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    機器學習改進供應鏈的十種方法

    forbes 托比網申飛譯 2019-05-05 17:35:48

    企業使用機器學習技術可以在今時今日實現兩位數的增長。這些革命供應鏈管理的場景包括:預測錯誤率,按需調節生產力;節省成本指出,及時的交付等等方面。

    機器學習的算法和模型基于從大數據集中發現異常,模式乃至預判。許多供應鏈挑戰都離不開時間、成本和資源等要素的制約,這使得機器學習成為解決這些問題的理想技術。

    無論是亞馬遜機器人系統(倉儲自動化機器人)通過機器學習提升準確率,速度和規模;還是DHL依賴AI和機器學習技術賦能其可預測性網絡管理系統——一套從內部數據的58個要素中尋找出影響交期延遲首要因素的系統,都通過機器學習定義了下一代供應鏈管理系統。Gartner預測,到2020年將有95%的SCP(Supply Chain Planning)廠商將在其解決方案中納入機器學習技術。而2023年,智能算法,AI技術將嵌入超過25%的供應鏈技術解決方案。

    以下是機器學習影響供應鏈管理的十種場景

    1)以機器學習為基礎的算法將成為下一代物流技術的基礎,通過先進的資源調配系統帶來重大收益。

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    圖片來源:MCKINSEY & COMPANY, AUTOMATION IN LOGISTICS: BIG OPPORTUNITY, BIGGER UNCERTAINTY, APRIL 2019. BY ASHUTOSH DEKHNE, GREG HASTINGS, JOHN MURNANE, AND FLORIAN NEUHAUS

    2)物聯網傳感器,新型信息通訊技術,智能運輸系統,交通數據將構成寬廣的數據集變量,這些內容將通過機器學習技術為供應鏈改善提供價值。

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    圖片來源:KPMG, SUPPLY CHAIN BIG DATA SERIES PART 1

    3)機器學習有機會幫助物流系統節省每年600萬美金的成本,這將通過從IoT設備采集的軌跡數據中學習模型來實現

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    圖片來源:BOSTON CONSULTING GROUP, PAIRING BLOCKCHAIN WITH IOT TO CUT SUPPLY CHAIN COSTS, DECEMBER 18, 2018, BY ZIA YUSUF , AKASH BHATIA , USAMA GILL , MACIEJ KRANZ, MICHELLE FLEURY, AND ANOOP NANNRA

    4)通過機器學習減少預測錯誤

    通過機器學習技術可以減少因庫存不足造成的銷售損失,最多可以降低65%。而在庫存的準備上也有20%-50%的優化空間。

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    圖片來源:DIGITAL/MCKINSEY, SMARTENING UP WITH ARTIFICIAL INTELLIGENCE (AI) - WHAT’S IN IT FOR GERMANY AND ITS INDUSTRIAL SECTOR? (PDF, 52 PP., NO OPT-IN).

    5)DHL研究發現,機器學習技術將幫助物流和供應鏈單元優化庫存占用情況,提升用戶體驗,減少風險和開發新商業模式。

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    圖片來源:SOURCE: DHL TREND RESEARCH, LOGISTICS TREND RADAR, VERSION 2018/2019 (PDF, 55 PP., NO OPT-IN)

    6)一家區域制造商正在使用AI技術來檢測和應對不一致的供應商質量等級和交付情況

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    圖片來源:MICROSOFT, SUPPLIER QUALITY ANALYSIS SAMPLE FOR POWER BI: TAKE A TOUR, 2018

    7)減少欺詐的潛在風險,改善產品和流程質量

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    圖片來源:FORBES, HOW MACHINE LEARNING IMPROVES MANUFACTURING INSPECTIONS, PRODUCT QUALITY & SUPPLY CHAIN VISIBILITY, JANUARY 23, 2019

    8)通過增強端對端的供應鏈透明度,幫助企業更快響應

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    圖片來源:CHAINLINK RESEARCH, HOW INFOR IS HELPING TO REALIZE HUMAN POTENTIAL,

    9)減少特權規則的使用來帶的安全風險

    首席信息官們正在解決供應鏈中的特權濫用問題,如果機器學習發現活動的環境處于風險當中,將要求更強力的許可來授權活動。

    10)通過機器學習技術,結合IoT數據改善設備的維護水平,降低運營成本。

    麥肯錫公司發現,通過機器學習賦能的預測式維護技術,將幫助企業更好地避免機器停止運轉。設備的生產力將得以提升20%,而整體維護成本將減少10%。

    原文參考資料包括:

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    Boston Consulting Group, Pairing Blockchain with IoT to Cut Supply Chain Costs, December 18, 2018, by Zia Yusuf, Akash Bhatia, Usama Gill, Maciej Kranz, Michelle Fleury, and Anoop Nannra

    Capgemini, Supply Chain Management – The Quiet Revolution. April 24, 2019

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    在夫面前夫侵犯中文字幕
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