Loading…

Stamping Plant 4.0 – Basics for the Application of Data Mining Methods in Manufacturing Car Body Parts

Data-driven quality evaluation in the stamping process of car body parts is quite promising because dependencies in the process have not yet been sufficiently researched. However, the application of data mining methods for the process in stamping plants would require a large number of sample data se...

Full description

Saved in:
Bibliographic Details
Published in:Key engineering materials 2015-03, Vol.639, p.21-30, Article 21
Main Authors: Ostermair, Martin, Werner, Axel, Glück, Bernhard, Meinhardt, Josef, Lipp, Arnulf, Purr, Stephan
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c3611-4a631d01bf32052f60931db1e8eda9014a4408141e3d68087e1b684fbdf1ad563
cites cdi_FETCH-LOGICAL-c3611-4a631d01bf32052f60931db1e8eda9014a4408141e3d68087e1b684fbdf1ad563
container_end_page 30
container_issue
container_start_page 21
container_title Key engineering materials
container_volume 639
creator Ostermair, Martin
Werner, Axel
Glück, Bernhard
Meinhardt, Josef
Lipp, Arnulf
Purr, Stephan
description Data-driven quality evaluation in the stamping process of car body parts is quite promising because dependencies in the process have not yet been sufficiently researched. However, the application of data mining methods for the process in stamping plants would require a large number of sample data sets. Today, acquiring these data represents a major challenge, because the necessary data are inadequately measured, recorded or stored. Thus, the preconditions for the sample data acquisition must first be created before being able to investigate any correlations. In addition, the process conditions change over time due to wear mechanisms. Therefore, the results do not remain valid and a constant data acquisition is required. In this publication, the current situation in stamping plants regarding the process robustness will be first discussed and the need for data-driven methods will be shown. Subsequently, the state of technology regarding the possibility of collecting the sample data sets for quality analysis in producing car body parts will be researched. At the end of this work, an overview will be provided concerning how this data collection was implemented at BMW as well as what kind of potential can be expected.
doi_str_mv 10.4028/www.scientific.net/KEM.639.21
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1744719029</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>4068679461</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3611-4a631d01bf32052f60931db1e8eda9014a4408141e3d68087e1b684fbdf1ad563</originalsourceid><addsrcrecordid>eNqNkdFqFDEYhQdRsFbfISCCNzPNn2Syk4si7dpasUsL6nXIZhI37WwyJhmW3vUdfEOfpFlXaOlF6VX-kHMOJ_9XVR8ANwyT7mCz2TRJO-Ozs0433uSDbyeLhlPREHhR7QHnpBYz0b4sMwZai47w19WblK4wptBBu1etvme1Hp3_hS4H5TNiDUZ_b_-gY5WcTsiGiPLKoKNxHJxW2QWPgkWfVVZo4fzWtzB5FfqEnEcL5SerdJ7i9mGuIjoO_Q26VDGnt9Urq4Zk3v0_96ufpyc_5mf1-cWXr_Oj81pTDlAzxSn0GJaWEtwSy7Eo9yWYzvRKYGCKMdwBA0N73uFuZmDJO2aXvQXVt5zuVx93uWMMvyeTsly7pM1QfmfClCTMGJuBwEQU6ftH0qswRV_aFZUA1pKWsqI63Kl0DClFY-UY3VrFGwlYbjnIwkHec5CFgywcZOEgCRT__JFfu_xvkzkqNzyVcm3W9ymfdinF5FM2evWg7LN63AHXkbDQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1791452534</pqid></control><display><type>article</type><title>Stamping Plant 4.0 – Basics for the Application of Data Mining Methods in Manufacturing Car Body Parts</title><source>Scientific.net Journals</source><creator>Ostermair, Martin ; Werner, Axel ; Glück, Bernhard ; Meinhardt, Josef ; Lipp, Arnulf ; Purr, Stephan</creator><creatorcontrib>Ostermair, Martin ; Werner, Axel ; Glück, Bernhard ; Meinhardt, Josef ; Lipp, Arnulf ; Purr, Stephan</creatorcontrib><description>Data-driven quality evaluation in the stamping process of car body parts is quite promising because dependencies in the process have not yet been sufficiently researched. However, the application of data mining methods for the process in stamping plants would require a large number of sample data sets. Today, acquiring these data represents a major challenge, because the necessary data are inadequately measured, recorded or stored. Thus, the preconditions for the sample data acquisition must first be created before being able to investigate any correlations. In addition, the process conditions change over time due to wear mechanisms. Therefore, the results do not remain valid and a constant data acquisition is required. In this publication, the current situation in stamping plants regarding the process robustness will be first discussed and the need for data-driven methods will be shown. Subsequently, the state of technology regarding the possibility of collecting the sample data sets for quality analysis in producing car body parts will be researched. At the end of this work, an overview will be provided concerning how this data collection was implemented at BMW as well as what kind of potential can be expected.</description><identifier>ISSN: 1013-9826</identifier><identifier>ISSN: 1662-9795</identifier><identifier>EISSN: 1662-9795</identifier><identifier>DOI: 10.4028/www.scientific.net/KEM.639.21</identifier><language>eng</language><publisher>Zurich: Trans Tech Publications Ltd</publisher><subject>Automotive bodies ; Automotive components ; Constants ; Data mining ; Production methods ; Robustness ; Stamping</subject><ispartof>Key engineering materials, 2015-03, Vol.639, p.21-30, Article 21</ispartof><rights>2015 Trans Tech Publications Ltd</rights><rights>Copyright Trans Tech Publications Ltd. Mar 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3611-4a631d01bf32052f60931db1e8eda9014a4408141e3d68087e1b684fbdf1ad563</citedby><cites>FETCH-LOGICAL-c3611-4a631d01bf32052f60931db1e8eda9014a4408141e3d68087e1b684fbdf1ad563</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://www.scientific.net/Image/TitleCover/3910?width=600</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Ostermair, Martin</creatorcontrib><creatorcontrib>Werner, Axel</creatorcontrib><creatorcontrib>Glück, Bernhard</creatorcontrib><creatorcontrib>Meinhardt, Josef</creatorcontrib><creatorcontrib>Lipp, Arnulf</creatorcontrib><creatorcontrib>Purr, Stephan</creatorcontrib><title>Stamping Plant 4.0 – Basics for the Application of Data Mining Methods in Manufacturing Car Body Parts</title><title>Key engineering materials</title><description>Data-driven quality evaluation in the stamping process of car body parts is quite promising because dependencies in the process have not yet been sufficiently researched. However, the application of data mining methods for the process in stamping plants would require a large number of sample data sets. Today, acquiring these data represents a major challenge, because the necessary data are inadequately measured, recorded or stored. Thus, the preconditions for the sample data acquisition must first be created before being able to investigate any correlations. In addition, the process conditions change over time due to wear mechanisms. Therefore, the results do not remain valid and a constant data acquisition is required. In this publication, the current situation in stamping plants regarding the process robustness will be first discussed and the need for data-driven methods will be shown. Subsequently, the state of technology regarding the possibility of collecting the sample data sets for quality analysis in producing car body parts will be researched. At the end of this work, an overview will be provided concerning how this data collection was implemented at BMW as well as what kind of potential can be expected.</description><subject>Automotive bodies</subject><subject>Automotive components</subject><subject>Constants</subject><subject>Data mining</subject><subject>Production methods</subject><subject>Robustness</subject><subject>Stamping</subject><issn>1013-9826</issn><issn>1662-9795</issn><issn>1662-9795</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqNkdFqFDEYhQdRsFbfISCCNzPNn2Syk4si7dpasUsL6nXIZhI37WwyJhmW3vUdfEOfpFlXaOlF6VX-kHMOJ_9XVR8ANwyT7mCz2TRJO-Ozs0433uSDbyeLhlPREHhR7QHnpBYz0b4sMwZai47w19WblK4wptBBu1etvme1Hp3_hS4H5TNiDUZ_b_-gY5WcTsiGiPLKoKNxHJxW2QWPgkWfVVZo4fzWtzB5FfqEnEcL5SerdJ7i9mGuIjoO_Q26VDGnt9Urq4Zk3v0_96ufpyc_5mf1-cWXr_Oj81pTDlAzxSn0GJaWEtwSy7Eo9yWYzvRKYGCKMdwBA0N73uFuZmDJO2aXvQXVt5zuVx93uWMMvyeTsly7pM1QfmfClCTMGJuBwEQU6ftH0qswRV_aFZUA1pKWsqI63Kl0DClFY-UY3VrFGwlYbjnIwkHec5CFgywcZOEgCRT__JFfu_xvkzkqNzyVcm3W9ymfdinF5FM2evWg7LN63AHXkbDQ</recordid><startdate>20150301</startdate><enddate>20150301</enddate><creator>Ostermair, Martin</creator><creator>Werner, Axel</creator><creator>Glück, Bernhard</creator><creator>Meinhardt, Josef</creator><creator>Lipp, Arnulf</creator><creator>Purr, Stephan</creator><general>Trans Tech Publications Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>KB.</scope><scope>L6V</scope><scope>M7S</scope><scope>PDBOC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>7SC</scope><scope>7TB</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20150301</creationdate><title>Stamping Plant 4.0 – Basics for the Application of Data Mining Methods in Manufacturing Car Body Parts</title><author>Ostermair, Martin ; Werner, Axel ; Glück, Bernhard ; Meinhardt, Josef ; Lipp, Arnulf ; Purr, Stephan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3611-4a631d01bf32052f60931db1e8eda9014a4408141e3d68087e1b684fbdf1ad563</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Automotive bodies</topic><topic>Automotive components</topic><topic>Constants</topic><topic>Data mining</topic><topic>Production methods</topic><topic>Robustness</topic><topic>Stamping</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ostermair, Martin</creatorcontrib><creatorcontrib>Werner, Axel</creatorcontrib><creatorcontrib>Glück, Bernhard</creatorcontrib><creatorcontrib>Meinhardt, Josef</creatorcontrib><creatorcontrib>Lipp, Arnulf</creatorcontrib><creatorcontrib>Purr, Stephan</creatorcontrib><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>Materials Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Materials Science Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Key engineering materials</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ostermair, Martin</au><au>Werner, Axel</au><au>Glück, Bernhard</au><au>Meinhardt, Josef</au><au>Lipp, Arnulf</au><au>Purr, Stephan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Stamping Plant 4.0 – Basics for the Application of Data Mining Methods in Manufacturing Car Body Parts</atitle><jtitle>Key engineering materials</jtitle><date>2015-03-01</date><risdate>2015</risdate><volume>639</volume><spage>21</spage><epage>30</epage><pages>21-30</pages><artnum>21</artnum><issn>1013-9826</issn><issn>1662-9795</issn><eissn>1662-9795</eissn><abstract>Data-driven quality evaluation in the stamping process of car body parts is quite promising because dependencies in the process have not yet been sufficiently researched. However, the application of data mining methods for the process in stamping plants would require a large number of sample data sets. Today, acquiring these data represents a major challenge, because the necessary data are inadequately measured, recorded or stored. Thus, the preconditions for the sample data acquisition must first be created before being able to investigate any correlations. In addition, the process conditions change over time due to wear mechanisms. Therefore, the results do not remain valid and a constant data acquisition is required. In this publication, the current situation in stamping plants regarding the process robustness will be first discussed and the need for data-driven methods will be shown. Subsequently, the state of technology regarding the possibility of collecting the sample data sets for quality analysis in producing car body parts will be researched. At the end of this work, an overview will be provided concerning how this data collection was implemented at BMW as well as what kind of potential can be expected.</abstract><cop>Zurich</cop><pub>Trans Tech Publications Ltd</pub><doi>10.4028/www.scientific.net/KEM.639.21</doi><tpages>10</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1013-9826
ispartof Key engineering materials, 2015-03, Vol.639, p.21-30, Article 21
issn 1013-9826
1662-9795
1662-9795
language eng
recordid cdi_proquest_miscellaneous_1744719029
source Scientific.net Journals
subjects Automotive bodies
Automotive components
Constants
Data mining
Production methods
Robustness
Stamping
title Stamping Plant 4.0 – Basics for the Application of Data Mining Methods in Manufacturing Car Body Parts
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T05%3A04%3A20IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Stamping%20Plant%204.0%20%E2%80%93%20Basics%20for%20the%20Application%20of%20Data%20Mining%20Methods%20in%20Manufacturing%20Car%20Body%20Parts&rft.jtitle=Key%20engineering%20materials&rft.au=Ostermair,%20Martin&rft.date=2015-03-01&rft.volume=639&rft.spage=21&rft.epage=30&rft.pages=21-30&rft.artnum=21&rft.issn=1013-9826&rft.eissn=1662-9795&rft_id=info:doi/10.4028/www.scientific.net/KEM.639.21&rft_dat=%3Cproquest_cross%3E4068679461%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c3611-4a631d01bf32052f60931db1e8eda9014a4408141e3d68087e1b684fbdf1ad563%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1791452534&rft_id=info:pmid/&rfr_iscdi=true