataway, NJ : IEEE, 2018'
havard: 'D. Lang, P. Wunderlich, M. Heinz, L. Wisniewski, J. Jasperneite, O. Niggemann,
C. Röcker, Assistance System to Support Troubleshooting of Complex Industrial
Systems, in: 14th IEEE International Workshop on Factory Communication Systems
(WFCS), IEEE, Piscataway, NJ, 2018.'
ieee: D. Lang et al., “Assistance System to Support Troubleshooting of Complex
Industrial Systems,” in 14th IEEE International Workshop on Factory Communication
Systems (WFCS), Imperia, Italy , 2018.
mla: Lang, Dorota, et al. “Assistance System to Support Troubleshooting of Complex
Industrial Systems.” 14th IEEE International Workshop on Factory Communication
Systems (WFCS), IEEE, 2018, doi:10.1109/WFCS.2018.8402380.
short: 'D. Lang, P. Wunderlich, M. Heinz, L. Wisniewski, J. Jasperneite, O. Niggemann,
C. Röcker, in: 14th IEEE International Workshop on Factory Communication Systems
(WFCS), IEEE, Piscataway, NJ, 2018.'
ufg: 'Lang, Dorota et. al. (2018): Assistance System to Support Troubleshooting
of Complex Industrial Systems, in: 14th IEEE International Workshop on Factory
Communication Systems (WFCS), Piscataway, NJ.'
van: 'Lang D, Wunderlich P, Heinz M, Wisniewski L, Jasperneite J, Niggemann O, et
al. Assistance System to Support Troubleshooting of Complex Industrial Systems.
In: 14th IEEE International Workshop on Factory Communication Systems (WFCS).
Piscataway, NJ: IEEE; 2018.'
conference:
end_date: 2018-06-15
location: 'Imperia, Italy '
name: 14th IEEE International Workshop on Factory Communication Systems (WFCS)
start_date: 2018-06-13
date_created: 2021-01-08T08:26:30Z
date_updated: 2023-03-15T13:49:52Z
department:
- _id: DEP5023
- _id: DEP5019
doi: 10.1109/WFCS.2018.8402380
keyword:
- Maintenance engineering
- Adaptation models
- Machine learning
- Data models
- Standards
- Software
- Bayes methods
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
place: Piscataway, NJ
publication: 14th IEEE International Workshop on Factory Communication Systems (WFCS)
publication_identifier:
eisbn:
- 978-1-5386-1066-4
publication_status: published
publisher: IEEE
status: public
title: Assistance System to Support Troubleshooting of Complex Industrial Systems
type: conference
user_id: '45673'
year: 2018
...
---
_id: '4254'
abstract:
- lang: eng
text: The current trend of integrating machines and factories into cyber-physical
systems (CPS) creates an enormous complexity for operators of such systems. Especially
the search for the root cause of cascading failures becomes highly time-consuming.
Within this paper, we address the question on how to help human users to better
and faster understand root causes of such situations. We propose a concept of
interactive alarm flood reduction and present the implementation of a first vertical
prototype for such a system. We consider this prototype as a first artifact to
be discussed by the research community and aim towards an incremental further
development of the system in order to support humans in complex error situations.
author:
- first_name: Sebastian
full_name: Büttner, Sebastian
id: '61868'
last_name: Büttner
- first_name: Paul
full_name: Wunderlich, Paul
id: '52317'
last_name: Wunderlich
- first_name: Mario
full_name: Heinz, Mario
id: '68913'
last_name: Heinz
- first_name: Oliver
full_name: Niggemann, Oliver
id: '10876'
last_name: Niggemann
- first_name: Carsten
full_name: Röcker, Carsten
id: '61525'
last_name: Röcker
citation:
ama: 'Büttner S, Wunderlich P, Heinz M, Niggemann O, Röcker C. Managing Complexity:
Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction.
In: Holzinger A, ed. Machine Learning and Knowledge Extraction : First IFIP
TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio,
Italy, August 29 – September 1, 2017, Proceedings. Vol 10410. Lecture Notes
in Computer Science . Cham: Springer; 2017:69-82.'
apa: 'Büttner, S., Wunderlich, P., Heinz, M., Niggemann, O., & Röcker, C. (2017).
Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive
Alarm Flood Reduction. In A. Holzinger (Ed.), Machine Learning and Knowledge
Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference,
CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings (Vol.
10410, pp. 69–82). Cham: Springer.'
bjps: 'Büttner S et al. (2017) Managing Complexity: Towards Intelligent
Error-Handling Assistance Trough Interactive Alarm Flood Reduction. In Holzinger
A (ed.), Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4,
8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy,
August 29 – September 1, 2017, Proceedings, vol. 10410. Cham: Springer, pp.
69–82.'
chicago: 'Büttner, Sebastian, Paul Wunderlich, Mario Heinz, Oliver Niggemann, and
Carsten Röcker. “Managing Complexity: Towards Intelligent Error-Handling Assistance
Trough Interactive Alarm Flood Reduction.” In Machine Learning and Knowledge
Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference,
CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings, edited
by Andreas Holzinger, 10410:69–82. Lecture Notes in Computer Science . Cham: Springer,
2017.'
chicago-de: 'Büttner, Sebastian, Paul Wunderlich, Mario Heinz, Oliver Niggemann
und Carsten Röcker. 2017. Managing Complexity: Towards Intelligent Error-Handling
Assistance Trough Interactive Alarm Flood Reduction. In: Machine Learning
and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain
Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings,
hg. von Andreas Holzinger, 10410:69–82. Lecture Notes in Computer Science . Cham:
Springer.'
din1505-2-1: 'Büttner, Sebastian ;
Wunderlich, Paul ; Heinz,
Mario ; Niggemann, Oliver
; Röcker, Carsten: Managing Complexity:
Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction.
In: Holzinger, A. (Hrsg.): Machine
Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International
Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1,
2017, Proceedings, Lecture Notes in Computer Science . Bd. 10410. Cham :
Springer, 2017, S. 69–82'
havard: 'S. Büttner, P. Wunderlich, M. Heinz, O. Niggemann, C. Röcker, Managing
Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm
Flood Reduction, in: A. Holzinger (Ed.), Machine Learning and Knowledge Extraction :
First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE
2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings, Springer, Cham,
2017: pp. 69–82.'
ieee: 'S. Büttner, P. Wunderlich, M. Heinz, O. Niggemann, and C. Röcker, “Managing
Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm
Flood Reduction,” in Machine Learning and Knowledge Extraction : First IFIP
TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio,
Italy, August 29 – September 1, 2017, Proceedings, Reggio, Italy, 2017, vol.
10410, pp. 69–82.'
mla: 'Büttner, Sebastian, et al. “Managing Complexity: Towards Intelligent Error-Handling
Assistance Trough Interactive Alarm Flood Reduction.” Machine Learning and
Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain
Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings,
edited by Andreas Holzinger, vol. 10410, Springer, 2017, pp. 69–82.'
short: 'S. Büttner, P. Wunderlich, M. Heinz, O. Niggemann, C. Röcker, in: A. Holzinger
(Ed.), Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9,
12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August
29 – September 1, 2017, Proceedings, Springer, Cham, 2017, pp. 69–82.'
ufg: 'Büttner, Sebastian et. al. (2017): Managing Complexity: Towards Intelligent
Error-Handling Assistance Trough Interactive Alarm Flood Reduction, in: Andreas
Holzinger (Hg.): Machine Learning and Knowledge Extraction : First IFIP TC
5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio,
Italy, August 29 – September 1, 2017, Proceedings (=Lecture Notes in Computer
Science 10410), Cham, S. 69–82.'
van: 'Büttner S, Wunderlich P, Heinz M, Niggemann O, Röcker C. Managing Complexity:
Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction.
In: Holzinger A, editor. Machine Learning and Knowledge Extraction : First IFIP
TC 5, WG 84, 89, 129 International Cross-Domain Conference, CD-MAKE 2017, Reggio,
Italy, August 29 – September 1, 2017, Proceedings. Cham: Springer; 2017. p. 69–82.
(Lecture Notes in Computer Science ; vol. 10410).'
conference:
end_date: 2017-09-01
location: Reggio, Italy
name: International Cross-Domain Conference, CD-MAKE 2017
start_date: 2017-08-29
date_created: 2020-12-10T13:40:04Z
date_updated: 2023-03-15T13:49:51Z
department:
- _id: DEP5023
editor:
- first_name: Andreas
full_name: Holzinger, Andreas
last_name: Holzinger
intvolume: ' 10410'
keyword:
- Alarm flood reduction
- Machine learning
- Assistive system
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
page: 69-82
place: Cham
publication: ' Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4,
8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August
29 – September 1, 2017, Proceedings'
publication_identifier:
eisbn:
- '9783319668086 '
isbn:
- 978-3-319-66807-9
publication_status: published
publisher: Springer
series_title: 'Lecture Notes in Computer Science '
status: public
title: 'Managing Complexity: Towards Intelligent Error-Handling Assistance Trough
Interactive Alarm Flood Reduction'
type: conference
user_id: '15514'
volume: 10410
year: 2017
...