A design of experiments based on the Normal‐boundary‐intersection method to identify optimum machine settings in manufacturing processes

Finding the appropriate machine settings for a given manufacturing process is an important issue in industrial production. A set of minimum and maximum machine settings correspond to the lower and upper quality limits that are specified for the produced product, and by this define the boundaries of...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Proceedings in applied mathematics and mechanics 2023-11, Vol.23 (3), p.n/a
Hauptverfasser: Gellerich, Peter Anton, Majschak, Jens‐Peter
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page n/a
container_issue 3
container_start_page
container_title Proceedings in applied mathematics and mechanics
container_volume 23
creator Gellerich, Peter Anton
Majschak, Jens‐Peter
description Finding the appropriate machine settings for a given manufacturing process is an important issue in industrial production. A set of minimum and maximum machine settings correspond to the lower and upper quality limits that are specified for the produced product, and by this define the boundaries of all appropriate machine settings. This paper shows that these boundaries are the solution of a multi‐objective optimisation problem, which is called the optimum machine settings problem. However, for most processes there is no mathematical model of the manufacturing process available, which maps the setting parameters on the quality key figures in a way that allows to compute the optimisation problem. In this case, experiments may provide the required empirical data simultaneously while executing the optimisation procedure. Using a case study on heat sealing in industrial packaging, the paper shows, how to develop a design of experiments based on the Normal‐boundary‐intersection method (NBI), and how to generate the Pareto‐frontier by executing test according to this test plan. It addresses the specific limitations inherent in solving an optimisation problem by experiments. The behaviour of the method towards discrete and binary objectives and constraints is discussed.
doi_str_mv 10.1002/pamm.202300009
format Article
fullrecord <record><control><sourceid>wiley_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1002_pamm_202300009</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>PAMM202300009</sourcerecordid><originalsourceid>FETCH-LOGICAL-c1299-5af8c35ad698434da8b2349cfdf79adb7b1e5d34d1c0b35981a7a20f65e039653</originalsourceid><addsrcrecordid>eNqFkD1OAzEQhS0EEiHQUvsCG-x19sdlFPEnJUAB9cprjxOj2F6tvYJ0HICCM3ISHAUBHdPMaOZ7I72H0DklE0pIftEJayc5yRlJxQ_QiJa0yipS0sM_8zE6CeE58bRkZITeZ1hBMCuHvcbw2kFvLLgYcCsCKOwdjmvAd763YvP59tH6wSnRb9NoXIQ-gIwmQRbi2iscPTYqyY3eYt9FYweLrZBr4wAHiNG4VcAm4cINWsg49GmDu95LCAHCKTrSYhPg7LuP0dPV5eP8JlvcX9_OZ4tM0pzzrBC6lqwQquT1lE2VqNucTbnUSldcqLZqKRQqHagkLSt4TUUlcqLLAgjjZcHGaLL_K3sfQg-66ZLtZKuhpNll2eyybH6yTAK-F7yYDWz_oZuH2XL5q_0CF4B_AA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>A design of experiments based on the Normal‐boundary‐intersection method to identify optimum machine settings in manufacturing processes</title><source>Wiley Online Library Journals Frontfile Complete</source><creator>Gellerich, Peter Anton ; Majschak, Jens‐Peter</creator><creatorcontrib>Gellerich, Peter Anton ; Majschak, Jens‐Peter</creatorcontrib><description>Finding the appropriate machine settings for a given manufacturing process is an important issue in industrial production. A set of minimum and maximum machine settings correspond to the lower and upper quality limits that are specified for the produced product, and by this define the boundaries of all appropriate machine settings. This paper shows that these boundaries are the solution of a multi‐objective optimisation problem, which is called the optimum machine settings problem. However, for most processes there is no mathematical model of the manufacturing process available, which maps the setting parameters on the quality key figures in a way that allows to compute the optimisation problem. In this case, experiments may provide the required empirical data simultaneously while executing the optimisation procedure. Using a case study on heat sealing in industrial packaging, the paper shows, how to develop a design of experiments based on the Normal‐boundary‐intersection method (NBI), and how to generate the Pareto‐frontier by executing test according to this test plan. It addresses the specific limitations inherent in solving an optimisation problem by experiments. The behaviour of the method towards discrete and binary objectives and constraints is discussed.</description><identifier>ISSN: 1617-7061</identifier><identifier>EISSN: 1617-7061</identifier><identifier>DOI: 10.1002/pamm.202300009</identifier><language>eng</language><ispartof>Proceedings in applied mathematics and mechanics, 2023-11, Vol.23 (3), p.n/a</ispartof><rights>2023 The Authors. published by Wiley‐VCH GmbH.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c1299-5af8c35ad698434da8b2349cfdf79adb7b1e5d34d1c0b35981a7a20f65e039653</cites><orcidid>0000-0002-4771-0582</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fpamm.202300009$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fpamm.202300009$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Gellerich, Peter Anton</creatorcontrib><creatorcontrib>Majschak, Jens‐Peter</creatorcontrib><title>A design of experiments based on the Normal‐boundary‐intersection method to identify optimum machine settings in manufacturing processes</title><title>Proceedings in applied mathematics and mechanics</title><description>Finding the appropriate machine settings for a given manufacturing process is an important issue in industrial production. A set of minimum and maximum machine settings correspond to the lower and upper quality limits that are specified for the produced product, and by this define the boundaries of all appropriate machine settings. This paper shows that these boundaries are the solution of a multi‐objective optimisation problem, which is called the optimum machine settings problem. However, for most processes there is no mathematical model of the manufacturing process available, which maps the setting parameters on the quality key figures in a way that allows to compute the optimisation problem. In this case, experiments may provide the required empirical data simultaneously while executing the optimisation procedure. Using a case study on heat sealing in industrial packaging, the paper shows, how to develop a design of experiments based on the Normal‐boundary‐intersection method (NBI), and how to generate the Pareto‐frontier by executing test according to this test plan. It addresses the specific limitations inherent in solving an optimisation problem by experiments. The behaviour of the method towards discrete and binary objectives and constraints is discussed.</description><issn>1617-7061</issn><issn>1617-7061</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNqFkD1OAzEQhS0EEiHQUvsCG-x19sdlFPEnJUAB9cprjxOj2F6tvYJ0HICCM3ISHAUBHdPMaOZ7I72H0DklE0pIftEJayc5yRlJxQ_QiJa0yipS0sM_8zE6CeE58bRkZITeZ1hBMCuHvcbw2kFvLLgYcCsCKOwdjmvAd763YvP59tH6wSnRb9NoXIQ-gIwmQRbi2iscPTYqyY3eYt9FYweLrZBr4wAHiNG4VcAm4cINWsg49GmDu95LCAHCKTrSYhPg7LuP0dPV5eP8JlvcX9_OZ4tM0pzzrBC6lqwQquT1lE2VqNucTbnUSldcqLZqKRQqHagkLSt4TUUlcqLLAgjjZcHGaLL_K3sfQg-66ZLtZKuhpNll2eyybH6yTAK-F7yYDWz_oZuH2XL5q_0CF4B_AA</recordid><startdate>202311</startdate><enddate>202311</enddate><creator>Gellerich, Peter Anton</creator><creator>Majschak, Jens‐Peter</creator><scope>24P</scope><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-4771-0582</orcidid></search><sort><creationdate>202311</creationdate><title>A design of experiments based on the Normal‐boundary‐intersection method to identify optimum machine settings in manufacturing processes</title><author>Gellerich, Peter Anton ; Majschak, Jens‐Peter</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1299-5af8c35ad698434da8b2349cfdf79adb7b1e5d34d1c0b35981a7a20f65e039653</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Gellerich, Peter Anton</creatorcontrib><creatorcontrib>Majschak, Jens‐Peter</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>CrossRef</collection><jtitle>Proceedings in applied mathematics and mechanics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gellerich, Peter Anton</au><au>Majschak, Jens‐Peter</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A design of experiments based on the Normal‐boundary‐intersection method to identify optimum machine settings in manufacturing processes</atitle><jtitle>Proceedings in applied mathematics and mechanics</jtitle><date>2023-11</date><risdate>2023</risdate><volume>23</volume><issue>3</issue><epage>n/a</epage><issn>1617-7061</issn><eissn>1617-7061</eissn><abstract>Finding the appropriate machine settings for a given manufacturing process is an important issue in industrial production. A set of minimum and maximum machine settings correspond to the lower and upper quality limits that are specified for the produced product, and by this define the boundaries of all appropriate machine settings. This paper shows that these boundaries are the solution of a multi‐objective optimisation problem, which is called the optimum machine settings problem. However, for most processes there is no mathematical model of the manufacturing process available, which maps the setting parameters on the quality key figures in a way that allows to compute the optimisation problem. In this case, experiments may provide the required empirical data simultaneously while executing the optimisation procedure. Using a case study on heat sealing in industrial packaging, the paper shows, how to develop a design of experiments based on the Normal‐boundary‐intersection method (NBI), and how to generate the Pareto‐frontier by executing test according to this test plan. It addresses the specific limitations inherent in solving an optimisation problem by experiments. The behaviour of the method towards discrete and binary objectives and constraints is discussed.</abstract><doi>10.1002/pamm.202300009</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-4771-0582</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1617-7061
ispartof Proceedings in applied mathematics and mechanics, 2023-11, Vol.23 (3), p.n/a
issn 1617-7061
1617-7061
language eng
recordid cdi_crossref_primary_10_1002_pamm_202300009
source Wiley Online Library Journals Frontfile Complete
title A design of experiments based on the Normal‐boundary‐intersection method to identify optimum machine settings in manufacturing processes
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-19T01%3A17%3A21IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-wiley_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20design%20of%20experiments%20based%20on%20the%20Normal%E2%80%90boundary%E2%80%90intersection%20method%20to%20identify%20optimum%20machine%20settings%20in%20manufacturing%20processes&rft.jtitle=Proceedings%20in%20applied%20mathematics%20and%20mechanics&rft.au=Gellerich,%20Peter%20Anton&rft.date=2023-11&rft.volume=23&rft.issue=3&rft.epage=n/a&rft.issn=1617-7061&rft.eissn=1617-7061&rft_id=info:doi/10.1002/pamm.202300009&rft_dat=%3Cwiley_cross%3EPAMM202300009%3C/wiley_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true