{"id":14231,"date":"2021-05-04T18:00:09","date_gmt":"2021-05-04T16:00:09","guid":{"rendered":"https:\/\/www.m-q.ch\/?p=14231"},"modified":"2021-05-11T18:30:40","modified_gmt":"2021-05-11T16:30:40","slug":"le-prix-seghezzi-est-decerne","status":"publish","type":"post","link":"https:\/\/www.m-q.ch\/fr\/seghezzi-preis-verliehen\/","title":{"rendered":"La SFAQ d\u00e9cerne le Prix Seghezzi"},"content":{"rendered":"
\"\"
De gauche \u00e0 droite : la pr\u00e9sidente du jury Martina Z\u00f6lch, le laur\u00e9at Philipp Schaber et Felix M\u00fcller, membre du Conseil de fondation de la SFAQ. Roger Str\u00e4ssle<\/figcaption><\/figure>\n

Cette ann\u00e9e \u00e9galement, le \"Journ\u00e9e suisse de la qualit\u00e9<\/a> de la SAQ du 4 mai 2021 a d\u00fb \u00eatre tenue virtuellement en raison de la pand\u00e9mie. Cependant, les intervenants \u00e9taient sur place, tout comme le laur\u00e9at du Prix Seghezzi et le jury. Martina Z\u00f6lch, membre du conseil de fondation du SFAQ et pr\u00e9sidente du jury, a ainsi pu remettre solennellement \u00e0 Philipp Schaber le Prix 2021 pour la promotion de la gestion int\u00e9gr\u00e9e de la qualit\u00e9.<\/p>\n

Philipp Schaber a d'abord obtenu un Bachelor of Science en g\u00e9nie m\u00e9canique et en transformation des entreprises \u00e0 l'Universit\u00e9 technique de Graz, avant d'entreprendre et de r\u00e9ussir un Master en gestion, technologie et \u00e9conomie \u00e0 l'ETH Zurich. Son parcours est aujourd'hui couronn\u00e9 par le prix Seghezzi : Schaber (1993), n\u00e9 en Autriche, a re\u00e7u la somme de 10 000 francs suisses pour les r\u00e9sultats exceptionnels de son m\u00e9moire de ma\u00eetrise intitul\u00e9 \"Using deep learning to detect assembly errors\".<\/p>\n

Utilisation de m\u00e9thodes d'apprentissage automatique non supervis\u00e9es<\/strong><\/h4>\n

Torbj\u00f6rn Netland et Julian Senoner ont \u00e9t\u00e9 les superviseurs de la th\u00e8se de ma\u00eetrise que Philipp Schaber a achev\u00e9e avec succ\u00e8s en ao\u00fbt 2020. Dans sa th\u00e8se, M. Schaber, en collaboration avec Siemens Smart Infrastructure (SI), s'est demand\u00e9 si les m\u00e9thodes d'apprentissage automatique non supervis\u00e9es pouvaient \u00eatre utilis\u00e9es pour d\u00e9tecter les erreurs d'assemblage dans la fabrication.<\/p>\n

Cette int\u00e9ressante question de recherche est d'une grande pertinence pratique, \u00e0 l'heure o\u00f9 l'apprentissage automatique est sur le point de faire une perc\u00e9e dans le secteur manufacturier, comme le souligne la SFAQ.<\/p>\n

Dans sa th\u00e8se de ma\u00eetrise, Schaber propose une approche d'apprentissage automatique non supervis\u00e9e qui ne peut \u00eatre entra\u00een\u00e9e que sur la base d'images \"sans erreur\". Des m\u00e9canismes fiables de d\u00e9tection des erreurs ainsi que l'efficacit\u00e9 des calculs doivent \u00eatre obtenus par une combinaison cibl\u00e9e de l'apprentissage par transfert et de la \"classification par le plus proche voisin\".<\/p>\n

Preuves empiriques fournies<\/strong><\/h4>\n

Philipp Schaber a soumis ces d\u00e9fis \u00e0 un test pratique dans deux usines d'essai de Siemens Smart Infrastructure. Au cours de ses essais sur le terrain, il a pu fournir des preuves empiriques de la mani\u00e8re dont l'approche propos\u00e9e peut d\u00e9tecter de mani\u00e8re fiable les erreurs d'installation dans la pratique, tout en conservant une grande efficacit\u00e9 de calcul, comme l'\u00e9crit la SFAQ.<\/p>\n

Le travail de recherche de Philipp Schaber est donc un excellent exemple de la mani\u00e8re dont l'apprentissage automatique peut soutenir la gestion de la qualit\u00e9. Gr\u00e2ce \u00e0 ce travail, une lacune dans la recherche a \u00e9t\u00e9 combl\u00e9e d'une mani\u00e8re bas\u00e9e sur un mod\u00e8le et convaincante sur le plan empirique, ce qui est d'une grande pertinence pratique.<\/p>\n

D\u00e9claration du jury<\/strong><\/h4>\n

Le jury a expliqu\u00e9 sa d\u00e9cision comme suit :<\/p>\n

Le Potentiel d'innovation<\/strong> du travail est consid\u00e9rable : <\/em>L'approche \"non supervis\u00e9e\" est innovante en soi. Jusqu'\u00e0 pr\u00e9sent, les m\u00e9canismes de d\u00e9tection des d\u00e9fauts ont principalement \u00e9t\u00e9 appris \u00e0 partir de produits d\u00e9fectueux. \"\u00c9tendre l'apprentissage profond par l'approche m\u00e9thodologique de l'approche non supervis\u00e9e et la relier aux th\u00e9ories des r\u00e9seaux de neurones ouvre de nouvelles perspectives pour l'apprentissage automatique et \u00e9largit la port\u00e9e de l'approche de l'apprentissage profond.<\/p>\n

L'approche \"apprentissage automatique non supervis\u00e9\" \u00e9tant bas\u00e9e sur un apprentissage qui fonctionne avec des images sans erreur, cela permet une utilisation extr\u00eamement efficace de la puissance de calcul. Comme cela a pu \u00eatre d\u00e9montr\u00e9 empiriquement dans le travail, il y a une r\u00e9duction significative de l'effort avec une expressivit\u00e9 presque inchang\u00e9e en termes de d\u00e9tection des erreurs.<\/p>\n

Ici, on voit le grande importance pratique<\/strong> de travail :<\/em> La d\u00e9tection des d\u00e9fauts dans la fabrication et l'assemblage des cartes de circuits imprim\u00e9s s'est jusqu'\u00e0 pr\u00e9sent largement bas\u00e9e sur l'inspection par les employ\u00e9s, ce qui reste in\u00e9vitable en dehors de la production \u00e0 grande \u00e9chelle. Cependant, leur perception est sujette \u00e0 des erreurs, qui peuvent entra\u00eener des co\u00fbts de suivi, et l'ex\u00e9cution de ces activit\u00e9s professionnelles est souvent stressante.<\/p>\n

Gr\u00e2ce \u00e0 l'approche propos\u00e9e, la d\u00e9tection des d\u00e9fauts des machines peut \u00e9galement \u00eatre utilis\u00e9e dans la production de petites et moyennes s\u00e9ries, ce qui devrait augmenter consid\u00e9rablement le champ d'application.<\/p>\n

En plus de l'approche th\u00e9orique et m\u00e9thodologique innovante de la d\u00e9tection efficace et efficiente des d\u00e9fauts, les questions de gestion commerciale des co\u00fbts des d\u00e9fauts et du d\u00e9ploiement du personnel sont donc \u00e9galement soulev\u00e9es. Ce travail, qui se situe \u00e0 l'interface de la gestion d'entreprise, de la technologie et de l'informatique, apporte ainsi une contribution int\u00e9grative \u00e0 la gestion g\u00e9n\u00e9rale et \u00e0 l'importance de la qualit\u00e9.<\/p>\n

En conclusion, le jury souligne : \" Nous sommes heureux de pouvoir r\u00e9compenser ce travail innovant et d'une grande pertinence scientifique et pratique par le Prix Seghezzi 2021. \"<\/p>\n

Le Prix Seghezzi<\/a> est annonc\u00e9 tous les deux ans.<\/em><\/p>\n

\"\"<\/p>\n

Le couronnement de son travail de master - Philipp Schaber avec le prix Seghezzi. \u00a9 R. Str\u00e4ssle<\/p>","protected":false},"excerpt":{"rendered":"

Auch der diesj\u00e4hrige \u00abTag der Schweizer Qualit\u00e4t\u00bb der SAQ vom 4. Mai 2021 musste pandemiebedingt virtuell durchgef\u00fchrt werden. Vor Ort waren jedoch die Referenten, aber auch der Seghezzi-Preistr\u00e4ger und die Jury. Und so konnte Prof. Dr. Martina Z\u00f6lch, SFAQ-Stiftungsratsmitglied und Pr\u00e4sidentin der Jury, Philipp Schaber den Award 2021 zur F\u00f6rderung eines integrierten Managements von Qualit\u00e4t […]<\/p>\n","protected":false},"author":35,"featured_media":14241,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[3303],"tags":[4945,4942,4944,4943],"class_list":["post-14231","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-qualitaetsmanagement","tag-using-deep-learning-to-detect-assembly-errors","tag-saw","tag-schweizerischen-stiftung-fuer-forschung-und-ausbildung-qualitaet","tag-sffaq"],"acf":[],"yoast_head":"\nSFAQ verleiht Seghezzi-Preis - MQ Management und Qualit\u00e4t<\/title>\n<meta name=\"description\" content=\"Die SFAQ (Schweizerischen Stiftung f\u00fcr Forschung und Ausbildung Qualit\u00e4t) hat den Seghezzi-Award 2021 verliehen.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.m-q.ch\/fr\/le-prix-seghezzi-est-decerne\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"SFAQ verleiht Seghezzi-Preis - 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