{"id":3668,"date":"2022-07-13T09:30:00","date_gmt":"2022-07-13T07:30:00","guid":{"rendered":"https:\/\/cirpicme.org\/?page_id=3668"},"modified":"2022-07-26T13:16:16","modified_gmt":"2022-07-26T11:16:16","slug":"quality-metrology-testing","status":"publish","type":"page","link":"https:\/\/cirpicme.org\/index.php\/quality-metrology-testing\/","title":{"rendered":"Quality, Metrology & Testing"},"content":{"rendered":"\n
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To access the paper presentation page (paper info, video viewing, Q&A posting), please click on the paper title.<\/p>\n\n\n\n

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  1. Algorithm for calculating distance and sensor-object angle from raw data of ultra-low power, long-range ultrasonic time-of-flight range sensors<\/a><\/strong><\/strong><\/strong><\/strong><\/strong>
    Kevin Bluemel<\/span>, Flaviana Tagliaferri, Michael Kuhl (Germany)<\/em><\/li>
  2. Interpretation Framework of Predictive Quality Models for Process- and Product-oriented Decision Support<\/a><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong>
    Daniel Buschmann<\/span>, Tobias Schulze, Chrismarie Enslin, Robert H. Schmitt (Germany)<\/em><\/li>
  3. A deep learning-based process monitoring system for toothbrush manufacturing defect characterization<\/a><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong>
    Nengsheng Bao, Yuchen Fan<\/span>, Zhaopeng Luo, Chaoping Li, Alessandro Simeone, Chunsheng Zhang (China)<\/em><\/li>
  4. A computer vision based approach to reduce system downtimes in an automated high-rack logistics warehouse<\/a><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong>
    Jakob Giner<\/span>, Denis Katic, Klaudia Kovacs, Robert Glawar, Wilfried Sihn (Austria)<\/em><\/li>
  5. Comparison of methods for management of measurement errors in surface topography measurements<\/a><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong>
    Giacomo Maculotti<\/span>, Gianfranco Genta, Danilo Quagliotti, Hans N. Hansen, Maurizio Galetto (Italy)<\/em><\/li>
  6. Large-volume metrology in shipbuilding: structured comparison of innovative measuring instruments<\/a><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong>
    Domenico A. Maisano<\/span>, Luca Mastrogiacomo, Fiorenzo Franceschini, Salvatore Capizzi, Gianandrea Pischedda, Daniele Laurenza, Giorgio Gomiero, Giuseppe Manca (Italy)<\/em><\/li>
  7. On the importance of domain expertise in feature engineering for predictive product quality in production<\/a><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong>
    Hendrik Mende<\/span>, Maik Frye, Paul-Alexander Vogel, Saksham Kiroriwal, Robert H. Schmitt, Thomas Bergs (Germany)<\/em><\/li>
  8. Predicting the solidification time of low pressure die castings using geometric feature-based machine learning metamodels<\/a><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong>
    Tobias Rosnitschek<\/span>, Maximilian Erber, Bettina Alber-Laukant, Christoph Hartmann, Wolfram Volk, Frank Rieg, Stephan Tremmel (Germany)<\/em><\/li>
  9. Deep Learning based Predictive Testing Strategy in the Automotive Industry<\/a><\/strong>
    Andreas Schoch<\/span>, Robert Refflinghaus, Patrick Zivkovic (Germany)<\/em><\/li>
  10. Time-Domain Reflectometry for Automated Failure Analysis in Power Transistors<\/a><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong>
    Kanuj Sharma<\/span>, Simon Kamm, Valentyna Afansenko, Kevin Munoz Baron, Ingmar Kallfass (Germany)<\/em><\/li>
  11. Marker-free identification of turned, ground and deep rolled workpieces using wavelet transformation<\/a><\/strong><\/strong><\/strong><\/strong><\/strong>
    Bernd Breidenstein, Marcel Wichmann, Hendrik Voelker<\/span> (Germany)<\/em><\/li>
  12. Web based maintenance work support by neural networks – Detection and wear estimation of components in wind energy turbines<\/a><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong>
    Waldemar Zeitler<\/span>, Moritz Quandt, Hendrik Stern, Michael Freitag (Germany)<\/em><\/li><\/ol>\n\n\n\n

    <\/p>\n\n\n\n

    <\/p>\n","protected":false},"excerpt":{"rendered":"

    To access the paper presentation page (paper info, video viewing, Q&A posting), please click on the paper title. Algorithm for calculating distance and sensor-object angle from raw data of ultra-low power, long-range ultrasonic time-of-flight range sensorsKevin Bluemel, Flaviana Tagliaferri, Michael Kuhl (Germany) Interpretation Framework of Predictive Quality Models for Process-…<\/p>\n

    Continue reading<\/span><\/i><\/a> <\/p>\n","protected":false},"author":9,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"nf_dc_page":"","om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"class_list":["post-3668","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/pages\/3668","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/comments?post=3668"}],"version-history":[{"count":3,"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/pages\/3668\/revisions"}],"predecessor-version":[{"id":4013,"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/pages\/3668\/revisions\/4013"}],"wp:attachment":[{"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/media?parent=3668"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}