AWS發佈五大用於工業領域的機器學習服務

{"type":"doc","content":[{"type":"bulletedlist","content":[{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"italic"}],"text":"Amazon Monitron提供包含傳感器、網關和機器學習服務的端到端機器監控解決方案,以檢測可能需要維護的異常設備狀況"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"italic"}],"text":"Amazon Lookout for Equipment爲擁有設備傳感器的客戶提供了使用AWS機器學習模型來檢測異常設備行爲並進行預測性維護的能力"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"italic"}],"text":"AWS Panorama Appliance幫助已在工業設施中裝配攝像機的客戶使用計算機視覺來改善質量控制和工作場所安全"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"italic"}],"text":"AWS Panorama軟件開發套件(SDK)允許工業相機制造商在新相機中嵌入計算機視覺功能"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"italic"}],"text":"Amazon Lookout for Vision在圖像和視頻流上使用AWS訓練的計算機視覺模型,以發現產品或流程中的異常和缺陷"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"italic"}],"text":"使用全新的AWS工業機器學習服務的客戶和合作夥伴包括Axis、凌華科技、BP、德勤、Fender芬達、GE 醫療和西門子交通"}]}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"北京"},{"type":"text","text":"-2020"},{"type":"text","text":"年"},{"type":"text","text":"12"},{"type":"text","text":"月"},{"type":"text","text":"9"},{"type":"text","text":"日,今天,在亞馬遜雲服務("},{"type":"text","text":"AWS"},{"type":"text","text":")舉辦的年度盛會"},{"type":"text","text":"——AWS re:Invent"},{"type":"text","text":"上,"},{"type":"text","text":"AWS"},{"type":"text","text":"宣佈了"},{"type":"text","marks":[{"type":"strong"}],"text":"Amazon Monitron"},{"type":"text","marks":[{"type":"strong"}],"text":"、"},{"type":"text","marks":[{"type":"strong"}],"text":"Amazon Lookout for Equipment"},{"type":"text","marks":[{"type":"strong"}],"text":"、"},{"type":"text","marks":[{"type":"strong"}],"text":"AWS Panorama Appliance"},{"type":"text","marks":[{"type":"strong"}],"text":"、"},{"type":"text","marks":[{"type":"strong"}],"text":"AWS Panorama SDK"},{"type":"text","marks":[{"type":"strong"}],"text":"和"},{"type":"text","marks":[{"type":"strong"}],"text":"Amazon Lookout for Vision"},{"type":"text","text":"。這五項全新的機器學習服務共同幫助工業和製造業客戶在其生產過程中嵌入智能能力,以提高運營效率,改善質量控制、信息安全和工作場所安全。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"這些服務代表了現有最全面的從雲端到邊緣的工業機器學習服務套件,通過結合先進的機器學習、傳感器分析和計算機視覺功能,解決工業客戶面臨的常見技術挑戰。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"實際上,數十萬客戶正在使用"},{"type":"text","text":"AWS"},{"type":"text","text":"雲服務進行機器學習工作,各個規模、各行各業的客戶都在使用"},{"type":"text","text":"AWS"},{"type":"text","text":"服務將機器學習作爲其業務戰略的核心。"},{"type":"text","marks":[{"type":"strong"}],"text":"對於此,"},{"type":"text","marks":[{"type":"strong"}],"text":"AWS"},{"type":"text","marks":[{"type":"strong"}],"text":"大中華區雲服務產品管理總經理顧凡先生在"},{"type":"text","marks":[{"type":"strong"}],"text":"2020亞馬遜re:Invent Swami主題演講專場媒體溝通會中"},{"type":"text","marks":[{"type":"strong"}],"text":"提到“機器學習領域今天有非常多的服務和功能,這些其實都是工具。而這些機器學習的工具已經被越來越多的行業客戶採用,在更多場景幫到他的業務。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"爲什麼會有超過10萬的客戶選擇在AWS上跑這些機器學習的工作負載呢?其實如果大家去看AWS的整個機器學習領域的服務,會發現幾個特點。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"第一,整個服務的寬度和深度具有明顯優勢。我們針對機器學習中的Righttools for the right job(合適的工具做合適的事兒,一把鑰匙開一把鎖),就是希望你在運行機器學習相關工作時,能夠在相應場景下應該選擇工具箱中最適合的工具。這反映出我們服務的寬度和深度優勢。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"第二,AWS在雲計算以及在機器學習領域裏始終抱持開放的心態,所以大家會看到我們的很多工具是非常開放的,可以跟客戶的整個環境做到非常好的集成。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"第三,AWS在配合客戶的時候,一般都是兩個原則,一個原則是授人以魚不如授人以漁,我們希望幫到客戶把能力建立起來,給他工具並教會他使用工具。第二是在產品原型實現、在工程方面有差距的時候,如果客戶需要幫忙,我們會幫客戶扶上馬再送一程,幫他快速的把一些業務解決方案用產品原型的方式實現。”"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"要了解有關全新"},{"type":"text","text":"AWS"},{"type":"text","text":"用於工業領域的機器學習服務的更多信息,請訪問"},{"type":"link","attrs":{"href":"https:\/\/aws.amazon.com\/industrial\/","title":"","type":null},"content":[{"type":"text","text":"https:\/\/aws.amazon.com\/industrial\/"}]},{"type":"text","text":"。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"企業越來越多地希望將機器學習功能添加到工業環境中,例如製造設施、配送中心、食品加工廠等。對於這些客戶來說,數據已成爲將複雜工業系統結合在一起的重要媒介。工業系統中通常具有許多相互依存的流程,這些流程容錯能力低,甚至很小的問題也會帶來重大後果。許多客戶通過分析其設施中運行設備的數據來應對這一挑戰,例如,許多客戶利用"},{"type":"text","text":"AWS IoT SiteWise"},{"type":"text","text":"等服務從工業設備收集數據並生成實時性能指標。隨着客戶開始使用雲收集和分析工業數據,他們還希望採用機器學習技術來解讀數據,進一步提高運營效率。在某些情況下,客戶希望使用機器學習來幫助他們實現預測性維護,從而降低成本並提高運營效率。同時,在非聯網或對延遲敏感的環境中運行的客戶則希望通過在邊緣使用計算機視覺來發現產品缺陷並提高工作場所安全性。伴隨這些不斷變化的需求和機遇,工業企業要求"},{"type":"text","text":"AWS"},{"type":"text","text":"幫助他們利用雲、工業邊緣和機器學習,以從其設備生成的大量數據中獲得更多價值。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"AmazonMonitron"},{"type":"text","marks":[{"type":"strong"}],"text":"和"},{"type":"text","marks":[{"type":"strong"}],"text":"Amazon Lookout for Equipment"},{"type":"text","marks":[{"type":"strong"}],"text":"通過機器學習支持預測性維護"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"今天,工業和製造企業面臨的主要挑戰是設備的持續維護。過去大多數設備維護都是被動的(在機器發生故障之後)或預防性的(定期進行以確保機器不會發生故障)。被動維護可能會損失大量成本並帶來長時間停機,而預防性維護若維護過度則成本過高,若維護不夠頻繁則無法防止故障。實際上,預測性維護(能夠預測設備何時可能需要維護的能力)是一種更有前景的解決方案。但是,爲了實現預測性維護,企業在過去需要僱傭熟練的技術人員和數據科學家從頭構建複雜的解決方案,同時需要針對用例識別和購買正確類型的傳感器,並將它們與"},{"type":"text","text":"IoT"},{"type":"text","text":"網關(一種聚合和傳輸數據的設備)連接在一起。然後,公司必須測試監測系統,並將數據傳輸到本地或雲上進行處理。只有這樣,數據科學家才能構建機器學習模型來分析數據模式和異常情況,或者在檢測到異常時創建警報系統。一些企業已經爲在設備和必要的基礎設施上安裝傳感器用於數據連接、存儲、分析和警報方面進行了大量投資,然而,即使這些企業也通常僅停留在使用初級數據分析和建模方法的階段,與高級機器學習模型相比,這些方法昂貴且通常無法有效地檢測異常情況。大部分企業依然缺乏專業知識和人員來構建和完善機器學習模型,無法進行高度準確的預測性維護。這些都導致了很少有企業能夠成功實施預測性維護,即使少數做到這一點的企業也希望讓這些投資進一步發揮作用,同時減輕維護解決方案的負擔。在這些問題上,全新的"},{"type":"text","text":"AWS"},{"type":"text","text":"機器學習服務可以提供衆多幫助:"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"bulletedlist","content":[{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"對於未建立傳感器網絡的客戶,Amazon Monitron提供由傳感器、網關和機器學習服務組成的端到端機器監控系統,以檢測異常並預測何時需要維護工業設備。 Amazon Monitron幫助客戶免去了從頭開始構建先進的、由機器學習驅動的預測性維護系統的高成本需求和複雜性,使他們能夠專注於其核心製造、供應鏈和運營功能。Amazon Monitron根據振動或溫度的異常波動來檢測機器是否正常運行,並在可能出現故障時通知客戶檢查機器以確定是否需要預測性維護。這一端到端的系統提供了用於捕獲振動和溫度數據的IoT傳感器、用於將數據聚合和傳輸到AWS的網關、以及用於檢測異常設備模式並在數分鐘內提供結果的機器學習雲服務,而無需客戶具備任何機器學習或雲經驗。藉助Amazon Monitron,機器維護人員無需任何開發工作或專業培訓就可以在數小時內開始跟蹤機器的運行狀況。Amazon Monitron可在軸承、電機、泵、傳送帶各種工業和製造領域的旋轉設備上使用,其典型應用場景包括數據中心冷卻風扇或水泵等關鍵機器的監測,或者大量安裝在具有生產和運輸系統的製造工廠中。Amazon Monitron還提供一個移動應用程序,供客戶的現場維護技術人員實時監控設備行爲。技術人員可以通過這個移動應用程序收到不同機器上任何異常設備狀況的警報,檢查機器的運行狀況,並決定是否需要安排維護。爲了提高系統的準確性,技術人員還可以在移動應用程序中輸入有關警報準確性的反饋,幫助進一步改善Amazon Monitron。Amazon Monitron已經正式推出。要了解有關Amazon Monitron的更多信息,請訪問"},{"type":"link","attrs":{"href":"https:\/\/aws.amazon.com\/monitron","title":"","type":null},"content":[{"type":"text","text":"https:\/\/aws.amazon.com\/monitron"}]},{"type":"text","text":"。"}]}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"bulletedlist","content":[{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"對於已經擁有傳感器但不希望自己構建機器學習模型的客戶,AmazonLookout for Equipment讓客戶可以將傳感器數據發送到AWS,由AWS爲其構建模型並返回預測結果,從而檢測異常設備行爲。首先,客戶將其傳感器數據上傳到AmazonSimple Storage Service (S3),並將S3位置提供給Amazon Lookout for Equipment。 Amazon Lookoutfor Equipment也可以從AWS IoT SiteWise提取數據,並與OSIsoft等其他流行的機器操作系統無縫協作。 Amazon Lookout forEquipment分析數據,評估正常或健康的模式,再利用從所有訓練數據中得到的洞察來構建爲客戶環境定製的模型。然後,Amazon Lookout for Equipment可以使用機器學習模型來分析傳入的傳感器數據並識別機器故障的預警信號。這也就使得客戶可以進行預測性維護,從而通過防止工業系統生產線崩潰來節省成本並提高生產率。 Amazon Lookout for Equipment幫助客戶從其現有傳感器中獲得更多價值,使得客戶能夠及時做出從根本上改善整個工業流程的決策。要了解有關Amazon Lookout for Equipment的更多信息,請訪問"},{"type":"link","attrs":{"href":"https:\/\/aws.amazon.com\/lookout-for-equipment","title":"","type":null},"content":[{"type":"text","text":"https:\/\/aws.amazon.com\/lookout-for-equipment"}]},{"type":"text","text":"。"}]}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"AWS Panorama"},{"type":"text","marks":[{"type":"strong"}],"text":"通過計算機視覺改善工業運營和工作場所安全"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"許多工業和製造業客戶希望在其設施和設備的實時視頻中使用計算機視覺技術自動執行監測或視覺檢查任務,並實時做出決策。例如,客戶通常需要檢查一些高速運轉的流程(例如精細銑削或激光工具)以確定是否需要進行調整,或者監視工地上和工廠的活動以確保操作合規(例如,確保行人和叉車留在指定的工作區域內),或評估其設施內的工人安全(例如,保持適當的人員距離或使用"},{"type":"text","text":"PPE"},{"type":"text","text":")。但是,當下普遍使用的監測手段是手動的,容易出錯的,並且難以擴展。客戶可以在雲中構建計算機視覺模型來監視和分析他們的實時視頻,但是工業設施和流程通常位於偏遠和孤立的位置,網路連接很慢、昂貴或完全不存在。尤其對於那些涉及零件或安全監控視頻審查等人工審覈的工業流程,在雲中構建計算機視覺模型更爲困難。例如,如果某個高吞吐量的生產線上出現質量問題,客戶希望立即得到預警,因爲問題存在時間越長,解決問題的成本越高。這種類型的監控視頻可以通過計算機視覺技術實現在雲中自動處理,但是這些視頻一般帶寬高並且上載速度慢。因此,客戶只能實時進行視頻監控,但這一方式操作難度高、易出錯並且成本高。有些客戶希望使用具有足夠處理能力的智能相機來運行實時監控模型,卻很難達到高準確性、低延遲的性能。大多數客戶最終會運行一些簡單的模型,卻無法編程爲可以集成到工業機器中的自定義代碼。針對這些問題,"},{"type":"text","text":"AWS"},{"type":"text","text":"現在可以提供以下幫助:"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"bulletedlist","content":[{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"AWSPanorama Appliance"},{"type":"text","text":"提供了一種新的硬件設備,使組織可以將計算機視覺添加到客戶可能已經部署在本地的攝像機中。客戶首先將AWS Panorama Appliance連接到他們的網絡,然後這一設備會自動識別攝像頭數據流並開始與現有的工業攝像頭進行交互。AWS Panorama Appliance可集成於那些用於構建自定義機器學習模型或獲取視頻以進行更精細分析的AWS機器學習服務和IoT服務中。AWSPanorama Appliance將AWS機器學習能力擴展到邊緣,以幫助客戶在沒有網絡連接的情況下在本地進行預測。每個AWS Panorama Appliance都可在多個攝像頭數據流上並行運行計算機視覺模型,從而使諸如質量控制、零件識別和工作場所安全的用例成爲可能。AWS Panorama Appliance還可與適用於零售、製造、建築和其他行業的AWS和第三方經過預先培訓的計算機視覺模型一起使用。此外,客戶使用Amazon SageMaker自主開發的計算機視覺模型也可以部署在AWSPanorama Appliance上。"}]}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"bulletedlist","content":[{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"AWSPanorama軟件開發套件(SDK)"},{"type":"text","text":"幫助硬件供應商開發可在邊緣有效運行計算機視覺模型的新型攝像頭。使用AWSPanorama SDK構建的攝像頭可在多種用例中運行計算機視覺模型,例如檢測快速移動的傳送帶上的損壞部件或定位那些脫離指定工作區域的器械等。這些相機可以使用英偉達和安霸旗下用於計算機視覺的芯片。通過使用AWS Panorama SDK,製造商可以開發自帶計算機視覺模型的相機,從而可以處理更高分辨率的高質量視頻以發現問題。他們還可以在低成本設備上構建更復雜的模型,這些設備可以通過以太網供電並可以放置在站點周圍。客戶可在Amazon SageMaker中訓練模型,並一鍵將其部署到使用AWS PanoramaSDK構建的攝像機上。客戶還可以將Lambda功能添加到使用AWSPanorama SDK構建的攝像頭中,以通過文本或電子郵件提醒潛在問題。 AWS還提供用於PPE檢測和保持人員距離等任務的預構建模型,並且可以在幾分鐘內部署這些模型,而無需進行任何機器學習工作或特殊優化。"}]}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"要了解更多關於AWS Panorama或其支持供應商和合作夥伴的信息,可訪問https:\/\/aws.amazon.com\/panorama。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"Amazon Lookoutfor Vision"},{"type":"text","marks":[{"type":"strong"}],"text":"可以低成本自動、快速、準確地對圖像和視頻進行視覺異常檢測"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"AWS客戶非常希望將計算機視覺部署到攝像頭中以用於質量控制。工業企業必須保持不斷的努力進行質量控制。僅在製造業中,由於忽略某些細微錯誤而導致的生產線停產每年導致數百萬美元的成本超支和收入損失。工業流程中的外觀檢查通常需要人工操作,這可能非常乏味且標準不一。計算機視覺技術可以保證持續識別外觀缺陷所需的速度和準確性,但實施過程卻可能非常複雜,並需要數據科學家團隊來構建、部署和管理機器學習模型。由於這些侷限,由機器學習支持的視覺異常系統對絕大多數企業而言仍然遙不可及。現在, AWS可在以下領域幫助到這些企業:"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"bulletedlist","content":[{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"Amazon Lookout for Vision"},{"type":"text","text":"爲客戶提供了一種高精度、低成本的異常檢測解決方案,可以通過機器學習技術每小時處理數千張圖像以發現缺陷和異常。客戶將攝像頭圖像批量或實時發送到Amazon Lookout for Vision以識別異常,例如機器部件的裂紋、面板上的凹痕、不規則形狀或產品上的顏色錯誤等。然後,Amazon Lookout for Vision報告與基線不同的圖像,以便客戶採取適當的措施。Amazon Lookout for Vision有強大的技術能力可以處理因工作環境變化而引起的相機角度、方位和照明方面的差異。客戶可以通過至少提供30張“良好”狀態的圖像建立基線,準確、一致地評估機械零件或製成品。Amazon Lookout for Vision也可以在Amazon Panorama設備上運行。即日起客戶可在AWS中運行Amazon Lookout for Vision。從明年開始,客戶還將可以在AWS Panorama Appliances和其他AWS Panorama設備上運行Amazon Lookout for Vision,從而可以在網絡連接受限或無網絡連接的環境中使用Amazon Lookout for Vision。要了解有關AmazonLookout for Vision的更多信息,請訪問"},{"type":"link","attrs":{"href":"https:\/\/aws.amazon.com\/lookout-for-vision","title":"","type":null},"content":[{"type":"text","text":"https:\/\/aws.amazon.com\/lookout-for-vision"}]},{"type":"text","text":"。"}]}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"“"},{"type":"text","text":"工業和製造業客戶需要持續應對來自股東、客戶、政府和競爭對手的壓力,要求他們降低成本,提高質量並保持合規性。這些組織希望利用雲和機器學習來實現流程自動化並增強整個運營流程中的人員能力,但是構建這些系統可能出錯率高、複雜、耗時且昂貴,"},{"type":"text","text":"”"},{"type":"text","text":"負責亞馬遜機器學習的"},{"type":"text","text":"AWS"},{"type":"text","text":"副總裁"},{"type":"text","text":"SwamiSivasubramanian"},{"type":"text","text":"說,"},{"type":"text","text":"“"},{"type":"text","text":"我們很高興爲客戶帶來五項針對工業用途的全新機器學習服務。這些服務易於安裝、部署、快速啓動和運行,並將雲和邊緣相連,將助力工業客戶打造未來智慧工廠。"},{"type":"text","text":"”"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"對於此,"},{"type":"text","text":"AWS"},{"type":"text","text":"大中華區機器學習產品總監代聞在"},{"type":"text","text":"2020"},{"type":"text","text":"亞馬遜"},{"type":"text","text":"re:Invent Swami"},{"type":"text","text":"主題演講專場媒體溝通會中以一個鉛筆廠作爲例子,講述了上述機器學習服務聯合使用的工業場景。"},{"type":"text","text":"“"},{"type":"text","text":"製作鉛筆是一個低利潤而高壓的過程。過程中首先需要很大的壓縮機來生產鉛筆,然後再用一個紅顏色的上色器給鉛筆上色,之後再補鉛芯,最後還需要用特定的齒輪來削鉛筆。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"這個過程中,首先可以用"},{"type":"text","text":"Lookout for Equipment"},{"type":"text","text":",利用所有黃色的數值去建一個模型,當一個數值出現問題或者維度出現問題的時候就代表轉速出現問題,於是會出現預警,通知工作人員處理。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"第二,很多老的機械沒有傳感器,我們可以貼上"},{"type":"text","text":"Monitron"},{"type":"text","text":"對它的溫度和振動進行建模和判斷。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"第三,鉛出來以後,你總得判斷鉛筆是不是正常的鉛筆,筆芯是不是在正中間,我們可以用"},{"type":"text","text":"Lookout for Vision"},{"type":"text","text":"分辨哪些鉛筆是正常的,哪些是不正常的,只需上傳"},{"type":"text","text":"30"},{"type":"text","text":"張鉛筆的圖像就可以獲得基礎模型,進而投產。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"而剛纔提到的"},{"type":"text","text":"Panorama Appliance"},{"type":"text","text":"可以用來監測整個生產線的狀態,包括你旁邊的貨物。更進一步,"},{"type":"text","text":"Panorama Appliance"},{"type":"text","text":"可以用監控整個廠區,比如你的貨物已經剩"},{"type":"text","text":"80%"},{"type":"text","text":"了,生產的效率是"},{"type":"text","text":"65"},{"type":"text","text":"箱每分鐘等數據,都是可以看出來的。通過這個例子就可以完成整個的陳舊的鉛筆生產過程的"},{"type":"text","text":"AI"},{"type":"text","text":"化。”代聞說到。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"芬達樂器公司("},{"type":"text","text":"Fender Musical Instruments Corporation"},{"type":"text","text":")是吉他、貝斯、放大器和相關設備的全球領先製造商和標誌性品牌。芬達基礎設施全球總監"},{"type":"text","text":"Bill Holmes"},{"type":"text","text":"表示,"},{"type":"text","text":"“"},{"type":"text","text":"在過去的一年中,我們與"},{"type":"text","text":"AWS"},{"type":"text","text":"共同針對設備狀態檢查進行了很多努力,這是對成功的製造業務而言非常關鍵卻容易被忽略的部分。對於全球製造商而言,維持設備正常運行時間是在全球市場上保持競爭力的唯一途徑。由於設備故障的緊急性,計劃外的停機會給生產和勞動力造成巨大的損失。"},{"type":"text","text":"Amazon Monitron"},{"type":"text","text":"讓大型工業製造商以及小型家族企業都能具備設備故障預測的能力,有機會搶先安排設備維修。"},{"type":"text","text":"”"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"斗山工程機械是全球領先的重型設備和發動機製造商。斗山工程機械戰略副總裁"},{"type":"text","text":"Jaeyeon Cho"},{"type":"text","text":"表示,"},{"type":"text","text":"“AI"},{"type":"text","text":"在推進斗山下一代設備開發方面至關重要,因此我們正與"},{"type":"text","text":"AWS"},{"type":"text","text":"合作開發可利用自動化和可擴展機器學習的用例。很高興繼續與"},{"type":"text","text":"AWS"},{"type":"text","text":"合作,在我們的下一代"},{"type":"text","text":"IoT"},{"type":"text","text":"平臺中利用"},{"type":"text","text":"Amazon Lookout for Equipment"},{"type":"text","text":"。"},{"type":"text","text":"”"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Amazon.com Middle Mile Production Technology"},{"type":"text","text":"副總裁"},{"type":"text","text":"Steve Armato"},{"type":"text","text":"表示,"},{"type":"text","text":"“"},{"type":"text","text":"每個月有數百萬輛卡車進入亞馬遜工廠,因此使用自動化拖車裝卸和停車的技術非常重要。"},{"type":"text","text":"Amazon’s Middle Mile Products & Technology (MMPT) "},{"type":"text","text":"已開始使用"},{"type":"text","text":"AWS Panorama"},{"type":"text","text":"來識別車牌,自動加快駕駛員的出入手續,從而使這些車輛可以安全、快速地進入亞馬遜站點,確保爲客戶提供更快的配送速度。"},{"type":"text","text":"”"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"BP是一家全球性能源企業,爲客戶提供運輸用燃料,熱能和光能,潤滑油以及用於製造油漆、服裝、包裝物等日常用品的石化產品。BP在全球擁有18,000個服務站和74,000多名員工。BP美國首席技術官Grant Matthews說:“我們位於bpx的工程團隊正與AWS緊密合作,以構建一個物聯網和雲平臺,助力BP持續提高運營效率。作爲這項工作的一部分,我們也在探索通過計算機視覺輔助提高安全性和工作人員安全。我們希望利用計算機視覺實現卡車自動化進出工廠,確認它們已完成正確的訂單。此外,我們還在監控人員距離、設置動態禁區和檢測石油泄漏等方面看到了通過計算機視覺輔助保護工人安全的可能性。AWS Panorama創新地實現了在單一硬件平臺上以直觀的用戶體驗提供所有這些解決方案。我們的團隊非常高興與AWS一起使用這項新技術,並期望解決許多新的用例。”"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"西門子交通爲市內、城市間運輸和貨運提供智能高效的移動解決方案。"},{"type":"text","text":"“"},{"type":"text","text":"在過去的"},{"type":"text","text":"160"},{"type":"text","text":"年中,西門子交通在無縫、可持續和安全的運輸解決方案領域持續處於領導地位。西門子"},{"type":"text","text":"ITS"},{"type":"text","text":"數字實驗室負責將最新的數字技術帶入交通行業,並處於向公共機構提供數據分析和"},{"type":"text","text":"AI"},{"type":"text","text":"解決方案的獨特位置。"},{"type":"text","text":"”"},{"type":"text","text":"西門子交通"},{"type":"text","text":"ITS"},{"type":"text","text":"數字實驗室創新經理"},{"type":"text","text":"LauraSanchez"},{"type":"text","text":"表示,"},{"type":"text","text":"“"},{"type":"text","text":"隨着城市面臨新的挑戰,市政部門希望西門子交通幫助他們進行創新。城市想了解如何有效地管理資產並改善擁堵和直接交通。我們希望使用"},{"type":"text","text":"AWS Panorama"},{"type":"text","text":"將計算機視覺帶入現有的安全攝像頭中,以監控交通並智能分配路邊空間,幫助城市優化停車和交通,改善居民的生活質量。"},{"type":"text","text":"”"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"GE "},{"type":"text","text":"醫療是全球領先的醫療技術和數字解決方案的創新者,致力於開發、製造和分銷診斷成像劑、放射性藥物、"},{"type":"text","text":"CT"},{"type":"text","text":"和"},{"type":"text","text":"MRI"},{"type":"text","text":"機器等醫療診斷設備、以及由其"},{"type":"text","text":"Edison"},{"type":"text","text":"數字醫療智能平臺支持的智能設備。"},{"type":"text","text":" “"},{"type":"text","text":"今天,我們通過人工檢驗醫療設備的質量。爲了提升我們的品牌併爲醫療保健專業人員提供值得信任的一流產品,我們很高興能夠通過"},{"type":"text","text":"Amazon Lookout for Vision"},{"type":"text","text":"探索以編程方式提高"},{"type":"text","text":"GE"},{"type":"text","text":"醫療日本工廠產品缺陷檢測的速度、一致性和準確性的可能性,短期內還可能應用於全球其他區域的工廠中。"},{"type":"text","text":"”GE"},{"type":"text","text":"醫療日本工廠經理、產線運營官和總經理"},{"type":"text","text":"Kozaburo Fujimoto"},{"type":"text","text":"說。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}}]}
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