Rule Model for Selecting Dimensional Measurement Equipment in Inspection Planning
Process uncertainty can have negative effects on part quality and is, therefore, critical to the safety and performance of products. Those effects are manifested in the dimensional measurement uncertainty associated with those parts and products. To minimize the effects of process uncertainties, the...
Gespeichert in:
Veröffentlicht in: | Journal of computing and information science in engineering 2022-02, Vol.22 (1) |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 1 |
container_start_page | |
container_title | Journal of computing and information science in engineering |
container_volume | 22 |
creator | Feng, Shaw C Horst, John A Feeney, Allison Barnard Jones, Albert T Kramer, Thomas R Hedberg, Thomas D |
description | Process uncertainty can have negative effects on part quality and is, therefore, critical to the safety and performance of products. Those effects are manifested in the dimensional measurement uncertainty associated with those parts and products. To minimize the effects of process uncertainties, the sources of dimensional uncertainty must be identified and clearly communicated to collaborators and suppliers. A principal source of dimensional uncertainty is the measurement equipment itself. This article presents an activity model, rule types, and sample rules for selecting dimensional metrology equipment. The activity model represents key operations and information flows associated with the dimensional measurement. Analysis of the included activity model facilitates the development of rule types for measurement equipment selection as described in the Quality Information Framework (QIF) standard. Rule types are based on design information and measurement requirements. Standard rule types enable industrial metrologists to capture, exchange, and share equipment selection rules with their collaborators. Example QIF rules are defined for successful and cost-saving use in planning a measurement process with functionally complex and appropriate dimensional measurement equipment. |
doi_str_mv | 10.1115/1.4048214 |
format | Article |
fullrecord | <record><control><sourceid>asme_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1115_1_4048214</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1086514</sourcerecordid><originalsourceid>FETCH-LOGICAL-a210t-1166dd29fdaff204addd51c93e69ddca0743113a9bc2da4d8487a46ad382795a3</originalsourceid><addsrcrecordid>eNotkL1PwzAQxS0EEqUwsDN4ZUjxOY4Tj6i0UKkV37N1xA5KldrBTgb-e1za6Z7u_e6k9wi5BjYDgOIOZoKJioM4IRNQQmQlK6vTpIucZari5Tm5iHHLGCuZlBPy-jZ2lm68sR1tfKDvtrP10Lpv-tDurIutd9jRjcU4BpsWA138jG3_r1pHVy72e947-tKhc-nwkpw12EV7dZxT8rlcfMyfsvXz42p-v86QAxsyACmN4aox2DScCTTGFFCr3EplTI2sFDlAjuqr5gaFqURVopBo8hRCFZhPye3hbx18jME2ug_tDsOvBqb3XWjQxy4Se3NgMe6s3voxpFQxgZUskv0H3eNbAw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Rule Model for Selecting Dimensional Measurement Equipment in Inspection Planning</title><source>ASME Transactions Journals</source><source>Alma/SFX Local Collection</source><creator>Feng, Shaw C ; Horst, John A ; Feeney, Allison Barnard ; Jones, Albert T ; Kramer, Thomas R ; Hedberg, Thomas D</creator><creatorcontrib>Feng, Shaw C ; Horst, John A ; Feeney, Allison Barnard ; Jones, Albert T ; Kramer, Thomas R ; Hedberg, Thomas D</creatorcontrib><description>Process uncertainty can have negative effects on part quality and is, therefore, critical to the safety and performance of products. Those effects are manifested in the dimensional measurement uncertainty associated with those parts and products. To minimize the effects of process uncertainties, the sources of dimensional uncertainty must be identified and clearly communicated to collaborators and suppliers. A principal source of dimensional uncertainty is the measurement equipment itself. This article presents an activity model, rule types, and sample rules for selecting dimensional metrology equipment. The activity model represents key operations and information flows associated with the dimensional measurement. Analysis of the included activity model facilitates the development of rule types for measurement equipment selection as described in the Quality Information Framework (QIF) standard. Rule types are based on design information and measurement requirements. Standard rule types enable industrial metrologists to capture, exchange, and share equipment selection rules with their collaborators. Example QIF rules are defined for successful and cost-saving use in planning a measurement process with functionally complex and appropriate dimensional measurement equipment.</description><identifier>ISSN: 1530-9827</identifier><identifier>EISSN: 1944-7078</identifier><identifier>DOI: 10.1115/1.4048214</identifier><language>eng</language><publisher>ASME</publisher><ispartof>Journal of computing and information science in engineering, 2022-02, Vol.22 (1)</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a210t-1166dd29fdaff204addd51c93e69ddca0743113a9bc2da4d8487a46ad382795a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,781,785,27929,27930,38525</link.rule.ids></links><search><creatorcontrib>Feng, Shaw C</creatorcontrib><creatorcontrib>Horst, John A</creatorcontrib><creatorcontrib>Feeney, Allison Barnard</creatorcontrib><creatorcontrib>Jones, Albert T</creatorcontrib><creatorcontrib>Kramer, Thomas R</creatorcontrib><creatorcontrib>Hedberg, Thomas D</creatorcontrib><title>Rule Model for Selecting Dimensional Measurement Equipment in Inspection Planning</title><title>Journal of computing and information science in engineering</title><addtitle>J. Comput. Inf. Sci. Eng</addtitle><description>Process uncertainty can have negative effects on part quality and is, therefore, critical to the safety and performance of products. Those effects are manifested in the dimensional measurement uncertainty associated with those parts and products. To minimize the effects of process uncertainties, the sources of dimensional uncertainty must be identified and clearly communicated to collaborators and suppliers. A principal source of dimensional uncertainty is the measurement equipment itself. This article presents an activity model, rule types, and sample rules for selecting dimensional metrology equipment. The activity model represents key operations and information flows associated with the dimensional measurement. Analysis of the included activity model facilitates the development of rule types for measurement equipment selection as described in the Quality Information Framework (QIF) standard. Rule types are based on design information and measurement requirements. Standard rule types enable industrial metrologists to capture, exchange, and share equipment selection rules with their collaborators. Example QIF rules are defined for successful and cost-saving use in planning a measurement process with functionally complex and appropriate dimensional measurement equipment.</description><issn>1530-9827</issn><issn>1944-7078</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNotkL1PwzAQxS0EEqUwsDN4ZUjxOY4Tj6i0UKkV37N1xA5KldrBTgb-e1za6Z7u_e6k9wi5BjYDgOIOZoKJioM4IRNQQmQlK6vTpIucZari5Tm5iHHLGCuZlBPy-jZ2lm68sR1tfKDvtrP10Lpv-tDurIutd9jRjcU4BpsWA138jG3_r1pHVy72e947-tKhc-nwkpw12EV7dZxT8rlcfMyfsvXz42p-v86QAxsyACmN4aox2DScCTTGFFCr3EplTI2sFDlAjuqr5gaFqURVopBo8hRCFZhPye3hbx18jME2ug_tDsOvBqb3XWjQxy4Se3NgMe6s3voxpFQxgZUskv0H3eNbAw</recordid><startdate>20220201</startdate><enddate>20220201</enddate><creator>Feng, Shaw C</creator><creator>Horst, John A</creator><creator>Feeney, Allison Barnard</creator><creator>Jones, Albert T</creator><creator>Kramer, Thomas R</creator><creator>Hedberg, Thomas D</creator><general>ASME</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20220201</creationdate><title>Rule Model for Selecting Dimensional Measurement Equipment in Inspection Planning</title><author>Feng, Shaw C ; Horst, John A ; Feeney, Allison Barnard ; Jones, Albert T ; Kramer, Thomas R ; Hedberg, Thomas D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a210t-1166dd29fdaff204addd51c93e69ddca0743113a9bc2da4d8487a46ad382795a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Feng, Shaw C</creatorcontrib><creatorcontrib>Horst, John A</creatorcontrib><creatorcontrib>Feeney, Allison Barnard</creatorcontrib><creatorcontrib>Jones, Albert T</creatorcontrib><creatorcontrib>Kramer, Thomas R</creatorcontrib><creatorcontrib>Hedberg, Thomas D</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of computing and information science in engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Feng, Shaw C</au><au>Horst, John A</au><au>Feeney, Allison Barnard</au><au>Jones, Albert T</au><au>Kramer, Thomas R</au><au>Hedberg, Thomas D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Rule Model for Selecting Dimensional Measurement Equipment in Inspection Planning</atitle><jtitle>Journal of computing and information science in engineering</jtitle><stitle>J. Comput. Inf. Sci. Eng</stitle><date>2022-02-01</date><risdate>2022</risdate><volume>22</volume><issue>1</issue><issn>1530-9827</issn><eissn>1944-7078</eissn><abstract>Process uncertainty can have negative effects on part quality and is, therefore, critical to the safety and performance of products. Those effects are manifested in the dimensional measurement uncertainty associated with those parts and products. To minimize the effects of process uncertainties, the sources of dimensional uncertainty must be identified and clearly communicated to collaborators and suppliers. A principal source of dimensional uncertainty is the measurement equipment itself. This article presents an activity model, rule types, and sample rules for selecting dimensional metrology equipment. The activity model represents key operations and information flows associated with the dimensional measurement. Analysis of the included activity model facilitates the development of rule types for measurement equipment selection as described in the Quality Information Framework (QIF) standard. Rule types are based on design information and measurement requirements. Standard rule types enable industrial metrologists to capture, exchange, and share equipment selection rules with their collaborators. Example QIF rules are defined for successful and cost-saving use in planning a measurement process with functionally complex and appropriate dimensional measurement equipment.</abstract><pub>ASME</pub><doi>10.1115/1.4048214</doi></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1530-9827 |
ispartof | Journal of computing and information science in engineering, 2022-02, Vol.22 (1) |
issn | 1530-9827 1944-7078 |
language | eng |
recordid | cdi_crossref_primary_10_1115_1_4048214 |
source | ASME Transactions Journals; Alma/SFX Local Collection |
title | Rule Model for Selecting Dimensional Measurement Equipment in Inspection Planning |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-13T20%3A55%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-asme_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Rule%20Model%20for%20Selecting%20Dimensional%20Measurement%20Equipment%20in%20Inspection%20Planning&rft.jtitle=Journal%20of%20computing%20and%20information%20science%20in%20engineering&rft.au=Feng,%20Shaw%20C&rft.date=2022-02-01&rft.volume=22&rft.issue=1&rft.issn=1530-9827&rft.eissn=1944-7078&rft_id=info:doi/10.1115/1.4048214&rft_dat=%3Casme_cross%3E1086514%3C/asme_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 |