---
_id: '570'
abstract:
- lang: eng
text: Additive manufacturing (AM) has matured rapidly during the last years due
to the advancement of AM machines and materials. Nevertheless, the widespread
adoption of AM is still challenged by producing parts with reliable quality. The
aim of this paper is t o introduce a first approach to apply in-situ monitoring
for quality evaluation of produced parts. Based on the monitored data, a model
is developed, in order to predict the quality of ready built parts.
author:
- first_name: Eva
full_name: Scheideler, Eva
id: '61522'
last_name: Scheideler
- first_name: Andrea
full_name: Huxol, Andrea
id: '43559'
last_name: Huxol
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
id: '14290'
last_name: Villmer
citation:
ama: 'Scheideler E, Huxol A, Villmer F-J. Nondestructive Quality Check of Additive
Manufactured Parts Using Empirical Models. In: Padoano E, Villmer F-J, Department
of Production Engineering and Management, eds. Production Engineeringand Management.
Publication series in direct digital manufacturing . Lemgo; 2017:89-100.'
apa: Scheideler, E., Huxol, A., & Villmer, F.-J. (2017). Nondestructive Quality
Check of Additive Manufactured Parts Using Empirical Models. In E. Padoano, F.-J.
Villmer, & Department of Production Engineering and Management (Eds.), Production
Engineeringand Management (pp. 89–100). Lemgo.
bjps: Scheideler E, Huxol A and Villmer F-J (2017) Nondestructive Quality
Check of Additive Manufactured Parts Using Empirical Models. In Padoano E, Villmer
F-J and Department of Production Engineering and Management (eds), Production
Engineeringand Management. Lemgo, pp. 89–100.
chicago: Scheideler, Eva, Andrea Huxol, and Franz-Josef Villmer. “Nondestructive
Quality Check of Additive Manufactured Parts Using Empirical Models.” In Production
Engineeringand Management, edited by Elio Padoano, Franz-Josef Villmer, and
Department of Production Engineering and Management, 89–100. Publication Series
in Direct Digital Manufacturing . Lemgo, 2017.
chicago-de: 'Scheideler, Eva, Andrea Huxol und Franz-Josef Villmer. 2017. Nondestructive
Quality Check of Additive Manufactured Parts Using Empirical Models. In: Production
Engineeringand Management, hg. von Elio Padoano, Franz-Josef Villmer, und
Department of Production Engineering and Management, 89–100. Publication series
in direct digital manufacturing . Lemgo.'
din1505-2-1: 'Scheideler, Eva ; Huxol, Andrea ; Villmer,
Franz-Josef: Nondestructive Quality Check of Additive Manufactured Parts
Using Empirical Models. In: Padoano, E.
; Villmer, F.-J. ; Department
of Production Engineering and Management (Hrsg.): Production Engineeringand
Management, Publication series in direct digital manufacturing . Lemgo,
2017, S. 89–100'
havard: 'E. Scheideler, A. Huxol, F.-J. Villmer, Nondestructive Quality Check of
Additive Manufactured Parts Using Empirical Models, in: E. Padoano, F.-J. Villmer,
Department of Production Engineering and Management (Eds.), Production Engineeringand
Management, Lemgo, 2017: pp. 89–100.'
ieee: E. Scheideler, A. Huxol, and F.-J. Villmer, “Nondestructive Quality Check
of Additive Manufactured Parts Using Empirical Models,” in Production Engineeringand
Management, Pordenone, Italy, 2017, no. 1, pp. 89–100.
mla: Scheideler, Eva, et al. “Nondestructive Quality Check of Additive Manufactured
Parts Using Empirical Models.” Production Engineeringand Management, edited
by Elio Padoano et al., no. 1, 2017, pp. 89–100.
short: 'E. Scheideler, A. Huxol, F.-J. Villmer, in: E. Padoano, F.-J. Villmer, Department
of Production Engineering and Management (Eds.), Production Engineeringand Management,
Lemgo, 2017, pp. 89–100.'
ufg: 'Scheideler, Eva et. al. (2017): Nondestructive Quality Check of Additive
Manufactured Parts Using Empirical Models, in: Elio Padoano et. al. (Hgg.): Production
Engineeringand Management (=Publication series in direct digital manufacturing
), Lemgo, S. 89–100.'
van: 'Scheideler E, Huxol A, Villmer F-J. Nondestructive Quality Check of Additive
Manufactured Parts Using Empirical Models. In: Padoano E, Villmer F-J, Department
of Production Engineering and Management, editors. Production Engineeringand Management.
Lemgo; 2017. p. 89–100. (Publication series in direct digital manufacturing ).'
conference:
end_date: 2017-09-29
location: Pordenone, Italy
name: Proceedings7th International Conference
start_date: 2017-09-28
corporate_editor:
- Department of Production Engineering and Management
- Hochschule Ostwestfalen-Lippe
date_created: 2019-02-18T09:46:43Z
date_updated: 2023-03-15T13:50:01Z
department:
- _id: DEP1306
editor:
- first_name: Elio
full_name: Padoano, Elio
last_name: Padoano
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
last_name: Villmer
issue: '1'
keyword:
- Nondestructive quality control
- Predictive analytics
- Metal model
- Additive manufacturing
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2017_Proceeding_web.pdf
oa: '1'
page: 89-100
place: Lemgo
publication: Production Engineeringand Management
publication_identifier:
isbn:
- 978-3-946856-01-6
publication_status: published
related_material:
link:
- relation: contains
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2017_Proceeding_web.pdf
series_title: 'Publication series in direct digital manufacturing '
status: public
title: Nondestructive Quality Check of Additive Manufactured Parts Using Empirical
Models
type: conference
user_id: '45673'
year: 2017
...
---
_id: '577'
abstract:
- lang: eng
text: A rising number of product variants together with decreasing lot sizes are
a result of the trend of individualization. Besides the upcoming organizational
issues, changes in the production technologies are required. Direct digital manufacturing
contributes to solve this problem by enabling the production of parts right from
the CAD data.Process capability analysis is applied in several industries to prove
the reliable compliance of products with quality requirements. As it is based
on statistical methods, new challenges arise in the context of single-part production.The
paper describes and compares different approaches for the adoption of process
capability analysis for single-part production with special focus on additive
manufacturing technologies. The statistical background and the applicability of
different capability parameters are discussed. An overview of existing research
work is given and supplemented by own approaches for the adoption of statistical
methods for single-part production. The aim of the research work is to establish
a first approach for the qualification of new technologies in single-part production.
author:
- first_name: Andrea
full_name: Huxol, Andrea
id: '43559'
last_name: Huxol
- first_name: Andrea
full_name: Davis, Andrea
id: '68611'
last_name: Davis
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
id: '14290'
last_name: Villmer
- first_name: Eva
full_name: Scheideler, Eva
id: '61522'
last_name: Scheideler
citation:
ama: 'Huxol A, Davis A, Villmer F-J, Scheideler E. Deployment of Process Capability
Analysis for Single-Part Production. In: Padoano E, Villmer F-J, Department of
Production Engineering and Management, eds. Production Engineering and Management.
Publication series in direct digital manufacturing . Lemgo; 2017:63-74.'
apa: Huxol, A., Davis, A., Villmer, F.-J., & Scheideler, E. (2017). Deployment
of Process Capability Analysis for Single-Part Production. In E. Padoano, F.-J.
Villmer, & Department of Production Engineering and Management (Eds.), Production
Engineering and Management (pp. 63–74). Lemgo.
bjps: Huxol A et al. (2017) Deployment of Process Capability Analysis
for Single-Part Production. In Padoano E, Villmer F-J and Department of Production
Engineering and Management (eds), Production Engineering and Management.
Lemgo, pp. 63–74.
chicago: Huxol, Andrea, Andrea Davis, Franz-Josef Villmer, and Eva Scheideler. “Deployment
of Process Capability Analysis for Single-Part Production.” In Production Engineering
and Management, edited by Elio Padoano, Franz-Josef Villmer, and Department
of Production Engineering and Management, 63–74. Publication Series in Direct
Digital Manufacturing . Lemgo, 2017.
chicago-de: 'Huxol, Andrea, Andrea Davis, Franz-Josef Villmer und Eva Scheideler.
2017. Deployment of Process Capability Analysis for Single-Part Production. In:
Production Engineering and Management, hg. von Elio Padoano, Franz-Josef
Villmer, und Department of Production Engineering and Management, 63–74. Publication
series in direct digital manufacturing . Lemgo.'
din1505-2-1: 'Huxol, Andrea ; Davis, Andrea ; Villmer,
Franz-Josef ; Scheideler, Eva:
Deployment of Process Capability Analysis for Single-Part Production. In: Padoano, E. ; Villmer,
F.-J. ; Department of Production
Engineering and Management (Hrsg.): Production Engineering and Management,
Publication series in direct digital manufacturing . Lemgo, 2017, S. 63–74'
havard: 'A. Huxol, A. Davis, F.-J. Villmer, E. Scheideler, Deployment of Process
Capability Analysis for Single-Part Production, in: E. Padoano, F.-J. Villmer,
Department of Production Engineering and Management (Eds.), Production Engineering
and Management, Lemgo, 2017: pp. 63–74.'
ieee: A. Huxol, A. Davis, F.-J. Villmer, and E. Scheideler, “Deployment of Process
Capability Analysis for Single-Part Production,” in Production Engineering
and Management, Pordenone, Italy, 2017, no. 1, pp. 63–74.
mla: Huxol, Andrea, et al. “Deployment of Process Capability Analysis for Single-Part
Production.” Production Engineering and Management, edited by Elio Padoano
et al., no. 1, 2017, pp. 63–74.
short: 'A. Huxol, A. Davis, F.-J. Villmer, E. Scheideler, in: E. Padoano, F.-J.
Villmer, Department of Production Engineering and Management (Eds.), Production
Engineering and Management, Lemgo, 2017, pp. 63–74.'
ufg: 'Huxol, Andrea et. al. (2017): Deployment of Process Capability Analysis
for Single-Part Production, in: Elio Padoano et. al. (Hgg.): Production Engineering
and Management (=Publication series in direct digital manufacturing ),
Lemgo, S. 63–74.'
van: 'Huxol A, Davis A, Villmer F-J, Scheideler E. Deployment of Process Capability
Analysis for Single-Part Production. In: Padoano E, Villmer F-J, Department of
Production Engineering and Management, editors. Production Engineering and Management.
Lemgo; 2017. p. 63–74. (Publication series in direct digital manufacturing ).'
conference:
end_date: 2017-09-29
location: Pordenone, Italy
name: Proceedings7th International Conference
start_date: 2017-09-28
corporate_editor:
- Department of Production Engineering and Management
- Hochschule Ostwestfalen-Lippe
date_created: 2019-02-18T11:16:07Z
date_updated: 2023-03-15T13:50:01Z
department:
- _id: DEP1306
editor:
- first_name: Elio
full_name: Padoano, Elio
last_name: Padoano
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
last_name: Villmer
issue: '1'
keyword:
- Statistical process control
- Process capability analysis
- Single-part production
- Process optimization
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2017_Proceeding_web.pdf
oa: '1'
page: 63-74
place: Lemgo
publication: Production Engineering and Management
publication_identifier:
isbn:
- 978-3-946856-01-6
publication_status: published
related_material:
link:
- relation: contains
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2017_Proceeding_web.pdf
series_title: 'Publication series in direct digital manufacturing '
status: public
title: Deployment of Process Capability Analysis for Single-Part Production
type: conference
user_id: '45673'
year: 2017
...
---
_id: '579'
abstract:
- lang: eng
text: Selective Laser Melting (SLM) is a powder bed fusion process to produce additively
metal parts. From the current point of view, it seems to be one of the most promising
additive manufacturing technologies for the production of end use parts. An increasing
number of examples prove the successful application of SLM for technical part
production. Nevertheless, they also show the enormous effort that is still required
to qualify the production process of every single part individually.The present
paper gives an overview of the major influencing factors of the SLM process. To
get a comprehensive research approach, existing publications on the topic are
taken into account as well as own experimental work, evaluating the effects of
the process parameters on the relative density of samples made from tool steel.
The experimental setup and the results are described and opportunities for the
further research work are discussed.
author:
- first_name: Andrea
full_name: Huxol, Andrea
id: '43559'
last_name: Huxol
- first_name: Eva
full_name: Scheideler, Eva
id: '61522'
last_name: Scheideler
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
id: '14290'
last_name: Villmer
citation:
ama: 'Huxol A, Scheideler E, Villmer F-J. Influencing Factors on Part Quality in
Selective Laser Melting. In: Padoano E, Villmer F-J, Department of Production
Engineering and Management, eds. Production Engineering and Management.
Lemgo; 2017:13-34.'
apa: Huxol, A., Scheideler, E., & Villmer, F.-J. (2017). Influencing Factors
on Part Quality in Selective Laser Melting. In E. Padoano, F.-J. Villmer, &
Department of Production Engineering and Management (Eds.), Production Engineering
and Management (pp. 13–34). Lemgo.
bjps: Huxol A, Scheideler E and Villmer F-J (2017) Influencing Factors on
Part Quality in Selective Laser Melting. In Padoano E, Villmer F-J and Department
of Production Engineering and Management (eds), Production Engineering and
Management. Lemgo, pp. 13–34.
chicago: Huxol, Andrea, Eva Scheideler, and Franz-Josef Villmer. “Influencing Factors
on Part Quality in Selective Laser Melting.” In Production Engineering and
Management, edited by Elio Padoano, Franz-Josef Villmer, and Department of
Production Engineering and Management, 13–34. Lemgo, 2017.
chicago-de: 'Huxol, Andrea, Eva Scheideler und Franz-Josef Villmer. 2017. Influencing
Factors on Part Quality in Selective Laser Melting. In: Production Engineering
and Management, hg. von Elio Padoano, Franz-Josef Villmer, und Department
of Production Engineering and Management, 13–34. Lemgo.'
din1505-2-1: 'Huxol, Andrea ; Scheideler, Eva ; Villmer,
Franz-Josef: Influencing Factors on Part Quality in Selective Laser Melting.
In: Padoano, E. ; Villmer,
F.-J. ; Department of Production
Engineering and Management (Hrsg.): Production Engineering and Management.
Lemgo, 2017, S. 13–34'
havard: 'A. Huxol, E. Scheideler, F.-J. Villmer, Influencing Factors on Part Quality
in Selective Laser Melting, in: E. Padoano, F.-J. Villmer, Department of Production
Engineering and Management (Eds.), Production Engineering and Management, Lemgo,
2017: pp. 13–34.'
ieee: A. Huxol, E. Scheideler, and F.-J. Villmer, “Influencing Factors on Part Quality
in Selective Laser Melting,” in Production Engineering and Management,
Pordenone, Italy, 2017, no. 1, pp. 13–34.
mla: Huxol, Andrea, et al. “Influencing Factors on Part Quality in Selective Laser
Melting.” Production Engineering and Management, edited by Elio Padoano
et al., no. 1, 2017, pp. 13–34.
short: 'A. Huxol, E. Scheideler, F.-J. Villmer, in: E. Padoano, F.-J. Villmer, Department
of Production Engineering and Management (Eds.), Production Engineering and Management,
Lemgo, 2017, pp. 13–34.'
ufg: 'Huxol, Andrea et. al. (2017): Influencing Factors on Part Quality in
Selective Laser Melting, in: Elio Padoano et. al. (Hgg.): Production Engineering
and Management, Lemgo, S. 13–34.'
van: 'Huxol A, Scheideler E, Villmer F-J. Influencing Factors on Part Quality in
Selective Laser Melting. In: Padoano E, Villmer F-J, Department of Production
Engineering and Management, editors. Production Engineering and Management. Lemgo;
2017. p. 13–34.'
conference:
end_date: 2017-09-29
location: Pordenone, Italy
name: Proceedings 7th International Conference
start_date: 2017-09-28
corporate_editor:
- Department of Production Engineering and Management
- Hochschule Ostwestfalen-Lippe
date_created: 2019-02-18T11:34:36Z
date_updated: 2023-03-15T13:50:02Z
department:
- _id: DEP1306
editor:
- first_name: Elio
full_name: Padoano, Elio
last_name: Padoano
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
last_name: Villmer
issue: '1'
keyword:
- Selective laser melting
- Additive manufacturing
- Process parameters
- Process optimization
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2017_Proceeding_web.pdf
oa: '1'
page: 13-34
place: Lemgo
publication: Production Engineering and Management
publication_identifier:
isbn:
- 978-3-946856-01-6
publication_status: published
related_material:
link:
- relation: contains
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2017_Proceeding_web.pdf
status: public
title: Influencing Factors on Part Quality in Selective Laser Melting
type: conference
user_id: '45673'
year: 2017
...
---
_id: '580'
abstract:
- lang: eng
text: Additive Manufacturing (AM) is increasingly used to design new products. This
is possible due to the further development of the AM-processes and materials.
The lack of quality assurance of AM built parts is a key technological barrier
that prevents manufacturers from adopting. The quality of an additive manufactured
part is influenced by more than 50 parameters, which make process control difficult.
Current research deals with using real time monitoring of the melt pool as feedback
control for laser power. This paper illustrates challenges and opportunities of
applying statistical predictive modeling and unsupervised learning to control
additive manufacturing. In particular, an approach how to build a feedforward
controller will be discussed.
author:
- first_name: Eva
full_name: Scheideler, Eva
id: '61522'
last_name: Scheideler
- first_name: Andrea
full_name: Ahlemeyer-Stubbe, Andrea
last_name: Ahlemeyer-Stubbe
citation:
ama: 'Scheideler E, Ahlemeyer-Stubbe A. Quality Control of Additive Manufacturing
Using Statistical Prediction Models. In: Padoano E, Villmer FJ, Department of
Production Engineering and Management, Hochschule Ostwestfalen-Lippe, eds.
Production Engineering and Management : Proceedings 7th International Conference,
September 28 and 29, 2017, Pordenone, Italy . Vol 2017. Publication series
in direct digital manufacturing . ; 2017:3-12.'
apa: 'Scheideler, E., & Ahlemeyer-Stubbe, A. (2017). Quality Control of Additive
Manufacturing Using Statistical Prediction Models. In E. Padoano, F.-J. Villmer,
Department of Production Engineering and Management, & Hochschule Ostwestfalen-Lippe
(Eds.), Production engineering and management : proceedings 7th international
conference, September 28 and 29, 2017, Pordenone, Italy (Vol. 2017, Issue
1, pp. 3–12).'
bjps: 'Scheideler E and Ahlemeyer-Stubbe A (2017) Quality Control of Additive
Manufacturing Using Statistical Prediction Models. In Padoano E et al. (eds),
Production Engineering and Management : Proceedings 7th International Conference,
September 28 and 29, 2017, Pordenone, Italy , vol. 2017. Lemgo, pp. 3–12.'
chicago: 'Scheideler, Eva, and Andrea Ahlemeyer-Stubbe. “Quality Control of Additive
Manufacturing Using Statistical Prediction Models.” In Production Engineering
and Management : Proceedings 7th International Conference, September 28 and 29,
2017, Pordenone, Italy , edited by Elio Padoano, Franz-Josef Villmer, Department
of Production Engineering and Management, and Hochschule Ostwestfalen-Lippe, 2017:3–12.
Publication Series in Direct Digital Manufacturing . Lemgo, 2017.'
chicago-de: 'Scheideler, Eva und Andrea Ahlemeyer-Stubbe. 2017. Quality Control
of Additive Manufacturing Using Statistical Prediction Models. In: Production
engineering and management : proceedings 7th international conference, September
28 and 29, 2017, Pordenone, Italy , hg. von Elio Padoano, Franz-Josef Villmer,
Department of Production Engineering and Management, und Hochschule Ostwestfalen-Lippe,
2017:3–12. Publication series in direct digital manufacturing . Lemgo.'
din1505-2-1: 'Scheideler, Eva ; Ahlemeyer-Stubbe, Andrea: Quality Control
of Additive Manufacturing Using Statistical Prediction Models. In: Padoano,
E. ; Villmer, F.-J. ; Department of Production Engineering and Management
; Hochschule Ostwestfalen-Lippe
(Hrsg.): Production engineering and management : proceedings 7th international
conference, September 28 and 29, 2017, Pordenone, Italy , Publication
series in direct digital manufacturing . Bd. 2017. Lemgo, 2017, S. 3–12'
havard: 'E. Scheideler, A. Ahlemeyer-Stubbe, Quality Control of Additive Manufacturing
Using Statistical Prediction Models, in: E. Padoano, F.-J. Villmer, Department
of Production Engineering and Management, Hochschule Ostwestfalen-Lippe (Eds.),
Production Engineering and Management : Proceedings 7th International Conference,
September 28 and 29, 2017, Pordenone, Italy , Lemgo, 2017: pp. 3–12.'
ieee: 'E. Scheideler and A. Ahlemeyer-Stubbe, “Quality Control of Additive Manufacturing
Using Statistical Prediction Models,” in Production engineering and management :
proceedings 7th international conference, September 28 and 29, 2017, Pordenone,
Italy , Pordenone, Italy, 2017, vol. 2017, no. 1, pp. 3–12.'
mla: 'Scheideler, Eva, and Andrea Ahlemeyer-Stubbe. “Quality Control of Additive
Manufacturing Using Statistical Prediction Models.” Production Engineering
and Management : Proceedings 7th International Conference, September 28 and 29,
2017, Pordenone, Italy , edited by Elio Padoano et al., vol. 2017, no. 1,
2017, pp. 3–12.'
short: 'E. Scheideler, A. Ahlemeyer-Stubbe, in: E. Padoano, F.-J. Villmer, Department
of Production Engineering and Management, Hochschule Ostwestfalen-Lippe (Eds.),
Production Engineering and Management : Proceedings 7th International Conference,
September 28 and 29, 2017, Pordenone, Italy , Lemgo, 2017, pp. 3–12.'
ufg: 'Scheideler, Eva/Ahlemeyer-Stubbe, Andrea: Quality Control of Additive
Manufacturing Using Statistical Prediction Models, in: Padoano, Elio u. a.
(Hgg.): Production engineering and management : proceedings 7th international
conference, September 28 and 29, 2017, Pordenone, Italy , Bd. 2017, Lemgo 2017
( Publication series in direct digital manufacturing ), S. 3–12.'
van: 'Scheideler E, Ahlemeyer-Stubbe A. Quality Control of Additive Manufacturing
Using Statistical Prediction Models. In: Padoano E, Villmer FJ, Department of
Production Engineering and Management, Hochschule Ostwestfalen-Lippe, editors.
Production engineering and management : proceedings 7th international conference,
September 28 and 29, 2017, Pordenone, Italy . Lemgo; 2017. p. 3–12. ( Publication
series in direct digital manufacturing ; vol. 2017).'
conference:
end_date: 2017-09-29
location: Pordenone, Italy
name: 7th International Conference on Production Engineering and Management
start_date: 2017-09-28
corporate_editor:
- Department of Production Engineering and Management
- Hochschule Ostwestfalen-Lippe
date_created: 2019-02-18T11:34:36Z
date_updated: 2024-03-22T13:19:02Z
department:
- _id: DEP1306
editor:
- first_name: Elio
full_name: Padoano, Elio
last_name: Padoano
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
id: '14290'
last_name: Villmer
intvolume: ' 2017'
issue: '1'
keyword:
- Additive manufacturing
- Process control
- Predictive modeling
- Predictive control
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2017_Proceeding_web.pdf
oa: '1'
page: 3-12
place: Lemgo
publication: "\t Production engineering and management : proceedings 7th international
conference, September 28 and 29, 2017, Pordenone, Italy "
publication_identifier:
isbn:
- 978-3-946856-01-6
publication_status: published
related_material:
link:
- relation: contains
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2017_Proceeding_web.pdf
series_title: "\t Publication series in direct digital manufacturing "
status: public
title: Quality Control of Additive Manufacturing Using Statistical Prediction Models
type: conference
user_id: '83781'
volume: 2017
year: '2017'
...
---
_id: '581'
author:
- first_name: Eva
full_name: Scheideler, Eva
id: '61522'
last_name: Scheideler
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
id: '14290'
last_name: Villmer
citation:
ama: 'Scheideler E, Villmer F-J. Anforderungen an integrierte Prozessketten in der
Additiven Fertigung. In: Rapid.Tech – International Trade Show & Conference
for Additive Manufacturing. München: Carl Hanser Verlag GmbH & Co. KG;
2017:10-24. doi:10.3139/9783446454606.001'
apa: 'Scheideler, E., & Villmer, F.-J. (2017). Anforderungen an integrierte
Prozessketten in der Additiven Fertigung. In Rapid.Tech – International Trade
Show & Conference for Additive Manufacturing (pp. 10–24). München: Carl
Hanser Verlag GmbH & Co. KG. https://doi.org/10.3139/9783446454606.001'
bjps: 'Scheideler E and Villmer F-J (2017) Anforderungen an Integrierte Prozessketten
in Der Additiven Fertigung. Rapid.Tech – International Trade Show & Conference
for Additive Manufacturing. München: Carl Hanser Verlag GmbH & Co. KG,
pp. 10–24.'
chicago: 'Scheideler, Eva, and Franz-Josef Villmer. “Anforderungen an Integrierte
Prozessketten in Der Additiven Fertigung.” In Rapid.Tech – International Trade
Show & Conference for Additive Manufacturing, 10–24. München: Carl Hanser
Verlag GmbH & Co. KG, 2017. https://doi.org/10.3139/9783446454606.001.'
chicago-de: 'Scheideler, Eva und Franz-Josef Villmer. 2017. Anforderungen an integrierte
Prozessketten in der Additiven Fertigung. In: Rapid.Tech – International Trade
Show & Conference for Additive Manufacturing, 10–24. München: Carl Hanser
Verlag GmbH & Co. KG. doi:10.3139/9783446454606.001,
.'
din1505-2-1: 'Scheideler, Eva ; Villmer, Franz-Josef: Anforderungen an
integrierte Prozessketten in der Additiven Fertigung. In: Rapid.Tech – International
Trade Show & Conference for Additive Manufacturing. München : Carl Hanser
Verlag GmbH & Co. KG, 2017, S. 10–24'
havard: 'E. Scheideler, F.-J. Villmer, Anforderungen an integrierte Prozessketten
in der Additiven Fertigung, in: Rapid.Tech – International Trade Show & Conference
for Additive Manufacturing, Carl Hanser Verlag GmbH & Co. KG, München, 2017:
pp. 10–24.'
ieee: E. Scheideler and F.-J. Villmer, “Anforderungen an integrierte Prozessketten
in der Additiven Fertigung,” in Rapid.Tech – International Trade Show &
Conference for Additive Manufacturing, 2017, no. 1, pp. 10–24.
mla: Scheideler, Eva, and Franz-Josef Villmer. “Anforderungen an Integrierte Prozessketten
in Der Additiven Fertigung.” Rapid.Tech – International Trade Show & Conference
for Additive Manufacturing, no. 1, Carl Hanser Verlag GmbH & Co. KG, 2017,
pp. 10–24, doi:10.3139/9783446454606.001.
short: 'E. Scheideler, F.-J. Villmer, in: Rapid.Tech – International Trade Show
& Conference for Additive Manufacturing, Carl Hanser Verlag GmbH & Co.
KG, München, 2017, pp. 10–24.'
ufg: 'Scheideler, Eva/Villmer, Franz-Josef (2017): Anforderungen an integrierte
Prozessketten in der Additiven Fertigung, in: Rapid.Tech – International Trade
Show & Conference for Additive Manufacturing, München, S. 10–24.'
van: 'Scheideler E, Villmer F-J. Anforderungen an integrierte Prozessketten in der
Additiven Fertigung. In: RapidTech – International Trade Show & Conference
for Additive Manufacturing. München: Carl Hanser Verlag GmbH & Co. KG; 2017.
p. 10–24.'
date_created: 2019-02-18T13:02:40Z
date_updated: 2023-03-15T13:50:02Z
department:
- _id: DEP1306
doi: 10.3139/9783446454606.001
issue: '1'
language:
- iso: eng
main_file_link:
- url: https://www.hanser-elibrary.com/doi/pdf/10.3139/9783446454606.001
page: 10-24
place: München
publication: Rapid.Tech – International Trade Show & Conference for Additive Manufacturing
publication_identifier:
isbn:
- 978-3-44645459-0
- 978-3-44645460-6
publication_status: published
publisher: Carl Hanser Verlag GmbH & Co. KG
related_material:
link:
- relation: contains
url: https://www.hanser-elibrary.com/doi/pdf/10.3139/9783446454606.001
- relation: supplementary_material
url: https://www.hs-owl.de/fb7/fileadmin/download/labore/konstruktion/06_Tagungen/01_RP_Tagungen/22_RP/Scheideler_DiMan.pdf
status: public
title: Anforderungen an integrierte Prozessketten in der Additiven Fertigung
type: conference
user_id: '45673'
year: 2017
...
---
_id: '609'
abstract:
- lang: ger
text: Einfach, ohne Expertenwissen anzuwenden – solch ein Planungswerkzeug spart
Zeit und Geld. Dieser Artikel stellt eine neue, effiziente Berechnungsmöglichkeit
vor, die z.B. Vertriebsmitarbeiter oder Architekten befähigt, Risiken bezüglich
Durch‐ oder Absturzsicherheit bei allseitig gelagerten Verglasungen früh in der
Planung schnell abzuprüfen. Dabei werden statistische Modelle und Simulationsberechnungen
eingesetzt. Verifiziert wurde die Methode gemäß DIN 18008 Teil 4 und Teil 6 mit
den Möglichkeiten der Finite‐Element‐Rechnung und Referenzdatensätzen. Sie kann
eine finale statische Beurteilung (z.B. prüffähige Statik) nicht ersetzen, doch
sie kann im Lauf der Planung verlässliche Abschätzungen liefern und somit Geld
und Zeit einsparen.
author:
- first_name: Eva
full_name: Scheideler, Eva
id: '61522'
last_name: Scheideler
- first_name: Andrea
full_name: Ahlemeyer-Stubbe, Andrea
last_name: Ahlemeyer-Stubbe
- first_name: Josef
full_name: Scheideler, Josef
last_name: Scheideler
citation:
ama: 'Scheideler E, Ahlemeyer-Stubbe A, Scheideler J. Statistische Modellierung
zur Unterstützung von Industrie 4.0 im Glasbau. ce/papers : Proceedings in
Civil Engineering. 2017;1(1):142-152. doi:10.1002/cepa.16'
apa: 'Scheideler, E., Ahlemeyer-Stubbe, A., & Scheideler, J. (2017). Statistische
Modellierung zur Unterstützung von Industrie 4.0 im Glasbau. ce/papers : Proceedings
in Civil Engineering, 1(1), 142–152. https://doi.org/10.1002/cepa.16'
bjps: 'Scheideler E, Ahlemeyer-Stubbe A and Scheideler J (2017) Statistische
Modellierung zur Unterstützung von Industrie 4.0 im Glasbau. ce/papers : Proceedings
in Civil Engineering 1, 142–152.'
chicago: 'Scheideler, Eva, Andrea Ahlemeyer-Stubbe, and Josef Scheideler. “Statistische
Modellierung zur Unterstützung von Industrie 4.0 im Glasbau.” ce/papers : Proceedings
in Civil Engineering 1, no. 1 (2017): 142–52. https://doi.org/10.1002/cepa.16.'
chicago-de: 'Scheideler, Eva, Andrea Ahlemeyer-Stubbe und Josef Scheideler. 2017.
Statistische Modellierung zur Unterstützung von Industrie 4.0 im Glasbau. ce/papers :
Proceedings in Civil Engineering 1, Nr. 1: 142–152. doi:10.1002/cepa.16,
.'
din1505-2-1: 'Scheideler, Eva ; Ahlemeyer-Stubbe, Andrea ; Scheideler,
Josef: Statistische Modellierung zur Unterstützung von Industrie 4.0 im
Glasbau. In: ce/papers : Proceedings in Civil Engineering Bd. 1, Ernst
& Sohn, a Wiley brand (2017), Nr. 1, S. 142–152'
havard: 'E. Scheideler, A. Ahlemeyer-Stubbe, J. Scheideler, Statistische Modellierung
zur Unterstützung von Industrie 4.0 im Glasbau, ce/papers : Proceedings in Civil
Engineering. 1 (2017) 142–152.'
ieee: 'E. Scheideler, A. Ahlemeyer-Stubbe, and J. Scheideler, “Statistische Modellierung
zur Unterstützung von Industrie 4.0 im Glasbau,” ce/papers : Proceedings in
Civil Engineering, vol. 1, no. 1, pp. 142–152, 2017, doi: 10.1002/cepa.16.'
mla: 'Scheideler, Eva, et al. “Statistische Modellierung zur Unterstützung von Industrie
4.0 im Glasbau.” ce/papers : Proceedings in Civil Engineering, vol. 1,
no. 1, 2017, pp. 142–52, https://doi.org/10.1002/cepa.16.'
short: 'E. Scheideler, A. Ahlemeyer-Stubbe, J. Scheideler, ce/papers : Proceedings
in Civil Engineering 1 (2017) 142–152.'
ufg: 'Scheideler, Eva/Ahlemeyer-Stubbe, Andrea/Scheideler, Josef: Statistische
Modellierung zur Unterstützung von Industrie 4.0 im Glasbau, in: ce/papers :
Proceedings in Civil Engineering 1 (2017), H. 1, S. 142–152.'
van: 'Scheideler E, Ahlemeyer-Stubbe A, Scheideler J. Statistische Modellierung
zur Unterstützung von Industrie 4.0 im Glasbau. ce/papers : Proceedings in Civil
Engineering. 2017;1(1):142–52.'
date_created: 2019-02-21T16:16:43Z
date_updated: 2024-03-22T13:09:48Z
department:
- _id: DEP1306
doi: 10.1002/cepa.16
intvolume: ' 1'
issue: '1'
language:
- iso: ger
page: 142-152
publication: 'ce/papers : Proceedings in Civil Engineering'
publication_identifier:
eissn:
- 2509-7075
publication_status: published
publisher: 'Ernst & Sohn, a Wiley brand '
status: public
title: Statistische Modellierung zur Unterstützung von Industrie 4.0 im Glasbau
type: journal_article
user_id: '83781'
volume: 1
year: '2017'
...
---
_id: '457'
abstract:
- lang: eng
text: "Additive Manufacturing (AM) increasingly enables the realization of structures,
which have a much greater freedom of design und can therefore better use nature
\ as a design ideal. Bionic design principles have already been introduced
\ into general design approaches, and several topology optimization systems
(TO) are available today to increase structural stiffness and to enable lightweight
\ design. AM and TO, used in synergy, promise completely new application
areas. However, staircase effects resulting from a layer-by-layer build process
\ and unavoidable support structures which must be mechanically removed afterwards
are disadvantageous with respect to surface texture and strength properties.\r\nThe
present article addresses the question of how far the notches resulting from
the staircase effect of Additive Manufacturing and the support structures removed
\ decrease the strength of components. Most engineers try to follow the
inner flow of forces in a part’s design by smoothening surfaces in notched areas.
Considering this, a elected component is investigated with finite element
\ analysis (FEA) with special regard for the concentration of tress arising
from surface notch effects. An outlook is given as regards how a reduction of
the notch effect from the taircase effect can be achieved effectively."
author:
- first_name: Eva
full_name: Scheideler, Eva
id: '61522'
last_name: Scheideler
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
id: '14290'
last_name: Villmer
- first_name: G.
full_name: Adam, G.
last_name: Adam
- first_name: Mirco
full_name: Timmer, Mirco
id: '69228'
last_name: Timmer
conference:
end_date: 2016-09-30
location: Lemgo
name: Proceedings 6th International Conference
start_date: 2016-09-29
corporate_editor:
- Department of Production Engineering and Management OWL University of Applied Sciences,
Lemgo (Germany)
- Hochschule Ostwestfalen-Lippe
date_created: 2019-01-22T14:07:32Z
date_updated: 2023-03-15T13:49:54Z
department:
- _id: DEP1306
editor:
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
id: '14290'
last_name: Villmer
- first_name: Elio
full_name: Padoano, Elio
last_name: Padoano
issue: '1'
keyword:
- Additive Manufacturing
- Topology optimization
- Staircase effect
- Support structures
- Stress concentration
- Lightweight construction
- Design rules
- Notch effect
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.th-owl.de/elsa/download/333/334/PEM_2016_Proceeding_2016_09_14_Inhaltsnavigation.pdf
oa: '1'
page: 39-50
place: Lemgo
publication: Production Engineering and Management Proceedings 6th International Conference
publication_identifier:
isbn:
- 978-3-946856-00-9
publication_status: published
status: public
title: Topology Optimization and Additive Manufacturing – A Perfect Symbiosis?
type: conference
user_id: '79260'
year: 2016
...
---
_id: '594'
abstract:
- lang: eng
text: Due to steadily increased demand for customized products, as well as their
enhanced complexity and shorter product lifecycles, companies in all industries
require a reliable prediction of the expected product development costs from the
very start of product realization. Incorrectly estimated project costs may lead
to serious consequences in the course of a development project. For example, offers
are most often based on such early cost estimations and consequently, a major
safety margin has to be added, which may result in the refusal of an order. A
too low estimation of the costs of aproduct development project, on the other
hand, may result in a loss for the project.In this paper, a software tool is presented
for the prediction of product development costs which offers the user the ability
to create a more accurate prediction of project costs on the basis of a minimum
of retrograde project information. By combining a parametric cost model and cost
result with stochastic character, based on the Monte Carlo method, in one software
system, it is possible to significantly improve projectcost estimations.
author:
- first_name: Andreas
full_name: Otte, Andreas
id: '51466'
last_name: Otte
- first_name: Eva
full_name: Scheideler, Eva
id: '61522'
last_name: Scheideler
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
id: '14290'
last_name: Villmer
citation:
ama: 'Otte A, Scheideler E, Villmer F-J. Project Cost Estimator - A Parameter-Based
Tool to Predict Product Realization Costs at a Very Early Stage. In: Villmer F-J,
Padoano E, Department of Production Engineering and Management, eds. Department
of Production Engineering and Management. Lemgo; 2016:281-292.'
apa: Otte, A., Scheideler, E., & Villmer, F.-J. (2016). Project Cost Estimator
- A Parameter-Based Tool to Predict Product Realization Costs at a Very Early
Stage. In F.-J. Villmer, E. Padoano, & Department of Production Engineering
and Management (Eds.), Department of Production Engineering and Management
(pp. 281–292). Lemgo.
bjps: Otte A, Scheideler E and Villmer F-J (2016) Project Cost Estimator
- A Parameter-Based Tool to Predict Product Realization Costs at a Very Early
Stage. In Villmer F-J, Padoano E and Department of Production Engineering and
Management (eds), Department of Production Engineering and Management.
Lemgo, pp. 281–292.
chicago: Otte, Andreas, Eva Scheideler, and Franz-Josef Villmer. “Project Cost Estimator
- A Parameter-Based Tool to Predict Product Realization Costs at a Very Early
Stage.” In Department of Production Engineering and Management, edited
by Franz-Josef Villmer, Elio Padoano, and Department of Production Engineering
and Management, 281–92. Lemgo, 2016.
chicago-de: 'Otte, Andreas, Eva Scheideler und Franz-Josef Villmer. 2016. Project
Cost Estimator - A Parameter-Based Tool to Predict Product Realization Costs at
a Very Early Stage. In: Department of Production Engineering and Management,
hg. von Franz-Josef Villmer, Elio Padoano, und Department of Production Engineering
and Management, 281–292. Lemgo.'
din1505-2-1: 'Otte, Andreas ; Scheideler, Eva ; Villmer,
Franz-Josef: Project Cost Estimator - A Parameter-Based Tool to Predict
Product Realization Costs at a Very Early Stage. In: Villmer,
F.-J. ; Padoano, E. ; Department of Production Engineering and Management
(Hrsg.): Department of Production Engineering and Management. Lemgo, 2016,
S. 281–292'
havard: 'A. Otte, E. Scheideler, F.-J. Villmer, Project Cost Estimator - A Parameter-Based
Tool to Predict Product Realization Costs at a Very Early Stage, in: F.-J. Villmer,
E. Padoano, Department of Production Engineering and Management (Eds.), Department
of Production Engineering and Management, Lemgo, 2016: pp. 281–292.'
ieee: A. Otte, E. Scheideler, and F.-J. Villmer, “Project Cost Estimator - A Parameter-Based
Tool to Predict Product Realization Costs at a Very Early Stage,” in Department
of Production Engineering and Management, Lemgo, 2016, no. 1, pp. 281–292.
mla: Otte, Andreas, et al. “Project Cost Estimator - A Parameter-Based Tool to Predict
Product Realization Costs at a Very Early Stage.” Department of Production
Engineering and Management, edited by Franz-Josef Villmer et al., no. 1, 2016,
pp. 281–92.
short: 'A. Otte, E. Scheideler, F.-J. Villmer, in: F.-J. Villmer, E. Padoano, Department
of Production Engineering and Management (Eds.), Department of Production Engineering
and Management, Lemgo, 2016, pp. 281–292.'
ufg: 'Otte, Andreas et. al. (2016): Project Cost Estimator - A Parameter-Based
Tool to Predict Product Realization Costs at a Very Early Stage, in: Franz-Josef
Villmer et. al. (Hgg.): Department of Production Engineering and Management,
Lemgo, S. 281–292.'
van: 'Otte A, Scheideler E, Villmer F-J. Project Cost Estimator - A Parameter-Based
Tool to Predict Product Realization Costs at a Very Early Stage. In: Villmer F-J,
Padoano E, Department of Production Engineering and Management, editors. Department
of Production Engineering and Management. Lemgo; 2016. p. 281–92.'
conference:
end_date: 2016-09-30
location: Lemgo
name: Proceedings 6th International Conference
start_date: 2016-09-29
corporate_editor:
- Department of Production Engineering and Management
- Hochschule Ostwestfalen-Lippe
date_created: 2019-02-18T15:41:41Z
date_updated: 2023-03-15T13:50:03Z
department:
- _id: DEP7000
- _id: DEP1306
editor:
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
last_name: Villmer
- first_name: Elio
full_name: Padoano, Elio
last_name: Padoano
issue: '1'
keyword:
- Cost prediction
- Product realization projects
- Monte Carlo method
- Parametric cost model
- Software tool
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2016_Proceeding_2016_09_14_Inhaltsnavigation.pdf
oa: '1'
page: 281-292
place: Lemgo
publication: Department of Production Engineering and Management
publication_identifier:
isbn:
- 978-3-946856-00-9
publication_status: published
related_material:
link:
- relation: contains
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2016_Proceeding_2016_09_14_Inhaltsnavigation.pdf
status: public
title: Project Cost Estimator - A Parameter-Based Tool to Predict Product Realization
Costs at a Very Early Stage
type: conference
user_id: '45673'
year: 2016
...
---
_id: '472'
abstract:
- lang: eng
text: "In the context of Industrie 4.0 respectively direct digital manufacturing,
seamless process chains are an important factor. The objective is to shorten the
time between quoting for individually designed products and their production and
delivery. Therefore, reliable automated and fast evaluation procedures are needed
to ensure the quality of the individually designed products in terms of product
safety and reliability. This paper aims \r\nto demonstrate how a metamodel, generated
on simulated data, adapts to the type of product and delivers the required quality
and evaluation procedure. The metamodel guarantees the requested characteristics
of the final product without the consultation of human expert knowledge. As proof
of concept, a simple, well-documented task from the field of construction has
been chosen. The estimation from of the metamodel will meet all safety requirements,
is based on the individual input variables and is confirmed without expert interaction.
Fast, reliable prediction models deriving from complex simulation models are indispensable
conditions for direct digital manufacturing. Using metamodels in automation contexts
will be a foundation of manufacturing in future."
author:
- first_name: Eva
full_name: Scheideler, Eva
id: '61522'
last_name: Scheideler
- first_name: Andrea
full_name: Ahlemeyer-Stubbe, Andrea
last_name: Ahlemeyer-Stubbe
citation:
ama: 'Scheideler E, Ahlemeyer-Stubbe A. Expert Knowledge Systems to Ensure Quality
and Reliability in Direct Digital Manufacturing Enviroments. In: Villmer FJ, Padoano
E, Department of Production Engineering and Management, Hochschule Ostwestfalen-Lippe,
eds. Production Engineering and Management : Proceedings 6th International
Conference, September 29 and 30, 2016 Lemgo, Germany . Vol 2016. Publication
series in direct digital manufacturing . Hochschule Ostwestfalen-Lippe; 2016:269-280.'
apa: 'Scheideler, E., & Ahlemeyer-Stubbe, A. (2016). Expert Knowledge Systems
to Ensure Quality and Reliability in Direct Digital Manufacturing Enviroments.
In F.-J. Villmer, E. Padoano, Department of Production Engineering and Management,
& Hochschule Ostwestfalen-Lippe (Eds.), Production engineering and management :
proceedings 6th international conference, September 29 and 30, 2016 Lemgo, Germany
(Vol. 2016, Issue 1, pp. 269–280). Hochschule Ostwestfalen-Lippe.'
bjps: 'Scheideler E and Ahlemeyer-Stubbe A (2016) Expert Knowledge Systems
to Ensure Quality and Reliability in Direct Digital Manufacturing Enviroments.
In Villmer F-J et al. (eds), Production Engineering and Management : Proceedings
6th International Conference, September 29 and 30, 2016 Lemgo, Germany , vol.
2016. Lemgo: Hochschule Ostwestfalen-Lippe, pp. 269–280.'
chicago: 'Scheideler, Eva, and Andrea Ahlemeyer-Stubbe. “Expert Knowledge Systems
to Ensure Quality and Reliability in Direct Digital Manufacturing Enviroments.”
In Production Engineering and Management : Proceedings 6th International Conference,
September 29 and 30, 2016 Lemgo, Germany , edited by Franz-Josef Villmer,
Elio Padoano, Department of Production Engineering and Management, and Hochschule
Ostwestfalen-Lippe, 2016:269–80. Publication Series in Direct Digital Manufacturing
. Lemgo: Hochschule Ostwestfalen-Lippe, 2016.'
chicago-de: 'Scheideler, Eva und Andrea Ahlemeyer-Stubbe. 2016. Expert Knowledge
Systems to Ensure Quality and Reliability in Direct Digital Manufacturing Enviroments.
In: Production engineering and management : proceedings 6th international conference,
September 29 and 30, 2016 Lemgo, Germany , hg. von Franz-Josef Villmer, Elio
Padoano, Department of Production Engineering and Management, und Hochschule Ostwestfalen-Lippe,
2016:269–280. Publication series in direct digital manufacturing . Lemgo: Hochschule
Ostwestfalen-Lippe.'
din1505-2-1: 'Scheideler, Eva ; Ahlemeyer-Stubbe, Andrea: Expert Knowledge
Systems to Ensure Quality and Reliability in Direct Digital Manufacturing Enviroments.
In: Villmer, F.-J. ; Padoano,
E. ; Department of Production Engineering
and Management ; Hochschule Ostwestfalen-Lippe
(Hrsg.): Production engineering and management : proceedings 6th international
conference, September 29 and 30, 2016 Lemgo, Germany , Publication series
in direct digital manufacturing . Bd. 2016. Lemgo : Hochschule Ostwestfalen-Lippe,
2016, S. 269–280'
havard: 'E. Scheideler, A. Ahlemeyer-Stubbe, Expert Knowledge Systems to Ensure
Quality and Reliability in Direct Digital Manufacturing Enviroments, in: F.-J.
Villmer, E. Padoano, Department of Production Engineering and Management, Hochschule
Ostwestfalen-Lippe (Eds.), Production Engineering and Management : Proceedings
6th International Conference, September 29 and 30, 2016 Lemgo, Germany , Hochschule
Ostwestfalen-Lippe, Lemgo, 2016: pp. 269–280.'
ieee: 'E. Scheideler and A. Ahlemeyer-Stubbe, “Expert Knowledge Systems to Ensure
Quality and Reliability in Direct Digital Manufacturing Enviroments,” in Production
engineering and management : proceedings 6th international conference, September
29 and 30, 2016 Lemgo, Germany , Lemgo, 2016, vol. 2016, no. 1, pp. 269–280.'
mla: 'Scheideler, Eva, and Andrea Ahlemeyer-Stubbe. “Expert Knowledge Systems to
Ensure Quality and Reliability in Direct Digital Manufacturing Enviroments.” Production
Engineering and Management : Proceedings 6th International Conference, September
29 and 30, 2016 Lemgo, Germany , edited by Franz-Josef Villmer et al., vol.
2016, no. 1, Hochschule Ostwestfalen-Lippe, 2016, pp. 269–80.'
short: 'E. Scheideler, A. Ahlemeyer-Stubbe, in: F.-J. Villmer, E. Padoano, Department
of Production Engineering and Management, Hochschule Ostwestfalen-Lippe (Eds.),
Production Engineering and Management : Proceedings 6th International Conference,
September 29 and 30, 2016 Lemgo, Germany , Hochschule Ostwestfalen-Lippe, Lemgo,
2016, pp. 269–280.'
ufg: 'Scheideler, Eva/Ahlemeyer-Stubbe, Andrea: Expert Knowledge Systems
to Ensure Quality and Reliability in Direct Digital Manufacturing Enviroments,
in: Villmer, Franz-Josef u. a. (Hgg.): Production engineering and management :
proceedings 6th international conference, September 29 and 30, 2016 Lemgo, Germany
, Bd. 2016, Lemgo 2016 ( Publication series in direct digital manufacturing ),
S. 269–280.'
van: 'Scheideler E, Ahlemeyer-Stubbe A. Expert Knowledge Systems to Ensure Quality
and Reliability in Direct Digital Manufacturing Enviroments. In: Villmer FJ, Padoano
E, Department of Production Engineering and Management, Hochschule Ostwestfalen-Lippe,
editors. Production engineering and management : proceedings 6th international
conference, September 29 and 30, 2016 Lemgo, Germany . Lemgo: Hochschule Ostwestfalen-Lippe;
2016. p. 269–80. ( Publication series in direct digital manufacturing ; vol.
2016).'
conference:
end_date: 2016-09-30
location: Lemgo
name: '6th International Conference on Production Engineering and Management '
start_date: 2016-09-29
corporate_editor:
- Department of Production Engineering and Management
- Hochschule Ostwestfalen-Lippe
date_created: 2019-01-29T13:06:45Z
date_updated: 2024-03-22T13:18:42Z
department:
- _id: DEP1306
editor:
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
last_name: Villmer
- first_name: Elio
full_name: Padoano, Elio
last_name: Padoano
intvolume: ' 2016'
issue: '1'
keyword:
- Simulation
- Metamodel
- Computer experiment
- Design of experiments
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2016_Proceeding_2016_09_14_Inhaltsnavigation.pdf
oa: '1'
page: 269-280
place: Lemgo
publication: 'Production engineering and management : proceedings 6th international
conference, September 29 and 30, 2016 Lemgo, Germany '
publication_identifier:
unknown:
- 978-3-946856-00-9
publication_status: published
publisher: Hochschule Ostwestfalen-Lippe
related_material:
link:
- relation: contains
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2016_Proceeding_2016_09_14_Inhaltsnavigation.pdf
series_title: "\t Publication series in direct digital manufacturing "
status: public
title: Expert Knowledge Systems to Ensure Quality and Reliability in Direct Digital
Manufacturing Enviroments
type: conference
user_id: '83781'
volume: 2016
year: '2016'
...
---
_id: '597'
abstract:
- lang: eng
text: "This paper is aimed to discuss current research using data mining techniques
and industry statistics in production environments. The general research approach
is based on the idea of using data mining processes and techniques of industry
statistics to find rare and hidden patterns behind failures of complex components.
A case study will be applied to illustrate how the technique is carried out and
where the limits of this approach occur. The case study deals with a component
supplier of printing machines, which received an increasing number of client complaints,
all related to one distinct problem. The observed failures seem to occur only
among clients with very high quality standards. The affected component undergoes
a very complex production process with several steps in different departments.
Every single production unit records data information from multiple process variables
and at different points in time. In the beginning there was no understanding of
the failure causes in production at all. Therefore a huge amount of production
data had to be analyzed to find the pattern that discloses the failure.\r\nThe
data mining process starts with a first step in which the given data sets are
prepared and then cleaned. Followed up by building a prediction model. The aim
is to detect the root causes for failures and to predict potential failures in
affected components. This paper shows how to use data mining to get the answer
on pressing production failures.\r\n"
author:
- first_name: Eva
full_name: Scheideler, Eva
id: '61522'
last_name: Scheideler
- first_name: Andrea
full_name: Ahlemeyer-Stubbe, Andrea
last_name: Ahlemeyer-Stubbe
citation:
ama: 'Scheideler E, Ahlemeyer-Stubbe A. Data Mining: A Potential Detector to Find
Failure in Complex Components. In: Padoano E, Villmer FJ, Department of Production
Engineering and Management, Hochschule Ostwestfalen-Lippe, eds. Production
Engineering and Management : Proceedings, 5th International Conference, October
1 and 2, 2015, Trieste, Italy. Hochschule Ostwestfalen-Lippe; 2015:163-174.'
apa: 'Scheideler, E., & Ahlemeyer-Stubbe, A. (2015). Data Mining: A Potential
Detector to Find Failure in Complex Components. In E. Padoano, F.-J. Villmer,
Department of Production Engineering and Management, & Hochschule Ostwestfalen-Lippe
(Eds.), Production engineering and management : proceedings, 5th international
conference, October 1 and 2, 2015, Trieste, Italy (Issue 1, pp. 163–174).
Hochschule Ostwestfalen-Lippe.'
bjps: 'Scheideler E and Ahlemeyer-Stubbe A (2015) Data Mining: A Potential
Detector to Find Failure in Complex Components. In Padoano E et al. (eds), Production
Engineering and Management : Proceedings, 5th International Conference, October
1 and 2, 2015, Trieste, Italy. Lemgo: Hochschule Ostwestfalen-Lippe, pp. 163–174.'
chicago: 'Scheideler, Eva, and Andrea Ahlemeyer-Stubbe. “Data Mining: A Potential
Detector to Find Failure in Complex Components.” In Production Engineering
and Management : Proceedings, 5th International Conference, October 1 and 2, 2015,
Trieste, Italy, edited by Elio Padoano, Franz-Josef Villmer, Department of
Production Engineering and Management, and Hochschule Ostwestfalen-Lippe, 163–74.
Lemgo: Hochschule Ostwestfalen-Lippe, 2015.'
chicago-de: 'Scheideler, Eva und Andrea Ahlemeyer-Stubbe. 2015. Data Mining: A Potential
Detector to Find Failure in Complex Components. In: Production engineering
and management : proceedings, 5th international conference, October 1 and 2, 2015,
Trieste, Italy, hg. von Elio Padoano, Franz-Josef Villmer, Department of Production
Engineering and Management, und Hochschule Ostwestfalen-Lippe, 163–174. Lemgo:
Hochschule Ostwestfalen-Lippe.'
din1505-2-1: 'Scheideler, Eva ; Ahlemeyer-Stubbe, Andrea: Data Mining:
A Potential Detector to Find Failure in Complex Components. In: Padoano,
E. ; Villmer, F.-J. ; Department of Production Engineering and Management
; Hochschule Ostwestfalen-Lippe
(Hrsg.): Production engineering and management : proceedings, 5th international
conference, October 1 and 2, 2015, Trieste, Italy. Lemgo : Hochschule Ostwestfalen-Lippe,
2015, S. 163–174'
havard: 'E. Scheideler, A. Ahlemeyer-Stubbe, Data Mining: A Potential Detector to
Find Failure in Complex Components, in: E. Padoano, F.-J. Villmer, Department
of Production Engineering and Management, Hochschule Ostwestfalen-Lippe (Eds.),
Production Engineering and Management : Proceedings, 5th International Conference,
October 1 and 2, 2015, Trieste, Italy, Hochschule Ostwestfalen-Lippe, Lemgo, 2015:
pp. 163–174.'
ieee: 'E. Scheideler and A. Ahlemeyer-Stubbe, “Data Mining: A Potential Detector
to Find Failure in Complex Components,” in Production engineering and management :
proceedings, 5th international conference, October 1 and 2, 2015, Trieste, Italy,
Trieste, Italy, 2015, no. 1, pp. 163–174.'
mla: 'Scheideler, Eva, and Andrea Ahlemeyer-Stubbe. “Data Mining: A Potential Detector
to Find Failure in Complex Components.” Production Engineering and Management :
Proceedings, 5th International Conference, October 1 and 2, 2015, Trieste, Italy,
edited by Elio Padoano et al., no. 1, Hochschule Ostwestfalen-Lippe, 2015, pp.
163–74.'
short: 'E. Scheideler, A. Ahlemeyer-Stubbe, in: E. Padoano, F.-J. Villmer, Department
of Production Engineering and Management, Hochschule Ostwestfalen-Lippe (Eds.),
Production Engineering and Management : Proceedings, 5th International Conference,
October 1 and 2, 2015, Trieste, Italy, Hochschule Ostwestfalen-Lippe, Lemgo, 2015,
pp. 163–174.'
ufg: 'Scheideler, Eva/Ahlemeyer-Stubbe, Andrea: Data Mining: A Potential
Detector to Find Failure in Complex Components, in: Padoano, Elio u. a. (Hgg.):
Production engineering and management : proceedings, 5th international conference,
October 1 and 2, 2015, Trieste, Italy, Lemgo 2015, S. 163–174.'
van: 'Scheideler E, Ahlemeyer-Stubbe A. Data Mining: A Potential Detector to Find
Failure in Complex Components. In: Padoano E, Villmer FJ, Department of Production
Engineering and Management, Hochschule Ostwestfalen-Lippe, editors. Production
engineering and management : proceedings, 5th international conference, October
1 and 2, 2015, Trieste, Italy. Lemgo: Hochschule Ostwestfalen-Lippe; 2015. p.
163–74.'
conference:
end_date: 2015-10-02
location: Trieste, Italy
name: '5th International Conference "Production Engineering and Management" '
start_date: 2015-10-01
corporate_editor:
- Department of Production Engineering and Management
- Hochschule Ostwestfalen-Lippe
date_created: 2019-02-19T07:15:57Z
date_updated: 2024-03-22T13:12:47Z
department:
- _id: DEP7000
- _id: DEP1306
editor:
- first_name: Elio
full_name: Padoano, Elio
last_name: Padoano
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
id: '14290'
last_name: Villmer
issue: '1'
keyword:
- Data mining
- production failure
- multi-variant analysis
- multivariate process control
- predictive modelling
- case study
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_Tagung_zusammen2015.pdf
oa: '1'
page: 163-174
place: Lemgo
publication: 'Production engineering and management : proceedings, 5th international
conference, October 1 and 2, 2015, Trieste, Italy'
publication_identifier:
isbn:
- 978-3-941645-11-0
publication_status: published
publisher: Hochschule Ostwestfalen-Lippe
related_material:
link:
- relation: contains
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_Tagung_zusammen2015.pdf
status: public
title: 'Data Mining: A Potential Detector to Find Failure in Complex Components'
type: conference
user_id: '83781'
year: '2015'
...