AI+物流的应用与发展,在物流行业起到什么作用

DHL近日与IBM发布了一份联合报告,对人工智能(AI)在物流行业的发展潜力进行了评估,并揭示了如何更好地应用人工智能实行物流行业变革,增加新智能物流资产,创造运营典范。
In a joint report, DHL and IBM have evaluated the potential of Artificial Intelligence (AI) in logistics and exposed how it can be best applied to transform the industry, giving rise to a new class of intelligent logistics assets and operational paradigms.
DHL和IBM阐述了在人工智能的性能、可达成性和成本等方面均达成突破的状况下,物流行业的领导者该如何利用人工智能的核心优势和机遇。
DHL and IBM outline how supply chain leaders can take advantage of AIs key benefits and opportunities now that performance, accessibility as well as costs are more favourable than ever before.
该合作报告指明了人工智能对物流行业的影响以及相关应用,认为人工智能有望显著增强人类的能力。
The collaborative report identifies implications and use cases of AI for the logistics industry, finding that AI has the potential to significantly augment human capabilities.
人工智能在消费领域已无处不在,语音助手应用的快速增长就是有力的证明。
While AI is already ubiquitous in the consumer realm, as demonstrated by the rapid growth of voice assistant applications.
与此同时,DHL和IBM发现人工智能技术正在快速成熟,可以为物流行业带来新的应用。
DHL and IBM find that AI technologies are maturing at great pace, allowing for additional applications for the logistics industry.
比如帮助物流供应商通过会话式互动来丰富客户体验,甚至能在客户下指令前就开始递送产品。
These can, for instance, help logistics providers enrich customer experiences through conversational engagement and even deliver articles before the customer has even ordered them.
DHL高级副总裁兼全球创新主管Matthias Heutger表示:“目前的技术、商业和社会状况比以往更适合对物流运作模式转变进行展望和预测。
“Today’s current technology, business, and societal conditions favour a paradigm shift to proactive and predictive logistics operations more than any previous time in history” explains Matthias Heutger, Senior Vice President and Global Head of Innovation DHL.
随着人工智能领域技术的飞速发展,我们有责任协同我们的客户和员工,共同探讨人工智能如何塑造物流行业的未来。”
As the technological progress in the field of AI is proceeding at great pace, we see it as our duty to explore, together with our customers and employees, how AI will shape the logistics industry’s future.”
许多行业已成功将人工智能应用于日常业务。比如,在工程和制造行业,人工智能正在生产线中发挥作用,通过图像识别和会话界面来简化生产和维护。
Many industries have already successfully adopted AI into their everyday business, such as the engineering and manufacturing industry: AI is being used in production lines to help streamline production and maintenance through image recognition and conversational interfaces.
在汽车业,通过人工智能来提升自动驾驶汽车自学能力的呼声很高。
In the automotive industry, AI is being extensively called upon to enhance the self-learning capabilities of autonomous vehicles.
越来越多的例子证明了人工智能有诸多优势,有能力在改变消费者世界后再改变工业世界。
Many more examples evidence AI’s benefits with the ability to transform the world of industry after its transformational impact on the consumer world.
有了人工智能的帮助,物流行业将把其运营模式从被动行为转变为积极主动的预测模式,花费较少的成本在后台系统、运营和面向客户的活动中产生更好的洞察。
With the help of AI, the logistics industry will shift its operating model from reactive actions to a proactive and predictive paradigm, which will generate better insights at favourable costs in back office, operational and customer-facing activities.
例如,DHL开发了一种基于机器学习的工具来预测空运延误状况,以预先采取缓解措施。
For example, DHL has developed a machine learning-based tool to predict air freight transit time delays in order to enable proactive mitigation.
通过对其内部数据的58个不同参数进行分析,这一机器学习模型能够提前一周对特定航线的日平均通行时间进行预测。
By analyzing 58 different parameters of internal data, the machine learning model is able to predict if the average daily transit time for a given lane is expected to rise or fall up to a week in advance.
此外,它还能确定导致运输延误的主要因素,比如是出发日之类的时间因素,或是航空公司准时率等方面的运营因素,
Furthermore, this solution is able to identify the top factors influencing shipment delays, including temporal factors like departure day or operational factors such as airline on-time performance.
有助于空运代理商提前进行科学计划,而不是只能靠主观猜测。
This can help air freight forwarders plan ahead by removing subjective guesswork around when or with which airline their shipments should fly.
人工智能技术可以使用先进的图像识别来跟踪货运和资产状况,为运输带来端到端的自主性,或提前预测全球出货量波动。
AI technologies can use advanced image recognition to track condition of shipments and assets, bring end-to-end autonomy to transportation, or predict fluctuations in global shipment volumes before they occur.
近期中外运-敦豪国际航空快件有限公司获得专利的“小型高效自动分拣装置”就利用了图像识别技术,在进行快件分拣的同时,自动获取数据,并对接DHL的相应系统进行数据上传。
Recently, DHL-Sinotrans has obtained a patent for its auto sorting. Leveraging image recognition technology, the device can acquire data automatically and upload the collected data to relevant DHL systems while sorting shipments.
显然,人工智能增强了人的能力,也让物流人员从日常工作中解放出来,将工作重点转向更有意义和价值的方向。
Clearly, AI augments human capabilities but also eliminates routine work, which will shift the focus of logistics workforces to more meaningful and value-added work.
就像人工智能目前在消费领域无处不在一样,未来的人工智能将在工业领域得到广泛应用。
AI will develop to become as omnipresent in the industrial sector as it currently is in the consumer world.
人工智能致力于将物流行业转变为积极主动、具有预测性、自动化和个性化的行业。
AI stands to transform the logistics industry into a proactive, predictive, automated and personalized branch.
有鉴于此,该报告阐述了物流公司如何抓住先机,将人工智能技术应用到全球供应链中的最佳实践与方法。
Considering this, the report provides perspectives and best practices on how logistics players can seize and adopt AI in their global supply chains.