Logistics Innovation Reveals Emerging Technologies

The major component driving the advancement of the logistics industry is the digital transformation.Emerging technologies offer new solutions to tackle existing challenges such as warehouse automation,last-mile delivery,and transportation optimization.For logistic companies striving to survive in this highly competitive industry,it is vital to innovate rapidly and integrate new solutions.

推動(dòng)物流業(yè)發(fā)展的主要因素是數(shù)字化轉(zhuǎn)型。新興技術(shù)為應(yīng)對(duì)倉(cāng)庫(kù)自動(dòng)化、最后一英里交付及運(yùn)輸優(yōu)化等現(xiàn)有挑戰(zhàn)提供了新的解決方案。對(duì)于努力在這個(gè)競(jìng)爭(zhēng)激烈的行業(yè)中求生存的物流公司來(lái)說(shuō)，快速創(chuàng)新和集成新的解決方案至關(guān)重要。

Automated guided vehicles (AGVs)

自動(dòng)導(dǎo)引車(chē)

Considered the ground equivalent of drones in last-mile delivery,automated guided vehicles hold an even greater potential for disruptionin the logistics industry.Logistics companies willing to innovate in this area can draw from various use cases such as last-mile delivery,line-haul transportation,and warehousing operations.In warehousing,the main application,AGVs massively contribute to a new paradigmof material handlingby meeting full automation.In last-mile delivery,significant progress is made as well with automated guided vehicles even being ahead of drones as the regulatory system is more open towards them.

在最后一英里交付中，自動(dòng)導(dǎo)引車(chē)被視作地面上的無(wú)人機(jī)，對(duì)物流業(yè)具有更大的顛覆性。愿意在這一領(lǐng)域進(jìn)行創(chuàng)新的物流公司可以借鑒多種使用案例，如最后一英里交付、長(zhǎng)途運(yùn)輸和倉(cāng)儲(chǔ)運(yùn)營(yíng)。在倉(cāng)儲(chǔ)這一主要應(yīng)用領(lǐng)域，自動(dòng)導(dǎo)引車(chē)通過(guò)實(shí)現(xiàn)全自動(dòng)化，為物料輸送的新模式做出巨大貢獻(xiàn)。在最后一英里交付方面，自動(dòng)導(dǎo)引車(chē)也取得了重大進(jìn)展，甚至領(lǐng)先于無(wú)人機(jī)，因?yàn)楸O(jiān)管體系對(duì)它們更為開(kāi)放。

Robotics & automation

機(jī)器人技術(shù)和自動(dòng)化

In less structured environments,robots are already capable of manipulating objects,therefore,supporting zero-defects logistics processes and massively supporting performance as well as improving sensing capabilities up to a point where they nearly substitute manual handling.These robots are either 100% automated or collaborate with people (“cobot”).A few of the use cases are remarkably conceivable: fully automatic solutions unload containers or palletize which establishes new application areas such as collaborative,pick& place,and shelving robots among many others.Whereas large companies focus on integration (building hardware and combining it with vision/tactilesolutions),cutting-edge startups tend to specialize on vision and tactile solutions,one of the biggest opportunities in the robotics area as they aim to solve challenges such as speed,picking from random,part quality vision,and color contrast.

在結(jié)構(gòu)化程度較低的場(chǎng)景中，機(jī)器人已能操縱物體，從而支持零缺陷物流流程，大幅提升物流效率，感知能力也提升到幾乎與人類(lèi)比肩的程度。這些機(jī)器人要么完全自動(dòng)化，要么與人協(xié)作（即“協(xié)作機(jī)器人”）。我們很容易想象一些使用案例：利用全自動(dòng)解決方案卸載貨柜或碼垛，從而開(kāi)創(chuàng)許多新的應(yīng)用領(lǐng)域，如可以完成分揀和取放、貨架整理的協(xié)作機(jī)器人等。大公司專(zhuān)注于集成，即構(gòu)建硬件并將其與視覺(jué)/觸覺(jué)解決方案相結(jié)合，而尖端初創(chuàng)公司往往專(zhuān)攻視覺(jué)和觸覺(jué)解決方案——這是機(jī)器人技術(shù)最大的潛在市場(chǎng)之一，旨在解決速度、雜亂環(huán)境下抓取、零部件質(zhì)量視覺(jué)檢測(cè)、顏色對(duì)比等方面的挑戰(zhàn)。

Augmented reality (AR)& wearables

增強(qiáng)現(xiàn)實(shí)和可穿戴設(shè)備

Wearable technology such as smart clothing,bionicarms or smart contact lenses act as a powerful support tool for the human workforce.Adding an augmented reality system such as wearable cameras or smart-glass displays unlocks additional value for logistics companies,e.g.gamification to train & onboardnew employees or the utilization of smart glasses for picking,positioning and scanning to empower employees to work hands-free.

智能服裝、仿生手臂、智能隱形眼鏡等可穿戴技術(shù)是人力的強(qiáng)大支持工具。添置一個(gè)增強(qiáng)現(xiàn)實(shí)系統(tǒng)，如可穿戴攝像頭或智能玻璃顯示器，能為物流公司帶來(lái)額外價(jià)值，例如通過(guò)游戲化形式來(lái)培訓(xùn)和錄用新員工，或利用智能眼鏡進(jìn)行挑選、定位和掃描，使員工不用動(dòng)手也能工作。

Drones

無(wú)人機(jī)

Drones (akaunmanned aerial vehicles)begin to disrupt the industry by offering in- and outdoor use cases such as last-mile delivery,inventory management,security,inspection scanning,serving as collaborative tools for delivering items between employees inside the warehouse as well as certain material handling scenarios.Though drones are not expected to replace ground delivery entirely (see AGVs for reference),this technology has a significant impact on logistics processes.

無(wú)人機(jī)（又稱(chēng)無(wú)人駕駛飛行器）開(kāi)始顛覆這個(gè)行業(yè)，它提供了室內(nèi)和室外的使用案例，如最后一英里交付、庫(kù)存管理、安防及掃描檢查。作為協(xié)作工具，無(wú)人機(jī)可在倉(cāng)庫(kù)內(nèi)于員工之間傳送物品，并在某些場(chǎng)景下搬運(yùn)貨物。雖然預(yù)計(jì)無(wú)人機(jī)不會(huì)完全取代地面交付工具（如自動(dòng)導(dǎo)引車(chē)），但這項(xiàng)技術(shù)對(duì)物流流程有重大影響。

Last-mile delivery

最后一英里交付

As the rise of ecommerce has reinforced the importance of customer preferences and demands,last-mile delivery has become a vital aspect for logistics companies.Through making use of smart lockers,a flexible courier workforce along with the power of the crowd,last-mile delivery acts as a key differentiator in terms of customer satisfaction.

電子商務(wù)的興起強(qiáng)化了客戶偏好和需求的重要性，最后一英里交付因而成為物流公司的一項(xiàng)重要業(yè)務(wù)。通過(guò)使用智能儲(chǔ)物柜、靈活的快遞員隊(duì)伍以及群體的力量，最后一英里交付成為客戶滿意度方面的關(guān)鍵分水嶺。

Anticipatory logistics

物流預(yù)測(cè)

Though anticipatory logistics is not yet very common in the industry,it is without a doubt that it will become a powerful asset.Implemented through software solutions,anticipatory logistics predict demand before it occurs.This enables logistics companies to substantially improve efficiency through reduced delivery time and better utilization of their transport capacity and network through predictive algorithms derived from big data.

雖然物流預(yù)測(cè)在業(yè)內(nèi)還不是很普遍，但毫無(wú)疑問(wèn)，它將具有強(qiáng)大價(jià)值。通過(guò)軟件對(duì)物流進(jìn)行預(yù)測(cè)，從而預(yù)知物流需求。物流公司從大數(shù)據(jù)得出預(yù)測(cè)算法，能夠縮短交付時(shí)間，更好地利用其運(yùn)輸能力和運(yùn)輸網(wǎng)絡(luò)，從而大幅提高效率。

Machine learning

機(jī)器學(xué)習(xí)

Machine learning or,as it is sometimes called self-learning,is one technology bound to transform the logistics industry as we know it today.Because this form of Artificial Intelligence (AI)requires very little human intervention and adapts algorithms according to the data received,it becomes more efficient automatically.Some application areas for machine learning in the logistics industry include the optimization of algorithms for shippers to select carriers,route and do quality control,the use of natural language processing (NLP)to speed up data entries,as well as the optimization of storage,order picking,order validation and waste reduction in the warehouse.Ultimately,this results in process optimization and the automation of decision making in logistics.

機(jī)器學(xué)習(xí)，有時(shí)也稱(chēng)為自學(xué)習(xí)，這項(xiàng)技術(shù)必將改變我們今天所知的物流業(yè)。作為一種人工智能，機(jī)器學(xué)習(xí)幾乎無(wú)須人工干預(yù)，它根據(jù)接收到的數(shù)據(jù)調(diào)整算法，因此會(huì)自動(dòng)變得更加高效。機(jī)器學(xué)習(xí)在物流業(yè)的一些應(yīng)用包括：優(yōu)化托運(yùn)人選擇承運(yùn)人、路線和進(jìn)行質(zhì)量控制的算法；使用自然語(yǔ)言處理加速數(shù)據(jù)輸入；優(yōu)化倉(cāng)庫(kù)中的存儲(chǔ)、訂單分揀、訂單驗(yàn)證及減少浪費(fèi)。最終，機(jī)器學(xué)習(xí)將實(shí)現(xiàn)最優(yōu)化的物流流程和自動(dòng)化的物流決策。

Internet of Things (IoT)

物聯(lián)網(wǎng)

Logistics companies are widely expected to take full advantage of the Internet of Things as it holds many promises.Some of the many application areas include smart objects taking part in event-drivenprocesses,asset tracking within the warehouse and in the delivery status,environment sensing (e.g.freshness monitoring),and fleet management.Overall,the IoT adds massive value across the entire supply chain including warehousing,last-mile delivery,and freight transportation.■

人們普遍認(rèn)為物流公司會(huì)充分利用物聯(lián)網(wǎng)，因?yàn)槲锫?lián)網(wǎng)潛力多多。物聯(lián)網(wǎng)應(yīng)用領(lǐng)域廣泛，其中包括：參與事件驅(qū)動(dòng)流程的智能物體、儲(chǔ)存和交付狀態(tài)下的資產(chǎn)跟蹤、環(huán)境感知（如新鮮度監(jiān)測(cè)）以及車(chē)隊(duì)管理?？傊?，物聯(lián)網(wǎng)為整個(gè)供應(yīng)鏈帶來(lái)巨大價(jià)值，惠及倉(cāng)儲(chǔ)、最后一英里交付及貨物運(yùn)輸。 □