---
_id: '11495'
abstract:
- lang: eng
  text: 'To evaluate the suitability of an analytical instrument, essential figures
    of merit such as the limit of detection (LOD) and the limit of quantification
    (LOQ) can be employed. However, as the definitions k nown in the literature are
    mostly applicable to one signal per sample, estimating the LOD for substances
    with instruments yielding multidimensional results like electronic noses (eNoses)
    is still challenging. In this paper, we will compare and present different approaches
    to estimate the LOD for eNoses by employing commonly used multivariate data analysis
    and regression techniques, including principal component analysis (PCA), principal
    component regression (PCR), as well as partial least squares regression (PLSR).
    These methods could subsequently be used to assess the suitability of eNoses to
    help control and steer processes where volatiles are key process parameters. As
    a use case, we determined the LODs for key compounds involved in beer maturation,
    namely acetaldehyde, diacetyl, dimethyl sulfide, ethyl acetate, isobutanol, and
    2-phenylethanol, and discussed the suitability of our eNose for that dertermination
    process. The results of the methods performed demonstrated differences of up to
    a factor of eight. For diacetyl, the LOD and the LOQ were sufficiently low to
    suggest potential for monitoring via eNose. '
article_number: '3520'
article_type: original
author:
- first_name: Julia
  full_name: Kruse, Julia
  id: '82298'
  last_name: Kruse
- first_name: Julius
  full_name: Wörner, Julius
  id: '79011'
  last_name: Wörner
- first_name: Jan
  full_name: Schneider, Jan
  id: '13209'
  last_name: Schneider
  orcid: 0000-0001-6401-8873
- first_name: Helene
  full_name: Dörksen, Helene
  id: '46416'
  last_name: Dörksen
- first_name: Miriam
  full_name: Pein-Hackelbusch, Miriam
  id: '64952'
  last_name: Pein-Hackelbusch
  orcid: 0000-0002-7920-0595
citation:
  ama: Kruse J, Wörner J, Schneider J, Dörksen H, Pein-Hackelbusch M. Methods for
    Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation
    with Electronic Noses . <i>Sensors</i>. 2024;24(11). doi:<a href="https://doi.org/10.3390/s24113520">10.3390/s24113520</a>
  apa: Kruse, J., Wörner, J., Schneider, J., Dörksen, H., &#38; Pein-Hackelbusch,
    M. (2024). Methods for Estimating the Detection and Quantification Limits of Key
    Substances in Beer Maturation with Electronic Noses . <i>Sensors</i>, <i>24</i>(11),
    Article 3520. <a href="https://doi.org/10.3390/s24113520">https://doi.org/10.3390/s24113520</a>
  bjps: <b>Kruse J <i>et al.</i></b> (2024) Methods for Estimating the Detection and
    Quantification Limits of Key Substances in Beer Maturation with Electronic Noses
    . <i>Sensors</i> <b>24</b>.
  chicago: Kruse, Julia, Julius Wörner, Jan Schneider, Helene Dörksen, and Miriam
    Pein-Hackelbusch. “Methods for Estimating the Detection and Quantification Limits
    of Key Substances in Beer Maturation with Electronic Noses .” <i>Sensors</i> 24,
    no. 11 (2024). <a href="https://doi.org/10.3390/s24113520">https://doi.org/10.3390/s24113520</a>.
  chicago-de: Kruse, Julia, Julius Wörner, Jan Schneider, Helene Dörksen und Miriam
    Pein-Hackelbusch. 2024. Methods for Estimating the Detection and Quantification
    Limits of Key Substances in Beer Maturation with Electronic Noses . <i>Sensors</i>
    24, Nr. 11. doi:<a href="https://doi.org/10.3390/s24113520">10.3390/s24113520</a>,
    .
  din1505-2-1: '<span style="font-variant:small-caps;">Kruse, Julia</span> ; <span
    style="font-variant:small-caps;">Wörner, Julius</span> ; <span style="font-variant:small-caps;">Schneider,
    Jan</span> ; <span style="font-variant:small-caps;">Dörksen, Helene</span> ; <span
    style="font-variant:small-caps;">Pein-Hackelbusch, Miriam</span>: Methods for
    Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation
    with Electronic Noses . In: <i>Sensors</i> Bd. 24, MDPI (2024), Nr. 11'
  havard: J. Kruse, J. Wörner, J. Schneider, H. Dörksen, M. Pein-Hackelbusch, Methods
    for Estimating the Detection and Quantification Limits of Key Substances in Beer
    Maturation with Electronic Noses , Sensors. 24 (2024).
  ieee: 'J. Kruse, J. Wörner, J. Schneider, H. Dörksen, and M. Pein-Hackelbusch, “Methods
    for Estimating the Detection and Quantification Limits of Key Substances in Beer
    Maturation with Electronic Noses ,” <i>Sensors</i>, vol. 24, no. 11, Art. no.
    3520, 2024, doi: <a href="https://doi.org/10.3390/s24113520">10.3390/s24113520</a>.'
  mla: Kruse, Julia, et al. “Methods for Estimating the Detection and Quantification
    Limits of Key Substances in Beer Maturation with Electronic Noses .” <i>Sensors</i>,
    vol. 24, no. 11, 3520, 2024, <a href="https://doi.org/10.3390/s24113520">https://doi.org/10.3390/s24113520</a>.
  short: J. Kruse, J. Wörner, J. Schneider, H. Dörksen, M. Pein-Hackelbusch, Sensors
    24 (2024).
  ufg: '<b>Kruse, Julia u. a.</b>: Methods for Estimating the Detection and Quantification
    Limits of Key Substances in Beer Maturation with Electronic Noses , in: <i>Sensors</i>
    24 (2024), H. 11.'
  van: Kruse J, Wörner J, Schneider J, Dörksen H, Pein-Hackelbusch M. Methods for
    Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation
    with Electronic Noses . Sensors. 2024;24(11).
date_created: 2024-06-03T07:43:48Z
date_updated: 2025-06-25T13:00:14Z
department:
- _id: DEP4028
doi: 10.3390/s24113520
external_id:
  isi:
  - '001245424000001'
  pmid:
  - '38894312'
intvolume: '        24'
isi: '1'
issue: '11'
keyword:
- multidimensional sensor arrays
- MOS sensors
- beer fermentation
- process control
- gas analysis
- metal oxide semiconductors
- intentional data analysis
- chemometrics
- PLSR
- PCA
- first-order calibration
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.mdpi.com/1424-8220/24/11/3520
oa: '1'
pmid: '1'
publication: Sensors
publication_identifier:
  issn:
  - '1424-8220 '
publication_status: published
publisher: MDPI
quality_controlled: '1'
status: public
title: 'Methods for Estimating the Detection and Quantification Limits of Key Substances
  in Beer Maturation with Electronic Noses '
type: scientific_journal_article
user_id: '83781'
volume: 24
year: '2024'
...
---
_id: '8437'
abstract:
- lang: eng
  text: Low voltage direct current microgrids (DC-MG) provide a solution for increased
    efficiency by the reduction of conversion losses, total reuse of recuperation
    energy and an increased share of local power generation. Especially industrial
    applications ask for high uptimes and a stable voltage supply, which are both
    at stake in a power grid dominated by renewable generation. DC-MGs overcome these
    drawbacks by balancing energy distribution and power demand locally. For the planning
    and design of these grids a systemic approach is needed, due to the fact that
    many components are interacting. The task arises of structuring the knowledge
    available for individual technologies in an overall design framework. For this
    purpose, current state-of-the-art design processes are discussed in this article.
    These processes are mapped into the context of the requirements in an industrial
    environment. The findings are transferred to the design of industrial DC networks.
    Finally, a complete design process for DC-MGs is derived, which is proposed as
    a basis for the development of tools.
citation:
  ama: Schaab D, Spanier P, Ehlich  M, Fosselmann E, eds. <i>Design Framework for
    Multiple Infeed DC-Microgrids in Industrial Applications</i>. IEEE; 2022. doi:<a
    href="https://doi.org/10.1109/CEECT53198.2021.9672633">10.1109/CEECT53198.2021.9672633</a>
  apa: Schaab, D., Spanier, P., Ehlich , M., &#38; Fosselmann, E. (Eds.). (2022).
    <i>Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications</i>.
    IEEE. <a href="https://doi.org/10.1109/CEECT53198.2021.9672633">https://doi.org/10.1109/CEECT53198.2021.9672633</a>
  bjps: '<b>Schaab D <i>et al.</i> (eds)</b> (2022) <i>Design Framework for Multiple
    Infeed DC-Microgrids in Industrial Applications</i>. Piscataway, NJ: IEEE.'
  chicago: 'Schaab, Darian, Patrick Spanier, Martin  Ehlich , and Eric  Fosselmann,
    eds. <i>Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications</i>.
    2021 3rd International Conference on Electrical Engineering and Control Technologies
    (CEECT). Piscataway, NJ: IEEE, 2022. <a href="https://doi.org/10.1109/CEECT53198.2021.9672633">https://doi.org/10.1109/CEECT53198.2021.9672633</a>.'
  chicago-de: 'Schaab, Darian, Patrick Spanier, Martin  Ehlich  und Eric  Fosselmann,
    Hrsg. 2022. <i>Design Framework for Multiple Infeed DC-Microgrids in Industrial
    Applications</i>. 2021 3rd International Conference on Electrical Engineering
    and Control Technologies (CEECT). Piscataway, NJ: IEEE. doi:<a href="https://doi.org/10.1109/CEECT53198.2021.9672633">10.1109/CEECT53198.2021.9672633</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Schaab, D.</span> ; <span style="font-variant:small-caps;">Spanier,
    P.</span> ; <span style="font-variant:small-caps;">Ehlich , M.</span> ; <span
    style="font-variant:small-caps;">Fosselmann, E.</span> (Hrsg.): <i>Design Framework
    for Multiple Infeed DC-Microgrids in Industrial Applications</i>, <i>2021 3rd
    International Conference on Electrical Engineering and Control Technologies (CEECT)</i>.
    Piscataway, NJ : IEEE, 2022'
  havard: D. Schaab, P. Spanier, M. Ehlich , E. Fosselmann, eds., Design Framework
    for Multiple Infeed DC-Microgrids in Industrial Applications, IEEE, Piscataway,
    NJ, 2022.
  ieee: 'D. Schaab, P. Spanier, M. Ehlich , and E. Fosselmann, Eds., <i>Design Framework
    for Multiple Infeed DC-Microgrids in Industrial Applications</i>. Piscataway,
    NJ: IEEE, 2022. doi: <a href="https://doi.org/10.1109/CEECT53198.2021.9672633">10.1109/CEECT53198.2021.9672633</a>.'
  mla: Schaab, Darian, et al., editors. <i>Design Framework for Multiple Infeed DC-Microgrids
    in Industrial Applications</i>. IEEE, 2022, <a href="https://doi.org/10.1109/CEECT53198.2021.9672633">https://doi.org/10.1109/CEECT53198.2021.9672633</a>.
  short: D. Schaab, P. Spanier, M. Ehlich , E. Fosselmann, eds., Design Framework
    for Multiple Infeed DC-Microgrids in Industrial Applications, IEEE, Piscataway,
    NJ, 2022.
  ufg: '<i><i>Schaab, Darian</i> u. a.</i>: Design Framework for Multiple Infeed DC-Microgrids
    in Industrial Applications, Piscataway, NJ 2022 (2021 3rd International Conference
    on Electrical Engineering and Control Technologies (CEECT)).'
  van: 'Schaab D, Spanier P, Ehlich  M, Fosselmann E, editors. Design Framework for
    Multiple Infeed DC-Microgrids in Industrial Applications. Piscataway, NJ: IEEE;
    2022. (2021 3rd International Conference on Electrical Engineering and Control
    Technologies (CEECT)).'
conference:
  end_date: 2021-12-18
  location: ' Macau, Macao '
  name: 3rd International Conference on Electrical Engineering and Control Technologies
    (CEECT)
  start_date: 2021-12-16
date_created: 2022-07-06T08:55:01Z
date_updated: 2024-08-07T09:37:05Z
department:
- _id: DEP6020
- _id: DEP5018
doi: 10.1109/CEECT53198.2021.9672633
editor:
- first_name: Darian
  full_name: Schaab, Darian
  last_name: Schaab
- first_name: Patrick
  full_name: Spanier, Patrick
  id: '43516'
  last_name: Spanier
- first_name: 'Martin '
  full_name: 'Ehlich , Martin '
  last_name: 'Ehlich '
- first_name: 'Eric '
  full_name: 'Fosselmann, Eric '
  last_name: Fosselmann
keyword:
- Renewable energy sources
- Power demand
- Process control
- Voltage
- Robustness
- Planning
- Stakeholders
language:
- iso: eng
place: Piscataway, NJ
publication_identifier:
  eisbn:
  - 978-1-6654-4041-7
  isbn:
  - 978-1-6654-4042-4
publication_status: published
publisher: IEEE
quality_controlled: '1'
series_title: 2021 3rd International Conference on Electrical Engineering and Control
  Technologies (CEECT)
status: public
title: Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications
type: conference_editor
user_id: '83781'
year: '2022'
...
---
_id: '12789'
abstract:
- lang: eng
  text: Additive manufacturing is being increasingly focused on the production of
    end-use parts. Compared to the prototyping application, the production of end-use
    parts demands a higher level of repeatability and process quality. To achieve
    this, increased knowledge is required about the influence of various process parameters
    on the part characteristics and the parameter interrelations. Design of Experiment
    methods can be applied to gain knowledge on the process behavior, but the applicability
    of different DoE methods for AM processes has to be validated. This paper describes
    the application of a definitive screening design for the identification of influencing
    parameters in Laser Powder Bed Fusion of CoCrW alloy. The impact of various hatch
    parameters on the part porosity is analyzed. The experimental setup and results
    are described. The results are validated in an additional test series, comparing
    the part quality achieved by parameter-sets obtained by different optimization
    approaches. Furthermore, the correlation of the porosity towards mechanical properties
    is investigated. Finally, the opportunities and limitations of the method are
    discussed.
author:
- 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: Huxol A, Villmer FJ. Experimental approach towards parameter evaluation in
    laser powder bed fusion of metals. <i>International Journal of Computer Integrated
    Manufacturing</i>. 2021;35(4-5):556-567. doi:<a href="https://doi.org/10.1080/0951192x.2021.1901313">10.1080/0951192x.2021.1901313</a>
  apa: Huxol, A., &#38; Villmer, F.-J. (2021). Experimental approach towards parameter
    evaluation in laser powder bed fusion of metals. <i>International Journal of Computer
    Integrated Manufacturing</i>, <i>35</i>(4–5), 556–567. <a href="https://doi.org/10.1080/0951192x.2021.1901313">https://doi.org/10.1080/0951192x.2021.1901313</a>
  bjps: <b>Huxol A and Villmer F-J</b> (2021) Experimental Approach towards Parameter
    Evaluation in Laser Powder Bed Fusion of Metals. <i>International Journal of Computer
    Integrated Manufacturing</i> <b>35</b>, 556–567.
  chicago: 'Huxol, Andrea, and Franz-Josef Villmer. “Experimental Approach towards
    Parameter Evaluation in Laser Powder Bed Fusion of Metals.” <i>International Journal
    of Computer Integrated Manufacturing</i> 35, no. 4–5 (2021): 556–67. <a href="https://doi.org/10.1080/0951192x.2021.1901313">https://doi.org/10.1080/0951192x.2021.1901313</a>.'
  chicago-de: 'Huxol, Andrea und Franz-Josef Villmer. 2021. Experimental approach
    towards parameter evaluation in laser powder bed fusion of metals. <i>International
    Journal of Computer Integrated Manufacturing</i> 35, Nr. 4–5: 556–567. doi:<a
    href="https://doi.org/10.1080/0951192x.2021.1901313">10.1080/0951192x.2021.1901313</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Huxol, Andrea</span> ; <span
    style="font-variant:small-caps;">Villmer, Franz-Josef</span>: Experimental approach
    towards parameter evaluation in laser powder bed fusion of metals. In: <i>International
    Journal of Computer Integrated Manufacturing</i> Bd. 35. London [u.a.], Taylor
    &#38; Francis (2021), Nr. 4–5, S. 556–567'
  havard: A. Huxol, F.-J. Villmer, Experimental approach towards parameter evaluation
    in laser powder bed fusion of metals, International Journal of Computer Integrated
    Manufacturing. 35 (2021) 556–567.
  ieee: 'A. Huxol and F.-J. Villmer, “Experimental approach towards parameter evaluation
    in laser powder bed fusion of metals,” <i>International Journal of Computer Integrated
    Manufacturing</i>, vol. 35, no. 4–5, pp. 556–567, 2021, doi: <a href="https://doi.org/10.1080/0951192x.2021.1901313">10.1080/0951192x.2021.1901313</a>.'
  mla: Huxol, Andrea, and Franz-Josef Villmer. “Experimental Approach towards Parameter
    Evaluation in Laser Powder Bed Fusion of Metals.” <i>International Journal of
    Computer Integrated Manufacturing</i>, vol. 35, no. 4–5, 2021, pp. 556–67, <a
    href="https://doi.org/10.1080/0951192x.2021.1901313">https://doi.org/10.1080/0951192x.2021.1901313</a>.
  short: A. Huxol, F.-J. Villmer, International Journal of Computer Integrated Manufacturing
    35 (2021) 556–567.
  ufg: '<b>Huxol, Andrea/Villmer, Franz-Josef</b>: Experimental approach towards parameter
    evaluation in laser powder bed fusion of metals, in: <i>International Journal
    of Computer Integrated Manufacturing</i> 35 (2021), H. 4–5,  S. 556–567.'
  van: Huxol A, Villmer FJ. Experimental approach towards parameter evaluation in
    laser powder bed fusion of metals. International Journal of Computer Integrated
    Manufacturing. 2021;35(4–5):556–67.
date_created: 2025-04-15T08:18:06Z
date_updated: 2025-06-26T07:56:42Z
department:
- _id: DEP7000
doi: 10.1080/0951192x.2021.1901313
external_id:
  isi:
  - '000630944800001'
intvolume: '        35'
isi: '1'
issue: 4-5
keyword:
- Additive manufacturing
- quality control
- process qualification
- process control
- screening design
language:
- iso: eng
page: 556-567
place: London [u.a.]
publication: International Journal of Computer Integrated Manufacturing
publication_identifier:
  eissn:
  - 1362-3052
  issn:
  - 0951-192X
publication_status: published
publisher: Taylor & Francis
status: public
title: Experimental approach towards parameter evaluation in laser powder bed fusion
  of metals
type: scientific_journal_article
user_id: '83781'
volume: 35
year: '2021'
...
---
_id: '12790'
abstract:
- lang: eng
  text: n the last years, Additive Manufacturing, thanks to its capability of continuous
    improvements in performance and cost-efficiency, was able to partly replace and
    redefine well-established manufacturing processes. This research is based on the
    idea to achieve great cost and operational benefits especially in the field of
    tool making for injection molding by combining traditional and additive manufacturing
    in one process chain. Special attention is given to the surface quality in terms
    of surface roughness and its optimization directly in the Selective Laser Melting
    process. This article presents the possibility for a remelting process of the
    SLM parts as a way to optimize the surfaces of the produced parts. The influence
    of laser remelting on the surface roughness of the parts is analyzed while varying
    machine parameters like laser power and scan settings. Laser remelting with optimized
    parameter settings considerably improves the surface quality of SLM parts and
    is a great starting point for further post-processing techniques, which require
    a low initial value of surface roughness.
author:
- first_name: Filippo
  full_name: Simoni, Filippo
  last_name: Simoni
- 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: Simoni F, Huxol A, Villmer FJ. Improving surface quality in selective laser
    melting based tool making. <i>Journal of Intelligent Manufacturing</i>. 2021;32(7):1927-1938.
    doi:<a href="https://doi.org/10.1007/s10845-021-01744-9">10.1007/s10845-021-01744-9</a>
  apa: Simoni, F., Huxol, A., &#38; Villmer, F.-J. (2021). Improving surface quality
    in selective laser melting based tool making. <i>Journal of Intelligent Manufacturing</i>,
    <i>32</i>(7), 1927–1938. <a href="https://doi.org/10.1007/s10845-021-01744-9">https://doi.org/10.1007/s10845-021-01744-9</a>
  bjps: <b>Simoni F, Huxol A and Villmer F-J</b> (2021) Improving Surface Quality
    in Selective Laser Melting Based Tool Making. <i>Journal of Intelligent Manufacturing</i>
    <b>32</b>, 1927–1938.
  chicago: 'Simoni, Filippo, Andrea Huxol, and Franz-Josef Villmer. “Improving Surface
    Quality in Selective Laser Melting Based Tool Making.” <i>Journal of Intelligent
    Manufacturing</i> 32, no. 7 (2021): 1927–38. <a href="https://doi.org/10.1007/s10845-021-01744-9">https://doi.org/10.1007/s10845-021-01744-9</a>.'
  chicago-de: 'Simoni, Filippo, Andrea Huxol und Franz-Josef Villmer. 2021. Improving
    surface quality in selective laser melting based tool making. <i>Journal of Intelligent
    Manufacturing</i> 32, Nr. 7: 1927–1938. doi:<a href="https://doi.org/10.1007/s10845-021-01744-9">10.1007/s10845-021-01744-9</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Simoni, Filippo</span> ; <span
    style="font-variant:small-caps;">Huxol, Andrea</span> ; <span style="font-variant:small-caps;">Villmer,
    Franz-Josef</span>: Improving surface quality in selective laser melting based
    tool making. In: <i>Journal of Intelligent Manufacturing</i> Bd. 32. Dordrecht
    [u.a.], Springer Science and Business Media (2021), Nr. 7, S. 1927–1938'
  havard: F. Simoni, A. Huxol, F.-J. Villmer, Improving surface quality in selective
    laser melting based tool making, Journal of Intelligent Manufacturing. 32 (2021)
    1927–1938.
  ieee: 'F. Simoni, A. Huxol, and F.-J. Villmer, “Improving surface quality in selective
    laser melting based tool making,” <i>Journal of Intelligent Manufacturing</i>,
    vol. 32, no. 7, pp. 1927–1938, 2021, doi: <a href="https://doi.org/10.1007/s10845-021-01744-9">10.1007/s10845-021-01744-9</a>.'
  mla: Simoni, Filippo, et al. “Improving Surface Quality in Selective Laser Melting
    Based Tool Making.” <i>Journal of Intelligent Manufacturing</i>, vol. 32, no.
    7, 2021, pp. 1927–38, <a href="https://doi.org/10.1007/s10845-021-01744-9">https://doi.org/10.1007/s10845-021-01744-9</a>.
  short: F. Simoni, A. Huxol, F.-J. Villmer, Journal of Intelligent Manufacturing
    32 (2021) 1927–1938.
  ufg: '<b>Simoni, Filippo/Huxol, Andrea/Villmer, Franz-Josef</b>: Improving surface
    quality in selective laser melting based tool making, in: <i>Journal of Intelligent
    Manufacturing</i> 32 (2021), H. 7,  S. 1927–1938.'
  van: Simoni F, Huxol A, Villmer FJ. Improving surface quality in selective laser
    melting based tool making. Journal of Intelligent Manufacturing. 2021;32(7):1927–38.
date_created: 2025-04-15T09:17:22Z
date_updated: 2025-06-26T13:41:37Z
department:
- _id: DEP7000
doi: 10.1007/s10845-021-01744-9
external_id:
  isi:
  - '000636136100001'
intvolume: '        32'
isi: '1'
issue: '7'
keyword:
- Direct rapid tooling
- Toolmaking
- Additive manufacturing process chain
- Process control
- Production systems
- Selective laser melting
- Surface roughness
- Laser surface remelting
language:
- iso: eng
page: 1927-1938
place: Dordrecht [u.a.]
publication: Journal of Intelligent Manufacturing
publication_identifier:
  eissn:
  - 1572-8145
  issn:
  - 0956-5515
publication_status: published
publisher: Springer Science and Business Media
status: public
title: Improving surface quality in selective laser melting based tool making
type: scientific_journal_article
user_id: '83781'
volume: 32
year: '2021'
...
---
_id: '12791'
abstract:
- lang: eng
  text: Additive manufacturing is being increasingly focused on the production of
    end-use parts. Compared to the prototyping application, the production of end-use
    parts demands a higher level of repeatability and process quality. To achieve
    this, increased knowledge is required about the influence of various process parameters
    on the part characteristics and the parameter interrelations. Design of Experiment
    methods can be applied to gain knowledge on the process behavior, but the applicability
    of different DoE methods for AM processes has to be validated. This paper describes
    the application of a definitive screening design for the identification of influencing
    parameters in Selective Laser Melting. The experimental setup and results are
    described and opportunities and limitations of the method are discussed. (C) 2019,
    IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd.
    All rights reserved.
author:
- 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: Huxol A, Villmer FJ. <i>DoE Methods for Parameter Evaluation in Selective Laser
    Melting</i>. Vol 52. Elsevier BV; 2019:270-275. doi:<a href="https://doi.org/10.1016/j.ifacol.2019.10.041">10.1016/j.ifacol.2019.10.041</a>
  apa: Huxol, A., &#38; Villmer, F.-J. (2019). DoE Methods for Parameter Evaluation
    in Selective Laser Melting. In <i>13th International-Federation-of-Automatic-Control
    (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i> (Vol. 52, pp. 270–275).
    Elsevier BV. <a href="https://doi.org/10.1016/j.ifacol.2019.10.041">https://doi.org/10.1016/j.ifacol.2019.10.041</a>
  bjps: '<b>Huxol A and Villmer F-J</b> (2019) <i>DoE Methods for Parameter Evaluation
    in Selective Laser Melting</i>. Amsterdam [u.a.]: Elsevier BV.'
  chicago: 'Huxol, Andrea, and Franz-Josef Villmer. <i>DoE Methods for Parameter Evaluation
    in Selective Laser Melting</i>. <i>13th International-Federation-of-Automatic-Control
    (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i>. Vol. 52. IFAC-PapersOnLine.
    Amsterdam [u.a.]: Elsevier BV, 2019. <a href="https://doi.org/10.1016/j.ifacol.2019.10.041">https://doi.org/10.1016/j.ifacol.2019.10.041</a>.'
  chicago-de: 'Huxol, Andrea und Franz-Josef Villmer. 2019. <i>DoE Methods for Parameter
    Evaluation in Selective Laser Melting</i>. <i>13th International-Federation-of-Automatic-Control
    (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i>. Bd. 52. IFAC-PapersOnLine.
    Amsterdam [u.a.]: Elsevier BV. doi:<a href="https://doi.org/10.1016/j.ifacol.2019.10.041">10.1016/j.ifacol.2019.10.041</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Huxol, Andrea</span> ; <span
    style="font-variant:small-caps;">Villmer, Franz-Josef</span>: <i>DoE Methods for
    Parameter Evaluation in Selective Laser Melting</i>, <i>IFAC-PapersOnLine</i>.
    Bd. 52. Amsterdam [u.a.] : Elsevier BV, 2019'
  havard: A. Huxol, F.-J. Villmer, DoE Methods for Parameter Evaluation in Selective
    Laser Melting, Elsevier BV, Amsterdam [u.a.], 2019.
  ieee: 'A. Huxol and F.-J. Villmer, <i>DoE Methods for Parameter Evaluation in Selective
    Laser Melting</i>, vol. 52. Amsterdam [u.a.]: Elsevier BV, 2019, pp. 270–275.
    doi: <a href="https://doi.org/10.1016/j.ifacol.2019.10.041">10.1016/j.ifacol.2019.10.041</a>.'
  mla: Huxol, Andrea, and Franz-Josef Villmer. “DoE Methods for Parameter Evaluation
    in Selective Laser Melting.” <i>13th International-Federation-of-Automatic-Control
    (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i>, vol. 52, Elsevier
    BV, 2019, pp. 270–75, <a href="https://doi.org/10.1016/j.ifacol.2019.10.041">https://doi.org/10.1016/j.ifacol.2019.10.041</a>.
  short: A. Huxol, F.-J. Villmer, DoE Methods for Parameter Evaluation in Selective
    Laser Melting, Elsevier BV, Amsterdam [u.a.], 2019.
  ufg: '<b>Huxol, Andrea/Villmer, Franz-Josef</b>: DoE Methods for Parameter Evaluation
    in Selective Laser Melting, Bd. 52, Amsterdam [u.a.] 2019 (IFAC-PapersOnLine).'
  van: 'Huxol A, Villmer FJ. DoE Methods for Parameter Evaluation in Selective Laser
    Melting. 13th International-Federation-of-Automatic-Control (IFAC) Workshop on
    Intelligent Manufacturing Systems (IMS). Amsterdam [u.a.]: Elsevier BV; 2019.
    (IFAC-PapersOnLine; vol. 52).'
conference:
  end_date: 2019-08-14
  location: Oshawa, CANADA
  name: 13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent
    Manufacturing Systems (IMS)
  start_date: 2019-08-12
date_created: 2025-04-15T09:27:00Z
date_updated: 2025-06-26T13:40:48Z
department:
- _id: DEP7000
doi: 10.1016/j.ifacol.2019.10.041
intvolume: '        52'
keyword:
- Additive manufacturing
- quality control
- process qualification
- process control
- screening design
language:
- iso: eng
page: 270-275
place: Amsterdam [u.a.]
publication: 13th International-Federation-of-Automatic-Control (IFAC) Workshop on
  Intelligent Manufacturing Systems (IMS)
publication_identifier:
  issn:
  - 2405-8963
publication_status: published
publisher: Elsevier BV
series_title: IFAC-PapersOnLine
status: public
title: DoE Methods for Parameter Evaluation in Selective Laser Melting
type: conference_editor_article
user_id: '83781'
volume: 52
year: '2019'
...
---
_id: '12792'
abstract:
- lang: eng
  text: Additive Manufacturing has arisen as a ground-breaking set of technologies
    that, thanks to their capability of continuous improvements in performance and
    cost-efficiency, was able in the last years to replace well-established manufacturing
    processes. Proficiency in the fabrication of highly complex parts forced this
    astonishing development. This research is based on the idea that through the integration
    of additive and conventional manufacturing technologies it is possible to achieve
    great cost and operational benefits especially in the field of tool making for
    injection molding. Such an integrated manufacturing solution could overcome the
    limitations of independent additive, subtractive, and post-processing procedures
    by strengthening their potentialities. The present study highlights the opportunities
    of a synergy between the above-mentioned manufacturing technologies for the optimized
    fabrication of injection molds. An additive manufacturing process chain is presented,
    and special attention is given to the surface quality and its optimization directly
    in the Selective Laser Melting process. The potentialities of the Laser Surface
    Re-melting technique are analyzed, and the process optimization leads to a reduction
    of 45% of the average roughness directly in the SLM process. (C) 2019, IFAC (International
    Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
author:
- first_name: Filippo
  full_name: Simoni, Filippo
  last_name: Simoni
- 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: Simoni F, Huxol A, Villmer FJ. <i>Approach Towards Surface Improvement in Additively
    Manufactured Tools</i>. Vol 52. Elsevier BV; 2019:254-259. doi:<a href="https://doi.org/10.1016/j.ifacol.2019.10.032">10.1016/j.ifacol.2019.10.032</a>
  apa: Simoni, F., Huxol, A., &#38; Villmer, F.-J. (2019). Approach Towards Surface
    Improvement in Additively Manufactured Tools. In <i>13th International-Federation-of-Automatic-Control
    (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i> (Vol. 52, pp. 254–259).
    Elsevier BV. <a href="https://doi.org/10.1016/j.ifacol.2019.10.032">https://doi.org/10.1016/j.ifacol.2019.10.032</a>
  bjps: '<b>Simoni F, Huxol A and Villmer F-J</b> (2019) <i>Approach Towards Surface
    Improvement in Additively Manufactured Tools</i>. Amsterdam [u.a.]: Elsevier BV.'
  chicago: 'Simoni, Filippo, Andrea Huxol, and Franz-Josef Villmer. <i>Approach Towards
    Surface Improvement in Additively Manufactured Tools</i>. <i>13th International-Federation-of-Automatic-Control
    (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i>. Vol. 52. IFAC-PapersOnLine.
    Amsterdam [u.a.]: Elsevier BV, 2019. <a href="https://doi.org/10.1016/j.ifacol.2019.10.032">https://doi.org/10.1016/j.ifacol.2019.10.032</a>.'
  chicago-de: 'Simoni, Filippo, Andrea Huxol und Franz-Josef Villmer. 2019. <i>Approach
    Towards Surface Improvement in Additively Manufactured Tools</i>. <i>13th International-Federation-of-Automatic-Control
    (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i>. Bd. 52. IFAC-PapersOnLine.
    Amsterdam [u.a.]: Elsevier BV. doi:<a href="https://doi.org/10.1016/j.ifacol.2019.10.032">10.1016/j.ifacol.2019.10.032</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Simoni, Filippo</span> ; <span
    style="font-variant:small-caps;">Huxol, Andrea</span> ; <span style="font-variant:small-caps;">Villmer,
    Franz-Josef</span>: <i>Approach Towards Surface Improvement in Additively Manufactured
    Tools</i>, <i>IFAC-PapersOnLine</i>. Bd. 52. Amsterdam [u.a.] : Elsevier BV, 2019'
  havard: F. Simoni, A. Huxol, F.-J. Villmer, Approach Towards Surface Improvement
    in Additively Manufactured Tools, Elsevier BV, Amsterdam [u.a.], 2019.
  ieee: 'F. Simoni, A. Huxol, and F.-J. Villmer, <i>Approach Towards Surface Improvement
    in Additively Manufactured Tools</i>, vol. 52. Amsterdam [u.a.]: Elsevier BV,
    2019, pp. 254–259. doi: <a href="https://doi.org/10.1016/j.ifacol.2019.10.032">10.1016/j.ifacol.2019.10.032</a>.'
  mla: Simoni, Filippo, et al. “Approach Towards Surface Improvement in Additively
    Manufactured Tools.” <i>13th International-Federation-of-Automatic-Control (IFAC)
    Workshop on Intelligent Manufacturing Systems (IMS)</i>, vol. 52, Elsevier BV,
    2019, pp. 254–59, <a href="https://doi.org/10.1016/j.ifacol.2019.10.032">https://doi.org/10.1016/j.ifacol.2019.10.032</a>.
  short: F. Simoni, A. Huxol, F.-J. Villmer, Approach Towards Surface Improvement
    in Additively Manufactured Tools, Elsevier BV, Amsterdam [u.a.], 2019.
  ufg: '<b>Simoni, Filippo/Huxol, Andrea/Villmer, Franz-Josef</b>: Approach Towards
    Surface Improvement in Additively Manufactured Tools, Bd. 52, Amsterdam [u.a.]
    2019 (IFAC-PapersOnLine).'
  van: 'Simoni F, Huxol A, Villmer FJ. Approach Towards Surface Improvement in Additively
    Manufactured Tools. 13th International-Federation-of-Automatic-Control (IFAC)
    Workshop on Intelligent Manufacturing Systems (IMS). Amsterdam [u.a.]: Elsevier
    BV; 2019. (IFAC-PapersOnLine; vol. 52).'
conference:
  end_date: 2019-08-14
  location: Oshawa, CANADA
  name: 13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent
    Manufacturing Systems (IMS)
  start_date: 2019-08-12
date_created: 2025-04-15T09:32:02Z
date_updated: 2025-06-26T13:40:36Z
department:
- _id: DEP7000
doi: 10.1016/j.ifacol.2019.10.032
intvolume: '        52'
keyword:
- Direct rapid tooling
- toolmaking
- additive manufacturing process chain
- process control
- production systems
- selective laser melting
- surface roughness
- laser surface re-melting
language:
- iso: eng
page: 254-259
place: Amsterdam [u.a.]
publication: 13th International-Federation-of-Automatic-Control (IFAC) Workshop on
  Intelligent Manufacturing Systems (IMS)
publication_identifier:
  issn:
  - 2405-8963
publication_status: published
publisher: Elsevier BV
series_title: IFAC-PapersOnLine
status: public
title: Approach Towards Surface Improvement in Additively Manufactured Tools
type: conference_editor_article
user_id: '83781'
volume: 52
year: '2019'
...
---
_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. <i>Production Engineering and Management</i>.
    Publication series in direct digital manufacturing . Lemgo; 2017:63-74.'
  apa: Huxol, A., Davis, A., Villmer, F.-J., &#38; Scheideler, E. (2017). Deployment
    of Process Capability Analysis for Single-Part Production. In E. Padoano, F.-J.
    Villmer, &#38; Department of Production Engineering and Management (Eds.), <i>Production
    Engineering and Management</i> (pp. 63–74). Lemgo.
  bjps: <b>Huxol A <i>et al.</i></b> (2017) Deployment of Process Capability Analysis
    for Single-Part Production. In Padoano E, Villmer F-J and Department of Production
    Engineering and Management (eds), <i>Production Engineering and Management</i>.
    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 <i>Production Engineering
    and Management</i>, 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:
    <i>Production Engineering and Management</i>, 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: '<span style="font-variant:small-caps;">Huxol, Andrea</span> ; <span
    style="font-variant:small-caps;">Davis, Andrea</span> ; <span style="font-variant:small-caps;">Villmer,
    Franz-Josef</span> ; <span style="font-variant:small-caps;">Scheideler, Eva</span>:
    Deployment of Process Capability Analysis for Single-Part Production. In: <span
    style="font-variant:small-caps;">Padoano, E.</span> ; <span style="font-variant:small-caps;">Villmer,
    F.-J.</span> ; <span style="font-variant:small-caps;">Department of Production
    Engineering and Management</span> (Hrsg.): <i>Production Engineering and Management</i>,
    <i>Publication series in direct digital manufacturing </i>. 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 <i>Production Engineering
    and Management</i>, Pordenone, Italy, 2017, no. 1, pp. 63–74.
  mla: Huxol, Andrea, et al. “Deployment of Process Capability Analysis for Single-Part
    Production.” <i>Production Engineering and Management</i>, 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: '<b>Huxol, Andrea et. al. (2017)</b>: Deployment of Process Capability Analysis
    for Single-Part Production, in: Elio Padoano et. al. (Hgg.): <i>Production Engineering
    and Management</i> (=<i>Publication series in direct digital manufacturing </i>),
    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: '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. <i> 
    Production Engineering and Management : Proceedings 7th International Conference,
    September 28 and 29, 2017, Pordenone, Italy </i>. Vol 2017.   Publication series
    in direct digital manufacturing . ; 2017:3-12.'
  apa: 'Scheideler, E., &#38; 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, &#38; Hochschule Ostwestfalen-Lippe
    (Eds.), <i>  Production engineering and management : proceedings 7th international
    conference, September 28 and 29, 2017, Pordenone, Italy </i> (Vol. 2017, Issue
    1, pp. 3–12).'
  bjps: '<b>Scheideler E and Ahlemeyer-Stubbe A</b> (2017) Quality Control of Additive
    Manufacturing Using Statistical Prediction Models. In Padoano E et al. (eds),
    <i>  Production Engineering and Management : Proceedings 7th International Conference,
    September 28 and 29, 2017, Pordenone, Italy </i>, vol. 2017. Lemgo, pp. 3–12.'
  chicago: 'Scheideler, Eva, and Andrea Ahlemeyer-Stubbe. “Quality Control of Additive
    Manufacturing Using Statistical Prediction Models.” In <i>  Production Engineering
    and Management : Proceedings 7th International Conference, September 28 and 29,
    2017, Pordenone, Italy </i>, 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: <i>  Production
    engineering and management : proceedings 7th international conference, September
    28 and 29, 2017, Pordenone, Italy </i>, 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: '<span style="font-variant:small-caps;">Scheideler, Eva</span> ; <span
    style="font-variant:small-caps;">Ahlemeyer-Stubbe, Andrea</span>: Quality Control
    of Additive Manufacturing Using Statistical Prediction Models. In: <span style="font-variant:small-caps;">Padoano,
    E.</span> ; <span style="font-variant:small-caps;">Villmer, F.-J.</span> ; <span
    style="font-variant:small-caps;">Department of Production Engineering and Management</span>
    ; <span style="font-variant:small-caps;">Hochschule Ostwestfalen-Lippe</span>
    (Hrsg.): <i>  Production engineering and management : proceedings 7th international
    conference, September 28 and 29, 2017, Pordenone, Italy </i>, <i>  Publication
    series in direct digital manufacturing </i>. 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 <i>  Production engineering and management :
    proceedings 7th international conference, September 28 and 29, 2017, Pordenone,
    Italy </i>, 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.” <i>  Production Engineering
    and Management : Proceedings 7th International Conference, September 28 and 29,
    2017, Pordenone, Italy </i>, 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: '<b>Scheideler, Eva/Ahlemeyer-Stubbe, Andrea</b>: Quality Control of Additive
    Manufacturing Using Statistical Prediction Models, in: <i>Padoano, Elio u. a.
    (Hgg.)</i>:   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: '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. <i>Production
    Engineering and Management : Proceedings, 5th International Conference, October
    1 and 2, 2015, Trieste, Italy</i>. Hochschule Ostwestfalen-Lippe; 2015:163-174.'
  apa: 'Scheideler, E., &#38; 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, &#38; Hochschule Ostwestfalen-Lippe
    (Eds.), <i>Production engineering and management : proceedings, 5th international
    conference, October 1 and 2, 2015, Trieste, Italy</i> (Issue 1, pp. 163–174).
    Hochschule Ostwestfalen-Lippe.'
  bjps: '<b>Scheideler E and Ahlemeyer-Stubbe A</b> (2015) Data Mining: A Potential
    Detector to Find Failure in Complex Components. In Padoano E et al. (eds), <i>Production
    Engineering and Management : Proceedings, 5th International Conference, October
    1 and 2, 2015, Trieste, Italy</i>. 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 <i>Production Engineering
    and Management : Proceedings, 5th International Conference, October 1 and 2, 2015,
    Trieste, Italy</i>, 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: <i>Production engineering
    and management : proceedings, 5th international conference, October 1 and 2, 2015,
    Trieste, Italy</i>, 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: '<span style="font-variant:small-caps;">Scheideler, Eva</span> ; <span
    style="font-variant:small-caps;">Ahlemeyer-Stubbe, Andrea</span>: Data Mining:
    A Potential Detector to Find Failure in Complex Components. In: <span style="font-variant:small-caps;">Padoano,
    E.</span> ; <span style="font-variant:small-caps;">Villmer, F.-J.</span> ; <span
    style="font-variant:small-caps;">Department of Production Engineering and Management</span>
    ; <span style="font-variant:small-caps;">Hochschule Ostwestfalen-Lippe</span>
    (Hrsg.): <i>Production engineering and management : proceedings, 5th international
    conference, October 1 and 2, 2015, Trieste, Italy</i>. 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 <i>Production engineering and management :
    proceedings, 5th international conference, October 1 and 2, 2015, Trieste, Italy</i>,
    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.” <i>Production Engineering and Management :
    Proceedings, 5th International Conference, October 1 and 2, 2015, Trieste, Italy</i>,
    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: '<b>Scheideler, Eva/Ahlemeyer-Stubbe, Andrea</b>: Data Mining: A Potential
    Detector to Find Failure in Complex Components, in: <i>Padoano, Elio u. a. (Hgg.)</i>:
    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'
...