{"id":90464,"date":"2025-03-04T14:52:09","date_gmt":"2025-03-04T06:52:09","guid":{"rendered":"https:\/\/solomon-3d.mesvr.tw\/?p=90464"},"modified":"2025-07-18T16:42:37","modified_gmt":"2025-07-18T08:42:37","slug":"ai-ve-aoi-arasindaki-farklar-nelerdir","status":"publish","type":"post","link":"https:\/\/solomon-3d.mesvr.tw\/tr\/blog\/ai-ve-aoi-arasindaki-farklar-nelerdir\/","title":{"rendered":"AI ve AOI Aras\u0131ndaki Farklar Nelerdir?"},"content":{"rendered":"
<\/div>
\n
<\/div>\n
\n

AI ve AOI Aras\u0131ndaki Farklar Nelerdir?<\/h1><\/div>\n\n\n\n
\n
\"\"<\/div>\n<\/div>\n <\/div><\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
\n
\n
\n

AOI’yi Tan\u0131yal\u0131m<\/h2>\n\n\n\n
S\u0131n\u0131rl\u0131 \u00e7e\u015fitlilikle yap\u0131lan kitlesel \u00fcretimden, d\u00fc\u015f\u00fck hacimli ve y\u00fcksek \u00e7e\u015fitlilikte \u00fcr\u00fcnlerin \u00fcretimine odaklanan dinamik modele ge\u00e7i\u015f, kalite kontrol\u00fcn\u00fc ve denetimini daha karma\u015f\u0131k ve zorlu hale getirmi\u015ftir. \u00dcr\u00fcnler art\u0131k daha geni\u015f \u015fekil, boyut, malzeme ve di\u011fer \u00f6zellik yelpazesinde sunulmakta, bu da daha tan\u0131mlanamayan kusurlara yol a\u00e7maktad\u0131r.

Bu nedenle, AOI (Otomatik Optik Muayene)<\/a><\/strong> sistemleri, end\u00fcstriyel s\u00fcre\u00e7lerdeki kusur tespiti i\u00e7in yayg\u0131n bir \u00e7\u00f6z\u00fcm haline gelmi\u015ftir. Ancak, geleneksel AOI, kusur tespiti<\/a> i\u00e7in \u00f6nceden belirlenmi\u015f kusur \u00f6rneklerine ve sabit parametrelere dayan\u0131r, bu da AOI sistemlerinin \u00e7evik ve h\u0131zl\u0131 denetim kapasitesini k\u0131s\u0131tlar. Geleneksel denetim sistemlerinin kusurlar\u0131 g\u00f6zden ka\u00e7\u0131rma olas\u0131l\u0131\u011f\u0131 \u00f6nemli \u00f6l\u00e7\u00fcde artar; ancak, AI, daha esnek ve verimli denetimlere olanak tan\u0131yarak makine g\u00f6r\u00fc\u015f\u00fc i\u00e7in d\u00f6n\u00fc\u015ft\u00fcr\u00fcc\u00fc bir \u00e7\u00f6z\u00fcm sunar.<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
\n
\n
\n

AOI ile Kusur Tespiti<\/h2>\n\n\n\n
T\u00fcketici elektroni\u011fi \u00fcr\u00fcnlerinin geli\u015fmeye devam etmesiyle birlikte, yar\u0131 iletkenler<\/a>, optoelektronik<\/a> ve ak\u0131ll\u0131 \u00fcretim<\/a> gibi end\u00fcstriler \u00f6nemli bir b\u00fcy\u00fcme ya\u015famaktad\u0131r. Kusurlar, \u00fcr\u00fcn i\u015flevselli\u011fini etkileyebilece\u011finden, \u00fcretim sekt\u00f6rlerinde verimlili\u011fi art\u0131rmaya y\u00f6nelik artan bir ihtiya\u00e7 vard\u0131r. Geleneksel \u00fcretim hatlar\u0131, \u00fcr\u00fcn kusur desenlerinin manuel olarak incelenmesine dayan\u0131yordu, ancak bu y\u00f6ntem, ayr\u0131nt\u0131l\u0131 denetim ve \u00fcretim verimlili\u011fi taleplerini kar\u015f\u0131lamakta yetersiz kalmaktad\u0131r.

AOI sistemleri, makine g\u00f6r\u00fc\u015f\u00fc teknolojisiyle g\u00fc\u00e7lendirilmi\u015f bir \u015fekilde, optikler, elektronik kontrol, mekanikler ve denetim yaz\u0131l\u0131mlar\u0131n\u0131 kusursuz bir \u015fekilde birle\u015ftirerek hassas denetim g\u00f6revlerini yerine getirir. Bu sistemler, optimize edilmi\u015f \u0131\u015f\u0131k kayna\u011f\u0131 konfig\u00fcrasyonlar\u0131yla g\u00f6r\u00fcnt\u00fc \u00f6zelliklerini vurgulayarak ve do\u011fru konumland\u0131rma ve denetim i\u00e7in ileri d\u00fczey bilgisayar g\u00f6r\u00fcnt\u00fc i\u015fleme tekniklerini kullanarak kusur tespiti verimlili\u011fini art\u0131r\u0131r. AOI, \u00fcretim hatt\u0131ndaki hem bitmi\u015f hem de yar\u0131 mamul \u00fcr\u00fcnlerde kusurlar, kirleticiler ve d\u00fczensizlikleri h\u0131zl\u0131ca tarayarak kalite kontrol \u00f6nlemlerini b\u00fcy\u00fck \u00f6l\u00e7\u00fcde iyile\u015ftirebilir.

Manuel denetim y\u00f6ntemleriyle kar\u015f\u0131la\u015ft\u0131r\u0131ld\u0131\u011f\u0131nda, AOI sistemleri kusur tespitinde daha \u00fcst\u00fcn bir tutarl\u0131l\u0131k seviyesi sa\u011flar. Ayr\u0131ca, y\u00fcksek \u00e7\u00f6z\u00fcn\u00fcrl\u00fckl\u00fc kameralarla<\/a> donat\u0131lm\u0131\u015f AOI sistemleri, insan g\u00f6z\u00fcn\u00fcn tespit etmekte zorlanabilece\u011fi ince ayr\u0131nt\u0131lar\u0131 ay\u0131rt edebilir. Bunun yan\u0131 s\u0131ra, dakikada binlerce \u00f6\u011feyi inceleme kapasitesi, geleneksel manuel g\u00f6rsel denetim s\u00fcre\u00e7lerindeki verimsizlikleri ortadan kald\u0131r\u0131r.<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
\n
\n
\n
AOI ve avantajlar\u0131 hakk\u0131nda daha fazlas\u0131n\u0131 ke\u015ffedin<\/span><\/span><\/span><\/a><\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
\n
\n
\n

AOI End\u00fcstriyel Uygulamalar\u0131<\/h2>\n\n\n\n
AOI teknolojisi, \u00fcr\u00fcnlerdeki deformasyonlar\u0131, hasarlar\u0131, eksik bile\u015fenleri, kirleri, \u00e7izikleri ve di\u011fer kusurlar\u0131 denetlemenin yan\u0131 s\u0131ra, barkod okuma, hassas \u00f6l\u00e7\u00fcmler ve bask\u0131 denetimi gibi kritik g\u00f6revleri yerine getirmek i\u00e7in \u00e7e\u015fitli end\u00fcstriyel sekt\u00f6rlerde yayg\u0131n olarak kullan\u0131lmaktad\u0131r. Sonu\u00e7 olarak, elektronik<\/a>, tekstil<\/a>, g\u0131da ve i\u00e7ecek<\/a>, otomotiv<\/a> gibi \u00e7e\u015fitli end\u00fcstriler AOI teknolojisinden fayda sa\u011flamaktad\u0131r.<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
\n
\n
\n
\"AOI<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
\n
\n
\n

AOI’nin Kusur Tespiti \u0130\u00e7in S\u0131n\u0131rlamalar\u0131<\/h2>\n\n\n\n
AOI’nin benimsenmesi, \u00e7e\u015fitli end\u00fcstriyel sekt\u00f6rlerde yayg\u0131n hale gelse de, AOI’nin son derece \u00f6zelle\u015ftirilmi\u015f yap\u0131s\u0131, yayg\u0131n uygulama i\u00e7in zorluklar ve s\u0131n\u0131rlamalar sunmaktad\u0131r. \u00d6zellikle karma\u015f\u0131k \u00fcr\u00fcn kusurlar\u0131, g\u00f6r\u00fcnt\u00fc arka planlar\u0131 ve \u0131\u015f\u0131kland\u0131rma varyasyonlar\u0131yla kar\u015f\u0131la\u015f\u0131ld\u0131\u011f\u0131nda, AOI sistemleri baz\u0131 k\u0131s\u0131tlamalarla kar\u015f\u0131la\u015fabilir.

AOI, sistem i\u00e7ine programlanm\u0131\u015f olan tespit mant\u0131\u011f\u0131na dayal\u0131 bir kural tabanl\u0131 yarg\u0131 mekanizmas\u0131yla \u00e7al\u0131\u015f\u0131r. AOI, yaln\u0131zca \u00f6nceden belirlenmi\u015f parametreler ve \u00f6rnek kusurlar i\u00e7in denetim yap\u0131lan temel olarak kusurlar\u0131 tan\u0131mlayabilir. \u00d6rne\u011fin, e\u011fer tespit mant\u0131\u011f\u0131 kusurlar\u0131 dairesel olarak tan\u0131ml\u0131yorsa, dairesel olmayan kusurlar AOI sistemi taraf\u0131ndan tespit edilemeyebilir. Yumurta kabu\u011fu kalitesindeki de\u011fi\u015fiklikler<\/a>, PCBA montaj\u0131ndaki anormal kusurlar<\/a>, plastik tokalardaki ya\u011f lekeleri<\/a> ve metal damgal\u0131 par\u00e7alardaki \u00e7izikler<\/a> gibi rastgele olu\u015fan kusur t\u00fcrleri, AOI’nin bu karma\u015f\u0131kl\u0131klar\u0131 etkili bir \u015fekilde tespit etme yetene\u011fini b\u00fcy\u00fck \u00f6l\u00e7\u00fcde zorla\u015ft\u0131r\u0131r.

Kusurlar\u0131n g\u00f6zden ka\u00e7ma riskini azaltmak i\u00e7in, AOI sistemleri genellikle y\u00fcksek d\u00fczeyde kat\u0131l\u0131k ile parametreler ayarlan\u0131r, bu da AOI’yi a\u015f\u0131r\u0131 hassas hale getirir ve yanl\u0131\u015f pozitiflere daha yatk\u0131n hale getirir. Dahas\u0131, sistem operat\u00f6rlerinin s\u00fcrekli olarak sistem algoritmalar\u0131n\u0131 ve parametrelerini ince ayar yapmalar\u0131 gerekir, ayr\u0131ca \u00fcretim hatlar\u0131n\u0131n kusurlar\u0131n g\u00f6zden ka\u00e7mas\u0131n\u0131 veya yanl\u0131\u015f pozitifleri engellemek i\u00e7in tekrar tekrar \u00fcr\u00fcn denetimleri yapmas\u0131 gerekebilir. Bu fakt\u00f6rler, \u00fcretim verimlili\u011fini \u00f6nemli \u00f6l\u00e7\u00fcde etkiler ve \u00fcretim maliyetlerini art\u0131r\u0131r.

AOI’nin etkinli\u011fi, \u0131\u015f\u0131k kaynaklar\u0131, kameralar ve lenslerin do\u011fru koordinasyonuna dayan\u0131r. I\u015f\u0131k kaynaklar\u0131 a\u00e7\u0131s\u0131ndan, yo\u011funluklar\u0131n\u0131n ve \u00f6zelliklerinin ayarlanmas\u0131, kontrast\u0131 art\u0131rmak ve nesne \u00f6zelliklerini etkili bir \u015fekilde g\u00f6stermek i\u00e7in \u00f6nemlidir. Bu ayar, denetlenen nesnenin malzemesine, rengini ve \u015feklini g\u00f6z \u00f6n\u00fcnde bulundurarak, optimal g\u00f6r\u00fcnt\u00fcler elde edilmesi ve yanl\u0131\u015f pozitif risklerinin azalt\u0131lmas\u0131 i\u00e7in \u00f6zelle\u015ftirilmelidir. Kameralar se\u00e7ilirken, duyarl\u0131l\u0131k bile\u015fenleri, \u00e7\u00f6z\u00fcn\u00fcrl\u00fck ve kare h\u0131zlar\u0131 gibi fakt\u00f6rler, denetim gereksinimlerine g\u00f6re dikkatle d\u00fc\u015f\u00fcn\u00fclmelidir. Bu kameralar, optik sistemin tam kapasitesinden yararlanmak i\u00e7in uygun lenslerle e\u015fle\u015ftirilmelidir.

Ekipman detaylar\u0131n\u0131n g\u00f6r\u00fcnt\u00fclemeyi etkilemesinin \u00f6tesinde, operat\u00f6rlerin, ayarlamalar veya bile\u015fen de\u011fi\u015fiklikleri gerekti\u011finde makine parametrelerini ve hizalamalar\u0131n\u0131 yeniden yap\u0131land\u0131rma g\u00f6revini deneyimlerine dayanarak \u00fcstlenmeleri gerekir. Ayr\u0131ca, donan\u0131m ve yaz\u0131l\u0131m bile\u015fenlerinin ayarlanmas\u0131 do\u011fas\u0131 gere\u011fi karma\u015f\u0131kt\u0131r ve onar\u0131m s\u00fcreleri geni\u015f bir yelpazede de\u011fi\u015febilir, birka\u00e7 g\u00fcnden birka\u00e7 aya kadar uzanabilir. Bu durum, modern \u00fcretim hatlar\u0131n\u0131n dinamik taleplerini kar\u015f\u0131lamakta zorluklar yaratmaktad\u0131r. Sonu\u00e7 olarak, AOI kullanan bir\u00e7ok end\u00fcstri, denetim do\u011frulu\u011funu ve verimlili\u011fini art\u0131rmak amac\u0131yla son zamanlarda yapay zekay\u0131 (AI)<\/a> benimsemi\u015ftir.<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
\n
\n
\n
Yapay zekay\u0131 AOI ile entegre etmenin avantajlar\u0131n\u0131 daha derinlemesine inceleyin<\/span><\/span><\/span><\/a><\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
\n
\n
\n

Kusur Tespiti Yapay Zeka (AI) ile<\/h2>\n\n\n\n
AI tabanl\u0131 denetim ile geleneksel AOI kusur tespiti aras\u0131ndaki temel fark, empirik kurallara dayanmalar\u0131ndaki farkl\u0131l\u0131kt\u0131r. AI, yeni bir \u00e7\u0131rak gibi \u00e7al\u0131\u015f\u0131r ve belirli bir \u00f6l\u00e7\u00fcde usta bir zanaatk\u00e2r\u0131n denetim yeteneklerini taklit edebilir. AI, b\u00fcy\u00fck miktarda ge\u00e7erli veri kullanarak ve derin \u00f6\u011frenme<\/a> teknikleri ile sistem modelini e\u011fiterek, kusur aral\u0131klar\u0131n\u0131 ve anormal tespit modellerini otonom olarak tan\u0131mlayabilir. AI, kabul edilebilir (OK) ve kabul edilemez (NG) kusurlar i\u00e7in optimal parametreleri otomatik olarak belirleyebilir. Bu, bilinmeyen kusurlar\u0131n etkili bir \u015fekilde tespit edilmesini sa\u011flar, denetim standartlar\u0131nda tutarl\u0131l\u0131k sa\u011flar ve denetim do\u011frulu\u011funu b\u00fcy\u00fck \u00f6l\u00e7\u00fcde art\u0131r\u0131r.

End\u00fcstriler aras\u0131nda alan bilgisi farkl\u0131l\u0131klar\u0131 nedeniyle, belirli sekt\u00f6rler i\u00e7in AOI sistemlerini geli\u015ftiren geleneksel AOI m\u00fchendisleri, pratik saha sorunlar\u0131n\u0131 h\u0131zla \u00e7\u00f6zmede zorluklarla kar\u015f\u0131la\u015fabilirler. Bu nedenle, etkili \u00e7\u00f6z\u00fcmler genellikle sekt\u00f6re \u00f6zg\u00fc uygun AOI donan\u0131m ve kurallar\u0131n\u0131n tasarlanmas\u0131 i\u00e7in sekt\u00f6r uzmanlar\u0131yla i\u015fbirli\u011fi gerektirir. Buna kar\u015f\u0131n, AI tabanl\u0131 kusur tespiti sistemleri, tespit i\u00e7in gereken g\u00f6r\u00fcnt\u00fc \u00f6zelliklerini aray\u00fczler arac\u0131l\u0131\u011f\u0131yla \u00f6\u011frenir. Buna kar\u015f\u0131l\u0131k, yapay zeka tabanl\u0131 kusur tespit sistemleri<\/a>, aray\u00fczler arac\u0131l\u0131\u011f\u0131yla tespit i\u00e7in gerekli g\u00f6r\u00fcnt\u00fc \u00f6zelliklerini \u00f6\u011frenir. Yapay zeka sistemleri e\u011fitildikten sonra otonom olarak tespit kurallar\u0131 olu\u015fturabilir. Bu iki yakla\u015f\u0131m aras\u0131nda \u00f6\u011frenme verimlili\u011fi ve y\u00fcr\u00fctme g\u00fcc\u00fc a\u00e7\u0131s\u0131ndan \u00f6nemli farkl\u0131l\u0131klar vard\u0131r.

Derin \u00f6\u011frenme ile tespit do\u011frulu\u011funu optimize etmenin yan\u0131 s\u0131ra, AI teknolojisi, \u0131\u015f\u0131k kaynaklar\u0131n\u0131n tespit performans\u0131 \u00fczerindeki etkisiyle ilgili sorunlar\u0131 da ele al\u0131r. Geleneksel AOI sistemleri, genellikle \u0131\u015f\u0131k ko\u015fullar\u0131, g\u00f6r\u00fcnt\u00fcleme a\u00e7\u0131lar\u0131, g\u00f6lge yans\u0131malar\u0131 ve denetlenen nesnenin malzemesi ve \u015fekli (\u00f6zellikle yar\u0131 saydam malzemeler ve metal y\u00fczeyler) nedeniyle s\u0131n\u0131rlamalarla kar\u015f\u0131la\u015f\u0131r. Bu s\u0131n\u0131rlamalar, do\u011fru tespit sonu\u00e7lar\u0131n\u0131n elde edilmesini s\u0131k\u00e7a engeller. Buna kar\u015f\u0131n, AI tabanl\u0131 denetimin do\u011frulu\u011fu, \u0131\u015f\u0131k kaynaklar\u0131na daha az ba\u011f\u0131ml\u0131d\u0131r. Stabil bir \u0131\u015f\u0131k kayna\u011f\u0131 ile AI, bulan\u0131k konturlar, farkl\u0131 \u015fekiller ve yans\u0131yan metal malzemelerden gelen parazitlere ra\u011fmen etkili bir \u015fekilde kusur tespiti<\/a> ve s\u0131n\u0131fland\u0131rma<\/a> yapabilir.

AI tabanl\u0131 kusur tespiti, yans\u0131t\u0131c\u0131 nesnelerdeki \u00e7\u00f6kme ve \u00e7izikler gibi karma\u015f\u0131k y\u00fczey ve g\u00f6r\u00fcn\u00fcm kusurlar\u0131nda m\u00fckemmel performans sergiler. Ayr\u0131ca, AI, deforme olmu\u015f veya daha az tan\u0131nabilir karakterlerin denetimi gibi OCR (Optik Karakter Tan\u0131ma)<\/a> g\u00f6revlerinde de yetkin olabilir. Ayr\u0131ca, AI tabanl\u0131 sistemler, renk ve boyutlardaki de\u011fi\u015fiklikler, geni\u015f deformasyonlar, karma\u015f\u0131k \u015fekiller veya rastgele da\u011f\u0131lmalar gibi de\u011fi\u015fkenlere bak\u0131lmaks\u0131z\u0131n, tahmin edilemez desenler ve kusurlar\u0131 taramakta ustad\u0131r. AI, verileri kapsaml\u0131 bir \u015fekilde analiz ederek kusurlar\u0131n varl\u0131\u011f\u0131n\u0131 do\u011fru bir \u015fekilde belirler.

AI vizyon sistemleri<\/a>, geleneksel kural tabanl\u0131 AOI sistemlerine g\u00f6re h\u0131z, hassasiyet ve i\u015f g\u00fcc\u00fc maliyetleri a\u00e7\u0131s\u0131ndan \u00fcst\u00fcn performans sergiler, karma\u015f\u0131k tespit ve s\u0131n\u0131fland\u0131rma uygulamalar\u0131ndaki zorluklar\u0131 a\u015far.<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
\n
\n
\n

AI ile Kusur Tespiti \u00d6rnek Olay<\/h2>\n\n\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
\n
\n
\n
\u0130la\u00e7 end\u00fcstrisinde, blister paket \u00fcretim hatlar\u0131 genellikle saatte 5.000 ila 40.000 aras\u0131nda hap i\u015fler. Ancak, doldurma s\u0131ras\u0131nda hatalar meydana gelebilir ve bu, bo\u015f blisterler, d\u00fc\u015f\u00fck kaliteli i\u00e7erikler veya kaps\u00fcllerden toz d\u00f6k\u00fclmesi gibi kusurlara yol a\u00e7abilir. SolVision<\/a>\u2019da AI modellerini \u00e7e\u015fitli kusur g\u00f6r\u00fcnt\u00fcleriyle e\u011fiterek, her bir paket ve doldurma durumu h\u0131zla ve do\u011fru bir \u015fekilde tan\u0131mlanabilir, etiketlenebilir ve s\u0131n\u0131fland\u0131r\u0131labilir.<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
\n
\n
\n
Bu vaka \u00e7al\u0131\u015fmas\u0131nda AI kullanarak blister paket denetimi hakk\u0131nda daha fazla bilgi edinin<\/span><\/span><\/span><\/a><\/div>\n<\/div>\n<\/div>\n <\/div><\/div>","protected":false},"excerpt":{"rendered":"

AI ve AOI aras\u0131ndaki temel farklar\u0131 ke\u015ffedin ve geleneksel AOI’nin \u00f6tesinde kusur tespitini nas\u0131l devrim niteli\u011finde d\u00f6n\u00fc\u015ft\u00fcrd\u00fc\u011f\u00fcn\u00fc inceleyin. Bu derinlemesine inceleme, AI ve AOI aras\u0131ndaki ana farklar\u0131 ke\u015ffetmektedir.<\/p>","protected":false},"author":875,"featured_media":89323,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_gspb_post_css":"#gspb_row-id-gsbp-5aebb46{justify-content:space-between;margin-top:0;margin-bottom:0;display:flex;flex-wrap:wrap;min-height:250px;padding:0;overflow:hidden;background-size:cover;background-repeat:no-repeat;background-position:50% 68%;background-image:url(https:\/\/solomon-3d.mesvr.tw\/wp-content\/uploads\/2024\/01\/\u2014Pngtree\u2014technological-sense-geometric-line-simple_932581-1.jpg);filter:brightness(1) contrast(1) grayscale(0)}#gspb_row-id-gsbp-5aebb46>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}div[id^=gspb_col-id]{box-sizing:border-box;position:relative;padding:var(--gs-row-column-padding, 15px min(3vw, 20px))}body.gspb-bodyfront #gspb_row-id-gsbp-07a22fc>.gspb_row__content,body.gspb-bodyfront #gspb_row-id-gsbp-249db28>.gspb_row__content,body.gspb-bodyfront #gspb_row-id-gsbp-266e9b3>.gspb_row__content,body.gspb-bodyfront #gspb_row-id-gsbp-26f992e>.gspb_row__content,body.gspb-bodyfront #gspb_row-id-gsbp-2fbb568>.gspb_row__content,body.gspb-bodyfront #gspb_row-id-gsbp-44510c0>.gspb_row__content,body.gspb-bodyfront #gspb_row-id-gsbp-5365471>.gspb_row__content,body.gspb-bodyfront #gspb_row-id-gsbp-54aacdc>.gspb_row__content,body.gspb-bodyfront #gspb_row-id-gsbp-5aebb46>.gspb_row__content,body.gspb-bodyfront #gspb_row-id-gsbp-65a6d4d>.gspb_row__content,body.gspb-bodyfront #gspb_row-id-gsbp-82c1fd4>.gspb_row__content,body.gspb-bodyfront #gspb_row-id-gsbp-83837a5>.gspb_row__content,body.gspb-bodyfront #gspb_row-id-gsbp-ddad9e1>.gspb_row__content{max-width:var(--wp--style--global--wide-size, 1200px)}#gspb_row-id-gsbp-5aebb46:hover{background-size:cover}#gspb_col-id-gsbp-a43d08d.gspb_row__col--12{width:100%}@media (max-width:575.98px){#gspb_col-id-gsbp-a43d08d.gspb_row__col--12{width:100%}}#gspb_row-id-gsbp-2fbb568{min-height:100%}#gspb_row-id-gsbp-2fbb568>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}body.gspb-bodyfront #gspb_row-id-gsbp-2fbb568{z-index:10}#gspb_col-id-gsbp-f1762f9.gspb_row__col--6{width:50%}@media (max-width:767.98px){#gspb_col-id-gsbp-f1762f9.gspb_row__col--6{width:100%}}@media (max-width:575.98px){#gspb_col-id-gsbp-f1762f9.gspb_row__col--6{width:100%}}#gspb_col-id-gsbp-f1762f9.gspb_row__col--6{flex-direction:column}body #gspb_col-id-gsbp-f1762f9.gspb_row__col--6{display:flex;flex-direction:column;justify-content:center}#gspb_col-id-gsbp-7a4a754.gspb_row__col--6{width:50%}@media (max-width:767.98px){#gspb_col-id-gsbp-7a4a754.gspb_row__col--6{width:100%}}@media (max-width:575.98px){#gspb_col-id-gsbp-7a4a754.gspb_row__col--6{width:100%}}body #gspb_col-id-gsbp-7a4a754.gspb_row__col--6{display:flex;flex-direction:column;justify-content:flex-end}#gspb_row-id-gsbp-2fbb568,#gspb_row-id-gsbp-44510c0,#gspb_row-id-gsbp-65a6d4d,#gspb_row-id-gsbp-83837a5{justify-content:space-between;margin-top:0;margin-bottom:0;display:flex;flex-wrap:wrap}#gspb_row-id-gsbp-44510c0>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}#gspb_col-id-gsbp-047c80d.gspb_row__col--12{width:100%}@media (max-width:575.98px){#gspb_col-id-gsbp-047c80d.gspb_row__col--12{width:100%}}.gspb_container-id-gsbp-b2beeee{flex-direction:column;box-sizing:border-box}#gspb_container-id-gsbp-1b48ec5.gspb_container>p:last-of-type,#gspb_container-id-gsbp-1c26103.gspb_container>p:last-of-type,#gspb_container-id-gsbp-529ff3b.gspb_container>p:last-of-type,#gspb_container-id-gsbp-718facc.gspb_container>p:last-of-type,#gspb_container-id-gsbp-765a81d.gspb_container>p:last-of-type,#gspb_container-id-gsbp-9167946.gspb_container>p:last-of-type,#gspb_container-id-gsbp-9ca7df1.gspb_container>p:last-of-type,#gspb_container-id-gsbp-ae19e2f.gspb_container>p:last-of-type,#gspb_container-id-gsbp-b2beeee.gspb_container>p:last-of-type,#gspb_container-id-gsbp-f829605.gspb_container>p:last-of-type,#gspb_container-id-gsbp-fee0c95.gspb_container>p:last-of-type{margin-bottom:0}#gspb_container-id-gsbp-b2beeee.gspb_container{position:relative}.gspb_text-id-gsbp-040fecb{font-size:20px}#gspb_row-id-gsbp-83837a5>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}#gspb_col-id-gsbp-234410e.gspb_row__col--12{width:100%}@media (max-width:575.98px){#gspb_col-id-gsbp-234410e.gspb_row__col--12{width:100%}}.gspb_container-id-gsbp-1b48ec5{flex-direction:column;box-sizing:border-box}#gspb_container-id-gsbp-1b48ec5.gspb_container{position:relative}.gspb_text-id-gsbp-7f6c250{font-size:20px}#gspb_row-id-gsbp-65a6d4d>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}#gspb_col-id-gsbp-1fc92a7.gspb_row__col--12{width:100%}@media (max-width:575.98px){#gspb_col-id-gsbp-1fc92a7.gspb_row__col--12{width:100%}}#gspb_container-id-gsbp-529ff3b.gspb_container{position:relative}#gspb_button-id-gsbp-2f3c0b4{display:flex;justify-content:center}#gspb_button-id-gsbp-2f3c0b4 .gspb-buttonbox-text{display:flex;flex-direction:column}#gspb_button-id-gsbp-2f3c0b4>.gspb-buttonbox{box-sizing:border-box;padding:5px 30px;background-color:#e4002b;font-size:22px;text-align:center!important;font-weight:700!important;color:var(--wp--preset--color--white, #ffffff);border-style:solid;border-width:2px;border-color:#e4002b}#gspb_button-id-gsbp-2f3c0b4>.gspb-buttonbox:hover{background-color:var(--wp--preset--color--white, #ffffff)!important}#gspb_button-id-gsbp-2f3c0b4>.gspb-buttonbox .gsap-g-line{text-align:center!important}#gspb_button-id-gsbp-2f3c0b4>.gspb-buttonbox:hover{color:#e4002b;border-style:solid;border-width:2px;border-color:#e4002b}#gspb_button-id-gsbp-2f3c0b4>.gspb-buttonbox,#gspb_button-id-gsbp-2f3c0b4>.gspb-buttonbox>.gspb_backgroundOverlay{border-top-left-radius:20px;border-top-right-radius:20px;border-bottom-right-radius:20px;border-bottom-left-radius:20px}#gspb_row-id-gsbp-54aacdc,#gspb_row-id-gsbp-82c1fd4{justify-content:space-between;margin-top:0;margin-bottom:0;display:flex;flex-wrap:wrap}#gspb_row-id-gsbp-54aacdc>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}#gspb_col-id-gsbp-7782d90.gspb_row__col--12{width:100%}@media (max-width:575.98px){#gspb_col-id-gsbp-7782d90.gspb_row__col--12{width:100%}}.gspb_container-id-gsbp-529ff3b,.gspb_container-id-gsbp-ae19e2f{flex-direction:column;box-sizing:border-box}#gspb_container-id-gsbp-ae19e2f.gspb_container{position:relative}.gspb_text-id-gsbp-6886292{font-size:20px}#gspb_row-id-gsbp-82c1fd4>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}#gspb_col-id-gsbp-d860a2c.gspb_row__col--12{width:100%}@media (max-width:575.98px){#gspb_col-id-gsbp-d860a2c.gspb_row__col--12{width:100%}}#gspb_container-id-gsbp-718facc.gspb_container{position:relative}#gspb_image-id-gsbp-672ea67{text-align:center;height:auto}#gspb_image-id-gsbp-672ea67 img{vertical-align:middle;display:inline-block;box-sizing:border-box;max-width:100%;width:600px}@media (max-width:575.98px){#gspb_image-id-gsbp-672ea67 img{width:custom}}#gspb_image-id-gsbp-672ea67 img{height:auto}@media (max-width:991.98px){#gspb_image-id-gsbp-672ea67,#gspb_image-id-gsbp-672ea67 img{height:auto}}@media (max-width:767.98px){#gspb_image-id-gsbp-672ea67,#gspb_image-id-gsbp-672ea67 img{height:auto}}@media (max-width:575.98px){#gspb_image-id-gsbp-672ea67,#gspb_image-id-gsbp-672ea67 img{height:165px}}#gspb_row-id-gsbp-07a22fc,#gspb_row-id-gsbp-249db28{justify-content:space-between;margin-top:0;margin-bottom:0;display:flex;flex-wrap:wrap}#gspb_row-id-gsbp-249db28>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}#gspb_col-id-gsbp-2caca17.gspb_row__col--12{width:100%}@media (max-width:575.98px){#gspb_col-id-gsbp-2caca17.gspb_row__col--12{width:100%}}.gspb_container-id-gsbp-718facc,.gspb_container-id-gsbp-f829605{flex-direction:column;box-sizing:border-box}#gspb_container-id-gsbp-f829605.gspb_container{position:relative}.gspb_text-id-gsbp-5a36a15{font-size:20px}#gspb_row-id-gsbp-07a22fc>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}#gspb_col-id-gsbp-de33bf0.gspb_row__col--12{width:100%}@media (max-width:575.98px){#gspb_col-id-gsbp-de33bf0.gspb_row__col--12{width:100%}}#gspb_container-id-gsbp-765a81d.gspb_container{position:relative}#gspb_button-id-gsbp-260cb2e{display:flex;justify-content:center}#gspb_button-id-gsbp-260cb2e .gspb-buttonbox-text{display:flex;flex-direction:column}#gspb_button-id-gsbp-260cb2e>.gspb-buttonbox{box-sizing:border-box;padding:5px 30px;background-color:#e4002b;font-size:22px;text-align:center!important;font-weight:700!important;color:var(--wp--preset--color--white, #ffffff);border-style:solid;border-width:2px;border-color:#e4002b}#gspb_button-id-gsbp-260cb2e>.gspb-buttonbox:hover{background-color:var(--wp--preset--color--white, #ffffff)!important}#gspb_button-id-gsbp-260cb2e>.gspb-buttonbox .gsap-g-line{text-align:center!important}#gspb_button-id-gsbp-260cb2e>.gspb-buttonbox:hover{color:#e4002b;border-style:solid;border-width:2px;border-color:#e4002b}#gspb_button-id-gsbp-260cb2e>.gspb-buttonbox,#gspb_button-id-gsbp-260cb2e>.gspb-buttonbox>.gspb_backgroundOverlay{border-top-left-radius:20px;border-top-right-radius:20px;border-bottom-right-radius:20px;border-bottom-left-radius:20px}#gspb_row-id-gsbp-266e9b3,#gspb_row-id-gsbp-26f992e,#gspb_row-id-gsbp-5365471,#gspb_row-id-gsbp-ddad9e1{justify-content:space-between;margin-top:0;margin-bottom:0;display:flex;flex-wrap:wrap}#gspb_row-id-gsbp-5365471>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}#gspb_col-id-gsbp-c584400.gspb_row__col--12{width:100%}@media (max-width:575.98px){#gspb_col-id-gsbp-c584400.gspb_row__col--12{width:100%}}.gspb_container-id-gsbp-765a81d,.gspb_container-id-gsbp-9ca7df1{flex-direction:column;box-sizing:border-box}#gspb_container-id-gsbp-9ca7df1.gspb_container{position:relative}.gspb_text-id-gsbp-f1f76e4{font-size:20px}#gspb_row-id-gsbp-266e9b3>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}#gspb_col-id-gsbp-39b6cec.gspb_row__col--12{width:100%}@media (max-width:575.98px){#gspb_col-id-gsbp-39b6cec.gspb_row__col--12{width:100%}}#gspb_container-id-gsbp-9167946.gspb_container{position:relative}#gspb_row-id-gsbp-26f992e>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}#gspb_col-id-gsbp-69590a8.gspb_row__col--12{width:100%}@media (max-width:575.98px){#gspb_col-id-gsbp-69590a8.gspb_row__col--12{width:100%}}.gspb_container-id-gsbp-1c26103,.gspb_container-id-gsbp-9167946{flex-direction:column;box-sizing:border-box}#gspb_container-id-gsbp-1c26103.gspb_container{position:relative}.gspb_text-id-gsbp-7176a78{font-size:20px}#gspb_row-id-gsbp-ddad9e1>.gspb_row__content{display:flex;justify-content:space-between;margin:0 auto;width:100%;flex-wrap:wrap}.gspb_row{position:relative}#gspb_col-id-gsbp-84f0b69.gspb_row__col--12{width:100%}@media (max-width:575.98px){#gspb_col-id-gsbp-84f0b69.gspb_row__col--12{width:100%}}.gspb_container-id-gsbp-fee0c95{flex-direction:column;box-sizing:border-box}#gspb_container-id-gsbp-fee0c95.gspb_container{position:relative}#gspb_button-id-gsbp-eda4edc{display:flex;justify-content:center}#gspb_button-id-gsbp-eda4edc .gspb-buttonbox-text{display:flex;flex-direction:column}#gspb_button-id-gsbp-eda4edc>.gspb-buttonbox{box-sizing:border-box;padding:5px 30px;background-color:#e4002b;font-size:22px;text-align:center!important;font-weight:700!important;color:var(--wp--preset--color--white, #ffffff);border-style:solid;border-width:2px;border-color:#e4002b}#gspb_button-id-gsbp-eda4edc>.gspb-buttonbox:hover{background-color:var(--wp--preset--color--white, #ffffff)!important}#gspb_button-id-gsbp-eda4edc>.gspb-buttonbox .gsap-g-line{text-align:center!important}#gspb_button-id-gsbp-eda4edc>.gspb-buttonbox:hover{color:#e4002b;border-style:solid;border-width:2px;border-color:#e4002b}#gspb_button-id-gsbp-eda4edc>.gspb-buttonbox,#gspb_button-id-gsbp-eda4edc>.gspb-buttonbox>.gspb_backgroundOverlay{border-top-left-radius:20px;border-top-right-radius:20px;border-bottom-right-radius:20px;border-bottom-left-radius:20px}","footnotes":""},"categories":[3756],"tags":[],"class_list":["post-90464","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"acf":[],"lang":"tr","translations":{"tr":90464,"zh":80357,"tw":51282,"en":76368,"es":83339,"jp":85901,"pt":90064,"de":90938,"fr":92719,"vi":93985,"th":96971,"it":98410,"ko":95155},"_links":{"self":[{"href":"https:\/\/solomon-3d.mesvr.tw\/tr\/wp-json\/wp\/v2\/posts\/90464","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/solomon-3d.mesvr.tw\/tr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/solomon-3d.mesvr.tw\/tr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/solomon-3d.mesvr.tw\/tr\/wp-json\/wp\/v2\/users\/875"}],"replies":[{"embeddable":true,"href":"https:\/\/solomon-3d.mesvr.tw\/tr\/wp-json\/wp\/v2\/comments?post=90464"}],"version-history":[{"count":0,"href":"https:\/\/solomon-3d.mesvr.tw\/tr\/wp-json\/wp\/v2\/posts\/90464\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/solomon-3d.mesvr.tw\/tr\/wp-json\/wp\/v2\/media\/89323"}],"wp:attachment":[{"href":"https:\/\/solomon-3d.mesvr.tw\/tr\/wp-json\/wp\/v2\/media?parent=90464"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/solomon-3d.mesvr.tw\/tr\/wp-json\/wp\/v2\/categories?post=90464"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/solomon-3d.mesvr.tw\/tr\/wp-json\/wp\/v2\/tags?post=90464"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}