{"id":6649,"date":"2026-06-18T05:54:12","date_gmt":"2026-06-18T05:54:12","guid":{"rendered":"https:\/\/dynaress.com\/oskim-dynaress-winovation-2026da-birincilik-odulunun-sahibi-oldu\/"},"modified":"2026-06-18T06:12:27","modified_gmt":"2026-06-18T06:12:27","slug":"oskim-dynaress-winovation-2026da-birincilik-odulunun-sahibi-oldu","status":"publish","type":"post","link":"https:\/\/dynaress.com\/tr\/oskim-dynaress-winovation-2026da-birincilik-odulunun-sahibi-oldu\/","title":{"rendered":"OSK\u0130M \/ Dynaress, WINOVATION 2026&#8217;da Birincilik \u00d6d\u00fcl\u00fcn\u00fcn Sahibi Oldu"},"content":{"rendered":"\n<p><strong>OSK\u0130M \/ Dynaress, WIN EURASIA kapsam\u0131nda d\u00fczenlenen WINOVATION 2026 Yar\u0131\u015fmas\u0131&#8217;nda &#8220;Sim\u00fclasyon ve Yapay Zek\u00e2 Destekli Kaynak S\u0131ras\u0131 Optimizasyonu ile Ara\u00e7 Sal\u0131ncaklar\u0131nda \u00c7arp\u0131lman\u0131n Azalt\u0131lmas\u0131&#8221; projesiyle birincilik \u00f6d\u00fcl\u00fcne lay\u0131k g\u00f6r\u00fcld\u00fc.<\/strong><\/p>\n\n<p>Yerli \u00fcretimi, katma de\u011ferli teknolojileri ve yenilik\u00e7i sanayi uygulamalar\u0131n\u0131 \u00f6ne \u00e7\u0131karan WINOVATION 2026&#8217;da elde edilen bu ba\u015far\u0131; OSK\u0130M \/ Dynaress&#8217;in \u00fcretim teknolojileri, yapay zek\u00e2 ve dijital d\u00f6n\u00fc\u015f\u00fcm alan\u0131ndaki \u00e7al\u0131\u015fmalar\u0131n\u0131n \u00f6nemli bir \u00e7\u0131kt\u0131s\u0131 olarak de\u011ferlendiriliyor.<\/p>\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/www.oskim.com.tr\/wp-content\/uploads\/2026\/06\/IMG_1167-1-1024x768.jpeg\" alt=\"\" class=\"wp-image-30623\"\/><\/figure>\n\n<h2 class=\"wp-block-heading\">Sanayi D\u00f6n\u00fc\u015f\u00fcm\u00fcn E\u015fi\u011finde<\/h2>\n\n<p>Sanayi d\u00fcnyas\u0131 bug\u00fcn yaln\u0131zca daha h\u0131zl\u0131 \u00fcretmenin de\u011fil; daha do\u011fru, daha verimli, daha s\u00fcrd\u00fcr\u00fclebilir ve daha \u00f6ng\u00f6r\u00fclebilir \u00fcretmenin yollar\u0131n\u0131 ar\u0131yor. K\u00fcresel rekabetin yo\u011funla\u015ft\u0131\u011f\u0131, kalite beklentilerinin artt\u0131\u011f\u0131 ve kaynaklar\u0131n daha verimli kullan\u0131lmas\u0131n\u0131n stratejik bir \u00f6ncelik haline geldi\u011fi bu d\u00f6nemde, \u00fcretim teknolojilerinin d\u00f6n\u00fc\u015f\u00fcm\u00fc ka\u00e7\u0131n\u0131lmaz hale geliyor. <\/p>\n\n<p><strong>Bu d\u00f6n\u00fc\u015f\u00fcm\u00fcn merkezinde ise yapay zek\u00e2 yer al\u0131yor.<\/strong><\/p>\n\n<p>Yapay zek\u00e2, art\u0131k yaln\u0131zca gelece\u011fe ait bir teknoloji ba\u015fl\u0131\u011f\u0131 de\u011fil; \u00fcretim sahas\u0131nda do\u011frudan kar\u015f\u0131l\u0131\u011f\u0131 olan, kaliteyi, verimlili\u011fi ve karar alma s\u00fcre\u00e7lerini d\u00f6n\u00fc\u015ft\u00fcren g\u00fc\u00e7l\u00fc bir ara\u00e7 haline geldi. Bug\u00fcn i\u015fletmeler i\u00e7in as\u0131l de\u011fer, veriyi yaln\u0131zca toplamakta de\u011fil; bu veriyi anlamland\u0131rmakta, karar s\u00fcre\u00e7lerine entegre etmekte ve \u00fcretim problemlerini daha olu\u015fmadan \u00f6ng\u00f6rebilmekte yat\u0131yor. <\/p>\n\n<h2 class=\"wp-block-heading\">Kaynakl\u0131 \u0130malat\u0131n En Zorlu Problemi: \u00c7arp\u0131lma<\/h2>\n\n<p>\u00d6zellikle kaynakl\u0131 imalat, otomotiv ba\u015fta olmak \u00fczere bir\u00e7ok sekt\u00f6rde kritik \u00f6neme sahip \u00fcretim y\u00f6ntemlerinden biri olarak \u00f6ne \u00e7\u0131k\u0131yor. Kaynak prosesi; malzeme davran\u0131\u015f\u0131, \u0131s\u0131 girdisi, fikst\u00fcrleme, par\u00e7a geometrisi ve operasyon s\u0131ras\u0131 gibi bir\u00e7ok de\u011fi\u015fkenin ayn\u0131 anda y\u00f6netilmesini gerektiren karma\u015f\u0131k bir s\u00fcre\u00e7tir. Bu nedenle kaynakl\u0131 imalat yapan i\u015fletmeler i\u00e7in \u00e7arp\u0131lma, \u00f6l\u00e7\u00fcsel sapma, yeniden i\u015fleme ve hurda riski \u00f6nemli bir maliyet ve kalite problemi olu\u015fturmaya devam ediyor.  <\/p>\n\n<p>Ara\u00e7 sal\u0131ncaklar\u0131 gibi g\u00fcvenlik, dayan\u0131m ve \u00f6l\u00e7\u00fcsel hassasiyetin kritik oldu\u011fu otomotiv par\u00e7alar\u0131nda bu problem daha da \u00f6nemli hale geliyor. Kaynak s\u0131ras\u0131nda olu\u015fan \u0131s\u0131l etkiler, par\u00e7an\u0131n nihai geometrisini do\u011frudan etkileyebiliyor. Bu durum yaln\u0131zca \u00fcretim kalitesini de\u011fil; yeni \u00fcr\u00fcn devreye alma s\u00fcrelerini, m\u00fc\u015fteri onay s\u00fcre\u00e7lerini, maliyetleri ve \u00fcretim s\u00fcreklili\u011fini de etkiliyor.  <\/p>\n\n<h2 class=\"wp-block-heading\">Deneme-Yan\u0131lman\u0131n \u00d6tesinde Bir Yakla\u015f\u0131m<\/h2>\n\n<p>OSK\u0130M \/ Dynaress, bu noktada klasik deneme-yan\u0131lma y\u00f6ntemlerinin \u00f6tesine ge\u00e7en, yapay zek\u00e2 destekli bir \u00fcretim yakla\u015f\u0131m\u0131 ortaya koyuyor. Geli\u015ftirilen \u00e7al\u0131\u015fma ile kaynak s\u0131ras\u0131 optimizasyonu, ki\u015fisel tecr\u00fcbeye dayal\u0131 bir karar olmaktan \u00e7\u0131kar\u0131larak veri temelli, tekrarlanabilir ve \u00f6l\u00e7eklenebilir bir m\u00fchendislik yakla\u015f\u0131m\u0131na d\u00f6n\u00fc\u015ft\u00fcr\u00fcl\u00fcyor. <\/p>\n\n<p>Bu yakla\u015f\u0131m\u0131n temelinde, \u00fcretim \u00f6ncesinde farkl\u0131 kaynak s\u0131ras\u0131 alternatiflerinin dijital ortamda de\u011ferlendirilmesi ve en d\u00fc\u015f\u00fck \u00e7arp\u0131lma potansiyeline sahip se\u00e7eneklerin yapay zek\u00e2 destekli olarak belirlenmesi yer al\u0131yor. B\u00f6ylece fiziksel deneme ihtiyac\u0131 azalt\u0131l\u0131rken; kalite, zaman, enerji ve kaynak kullan\u0131m\u0131 a\u00e7\u0131s\u0131ndan daha verimli bir \u00fcretim altyap\u0131s\u0131 olu\u015fturuluyor. <\/p>\n\n<p>Proje, yaln\u0131zca bir proses iyile\u015ftirme \u00e7al\u0131\u015fmas\u0131 olarak de\u011fil; sanayide yapay zek\u00e2n\u0131n nas\u0131l somut de\u011fere d\u00f6n\u00fc\u015ft\u00fcr\u00fclebilece\u011fini g\u00f6steren g\u00fc\u00e7l\u00fc bir \u00f6rnek olarak \u00f6ne \u00e7\u0131k\u0131yor. \u00c7\u00fcnk\u00fc burada yapay zek\u00e2, teorik bir model olarak de\u011fil, \u00fcretim sahas\u0131ndaki ger\u00e7ek bir problemin \u00e7\u00f6z\u00fcm\u00fcnde kullan\u0131lan karar destek mekanizmas\u0131 olarak konumlan\u0131yor. <\/p>\n\n<h2 class=\"wp-block-heading\">Hedefler ve Uzun Vadeli De\u011fer<\/h2>\n\n<p>Bu \u00e7al\u0131\u015fma ile kaynakl\u0131 imalatta \u00e7arp\u0131lma problemlerinin \u00fcretim \u00f6ncesinde \u00f6ng\u00f6r\u00fclmesi, proses kararlar\u0131n\u0131n daha kontroll\u00fc verilmesi ve yeni \u00fcr\u00fcn devreye alma s\u00fcre\u00e7lerinin daha h\u0131zl\u0131 ve g\u00fcvenilir \u015fekilde y\u00f6netilmesi hedefleniyor. Ayn\u0131 zamanda elde edilen bilgi birikimi dijital ortamda saklanarak kurumsal haf\u0131zaya aktar\u0131l\u0131yor ve farkl\u0131 par\u00e7alarda yeniden kullan\u0131labilecek s\u00fcrd\u00fcr\u00fclebilir bir altyap\u0131 olu\u015fturuluyor. <\/p>\n\n<p>Bug\u00fcn \u00fcretimde rekabet avantaj\u0131, yaln\u0131zca makine parkuru veya kapasiteyle de\u011fil; veriyi do\u011fru kullanan, s\u00fcre\u00e7lerini dijitalle\u015ftiren ve karar mekanizmalar\u0131n\u0131 ak\u0131ll\u0131 sistemlerle g\u00fc\u00e7lendiren i\u015fletmelerle \u015fekilleniyor.<\/p>\n\n<p><em>OSK\u0130M \/ Dynaress, \u00fcretim sahas\u0131ndan gelen m\u00fchendislik tecr\u00fcbesini yapay zek\u00e2, sim\u00fclasyon ve veri analiti\u011fiyle birle\u015ftirerek sanayinin ger\u00e7ek problemlerine uygulanabilir \u00e7\u00f6z\u00fcmler geli\u015ftirmeye devam ediyor.<\/em><\/p>\n\n<p><strong>\u00c7\u00fcnk\u00fc gelece\u011fin \u00fcretimi; veriyi anlayan, s\u00fcreci \u00f6ng\u00f6ren ve kaliteyi \u00fcretim ba\u015flamadan g\u00fcvence alt\u0131na alabilen sistemlerle m\u00fcmk\u00fcn olacak.<\/strong><\/p>\n\n<p>#OSK\u0130M #Dynaress #WINOVATION #WINEURASIA2026 #ArtificialIntelligence #Simulation #Industry40 #AutomotiveIndustry<\/p>\n","protected":false},"excerpt":{"rendered":"<p>OSK\u0130M \/ Dynaress, WIN EURASIA kapsam\u0131nda d\u00fczenlenen WINOVATION 2026 Yar\u0131\u015fmas\u0131&#8217;nda &#8220;Sim\u00fclasyon ve Yapay&hellip;<\/p>\n","protected":false},"author":1,"featured_media":6644,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[48,1],"tags":[],"class_list":["post-6649","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-dynalog","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/dynaress.com\/tr\/wp-json\/wp\/v2\/posts\/6649","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dynaress.com\/tr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dynaress.com\/tr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dynaress.com\/tr\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/dynaress.com\/tr\/wp-json\/wp\/v2\/comments?post=6649"}],"version-history":[{"count":1,"href":"https:\/\/dynaress.com\/tr\/wp-json\/wp\/v2\/posts\/6649\/revisions"}],"predecessor-version":[{"id":6650,"href":"https:\/\/dynaress.com\/tr\/wp-json\/wp\/v2\/posts\/6649\/revisions\/6650"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/dynaress.com\/tr\/wp-json\/wp\/v2\/media\/6644"}],"wp:attachment":[{"href":"https:\/\/dynaress.com\/tr\/wp-json\/wp\/v2\/media?parent=6649"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dynaress.com\/tr\/wp-json\/wp\/v2\/categories?post=6649"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dynaress.com\/tr\/wp-json\/wp\/v2\/tags?post=6649"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}