The Gemini makers

Millions of things will soon have digital twins

The Economist(July 13th. 2017)-Print Edition-Business

未來(lái)的工廠會(huì)滿是機(jī)器人生產(chǎn)機(jī)器人的景象芥挣。Amberg，巴伐利亞的一個(gè)小鎮(zhèn)里耻台，一座工廠雖然還沒(méi)有達(dá)到這樣的程度空免，但是已經(jīng)很接近了。德國(guó)的工程巨擘西門(mén)子運(yùn)行的這座工廠生產(chǎn)工業(yè)數(shù)控系統(tǒng)盆耽，用于一系列自動(dòng)化系統(tǒng)中關(guān)鍵配件的生產(chǎn)蹋砚，包括工廠自己的生產(chǎn)線。

Amberg里的這座工廠寬敞摄杂、明亮坝咐，而且極度潔凈。目前析恢，這個(gè)工廠里每年生產(chǎn)1500萬(wàn)個(gè)配件單元墨坚，從1989年成立以來(lái)，在沒(méi)有擴(kuò)大廠房并且維持1200個(gè)員工（實(shí)行三班倒班制度）的情況下映挂，產(chǎn)量已經(jīng)是最初的10倍泽篮。生產(chǎn)過(guò)程的75%實(shí)現(xiàn)自動(dòng)化，因?yàn)槲鏖T(mén)子認(rèn)為柑船，有些工作由人來(lái)完成是最好的帽撑。目前生產(chǎn)的配件的次品率接近于0，其中99.9988%都不需要進(jìn)行調(diào)整椎组；考慮到它們生產(chǎn)1000種以上不同的配件，這真的是一個(gè)令人吃驚的成就了历恐。

這樣的成就很大程度上歸功于“數(shù)字鏡像”寸癌，就是計(jì)算機(jī)系統(tǒng)中對(duì)實(shí)體設(shè)備建立了一個(gè)虛擬版本，像一個(gè)孿生工廠一樣弱贼≌粑“數(shù)字鏡像”中，實(shí)體工廠的每個(gè)細(xì)節(jié)都被模擬吮旅，用以設(shè)計(jì)控制單元并進(jìn)行測(cè)試溪烤，模擬如何生產(chǎn)以及操控設(shè)備。所有設(shè)備都運(yùn)轉(zhuǎn)完善后庇勃，數(shù)字模型就會(huì)交付給實(shí)體工廠用來(lái)進(jìn)行實(shí)際生產(chǎn)檬嘀。

數(shù)字模型并非新近發(fā)明。配對(duì)的概念追根溯源的話要追溯到太空旅行的早期责嚷，NASA為了能在飛行器發(fā)射后仍然能夠監(jiān)控和控制太空飛行器而建立了模擬模型鸳兽。在計(jì)算機(jī)計(jì)算能力提高后，模擬模型轉(zhuǎn)向了數(shù)字化罕拂。

這種強(qiáng)大的系統(tǒng)的出現(xiàn)整合了計(jì)算機(jī)輔助設(shè)計(jì)和建造揍异，模擬全陨，過(guò)程控制，產(chǎn)品周期管理等多種元素衷掷。有些數(shù)字模型還增加了人工智能和虛擬現(xiàn)實(shí)能力辱姨。這些數(shù)字模型可以對(duì)已經(jīng)賣出的產(chǎn)品幫助實(shí)現(xiàn)遠(yuǎn)程監(jiān)控和提供售后服務(wù)，西門(mén)子數(shù)字化工廠部的負(fù)責(zé)人Jan Mrosik說(shuō)“這是整個(gè)價(jià)值鏈的數(shù)字模型戚嗅∮晏危”

西門(mén)子不是唯一的使用數(shù)字鏡像的公司，GE也在使用渡处。這兩家公司镜悉，連同這個(gè)領(lǐng)域里的一家法國(guó)公司，Dassault Systèmes医瘫，都在出售各自的數(shù)字鏡像軟件侣肄。客戶來(lái)自航空醇份，國(guó)防稼锅，自動(dòng)化，消費(fèi)品僚纷，能源矩距，重工業(yè)，醫(yī)藥等多個(gè)領(lǐng)域怖竭。

使用鏡像的動(dòng)機(jī)之一是讓產(chǎn)品以較低的成本快速投向市場(chǎng)锥债。數(shù)字鏡像可以在虛擬環(huán)境無(wú)限重復(fù)設(shè)計(jì)過(guò)程，不需要停掉生產(chǎn)線去看生產(chǎn)出的產(chǎn)品是什么樣的痊臭。數(shù)字鏡像統(tǒng)一可以建立工人的工作模型哮肚，以提高功效。菲亞特克萊斯勒汽車品牌之一的瑪莎拉蒂广匙，使用數(shù)字鏡像允趟，讓Ghibli跑車僅用16個(gè)月即可在意大利Grugliasco投產(chǎn)，而正常周期則需要30個(gè)月鸦致。

數(shù)字鏡像的廣泛使用會(huì)沖擊供應(yīng)鏈潮剪。比如，買方可能要求賣方提供所售產(chǎn)品的數(shù)字鏡像分唾，用于在正式投產(chǎn)之前在虛擬條件下的生產(chǎn)模擬抗碰。這一點(diǎn)已經(jīng)成為Amberg工廠的要求，他們需要上游供應(yīng)商將數(shù)字鏡像連同正式產(chǎn)品一同提供以輔助安裝绽乔。

當(dāng)產(chǎn)品配備了連接互聯(lián)網(wǎng)數(shù)據(jù)的傳感器改含，數(shù)字鏡像就變得更加靈敏。F1賽車裝備了大量這樣的傳感器，參賽車隊(duì)使用傳感器的數(shù)據(jù)給自己的車創(chuàng)造鏡像捍壤，以便在大賽中間的一兩個(gè)星期里更快的設(shè)計(jì)骤视、測(cè)試和生產(chǎn)上百個(gè)所需要的更換配件。GE構(gòu)建風(fēng)力渦輪與噴氣發(fā)動(dòng)機(jī)的數(shù)字鏡像鹃觉，以便監(jiān)測(cè)工作狀態(tài)和定期維修专酗。

甚至復(fù)雜度甚低的量產(chǎn)產(chǎn)品最終也可能需要數(shù)字鏡像。數(shù)字鏡像的建立有助于追蹤和驗(yàn)證產(chǎn)品盗扇，這樣的用途對(duì)于食品工業(yè)以及制藥業(yè)愈加重要祷肯。挪威的一家利用算法生成產(chǎn)品安全碼的公司首席執(zhí)行官Thomas K?rmendi認(rèn)為，即使沒(méi)有完全普及數(shù)字鏡像疗隶，幾乎任何產(chǎn)品也都要有與生存日期相關(guān)的唯一識(shí)別標(biāo)識(shí)佑笋。這家公司的安全碼可以用手機(jī)去掃描，通過(guò)聯(lián)網(wǎng)斑鼻，進(jìn)而像產(chǎn)品位置和使用情況這樣的信息就會(huì)交換給數(shù)字鏡像蒋纬。比如說(shuō)，在倫敦的一位顧客要查驗(yàn)一瓶好酒坚弱，通過(guò)數(shù)字鏡像他可以知道的葡萄的原產(chǎn)地蜀备，如果酒瓶是掉過(guò)包的，則會(huì)有警示信息荒叶。這樣的用途則是同每個(gè)人息息相關(guān)的碾阁。

This article appeared in theBusinesssection of the print edition under the headline"The Gemini makers"

THE factory of the future will be a building stuffed full of robots making robots. A factory in Amberg, a small town in Bavaria, is not quite that, but it gets close. The plant is run by Siemens, a German engineering giant, and it makes industrial computer-control systems, which are essential bits of kit used in a variety of automated systems, including the factory’s own production lines.

The Amberg plant is bright, airy and squeaky clean. It produces 15m units a year—a tenfold increase since opening in 1989, and without the building being expanded or any great increase in the 1,200 workers employed in three shifts. (Production is about 75% automated, as Siemens reckons some tasks are still best done by humans.)The defect rate is close to zero, as 99.9988% of units require no adjustment, a remarkable feat considering they come in more than 1,000 different varieties.

Such achievements are largely down to the factory’s “digital twin”. For there is another factory, a virtual version of the physical facility that resides within a computer system. This digital twin is identical in every respect and is used to design the control units, test them, simulate how to make them and program production machines. Once everything is humming along nicely, the digital twin hands over to the physical factory to begin making things for real.

The digital twin is not a new invention. The concept of pairing traces its roots to the early days of space travel, when NASA built models to help monitor and modify spacecraft that, once launched, were beyond their physical reach. As computer power increased, these analogue models turned into digital ones.

The powerful systems that have since emerged bring together several elements—software services in computer-aided design and engineering; simulation; process control; and product life cycle management. Some digital twins are gaining artificial intelligence and virtual-reality capabilities, too. They can also help to monitor remotely and provide after-service for products that have been sold. “It is a digital twin of the entire value chain,” says Jan Mrosik, the chief executive of Siemens’s Digital Factory Division.

Siemens is not alone in equipping its factories with digital twins. Its American rival, GE, is doing the same. Both companies also sell their digital-twin software, along with firms such as Dassault Systèmes, a French specialist in the area. Customers come from industries ranging from aerospace and defence to automotive, consumer products, energy, heavy machinery and pharmaceuticals.

One motivation for twinning is to bring products to market faster and at a lower cost. The digital twin allows endless design iterations to be tried in the virtual world without having to stop the production line to see how they can be made, says Mr Mrosik. The twin can also model people working in a factory to improve their ergonomics. In one example, Maserati, which is part of Fiat Chrysler Automobiles (whose chairman is a director ofThe Economist’s parent company), used a digital twin to put its Ghibli sports saloon into production in Grugliasco, Italy, in just 16 months instead of the typical 30 months.

The spread of digital twins could shake up supply chains. For example, suppliers could be asked to submit a digital twin of their product so that it can be tested in a manufacturer’s virtual factory before an order is placed. It is already a requirement at the Amberg plant for suppliers to deliver a digital twin along with their product to help installation.

Twins will become more responsive still as products are increasingly fitted with sensors that relay data to the internet. Formula 1 cars are full of such sensors; racing teams use these data to create digital twins of their cars so that they can rapidly design, test and manufacture parts needed to make hundreds of changes in the week or two between races. GE creates digital twins of its wind turbines and jet engines to monitor their performance and carry out preventive maintenance. Data transmitted from a jet engine while planes are in the air can provide 15-30 days’ advance notice of potential failures.

Even mass-produced goods that are far less complex are likely to end up having digital siblings. This would help with product tracking and verification, which is increasingly important in food manufacturing and pharmaceutical production. Just about any product could have a unique identifier that links to production data, if not a full digital twin, reckons Thomas K?rmendi, the chief executive of Kezzler, a Norwegian company that produces secure product codes using an algorithm.

The firm’s codes can be scanned with a smartphone, which then connects over the internet so that information can be exchanged with a digital twin on things like a product’s location and use. A consumer in London checking the provenance of a bottle of fine wine, for example, could confirm the vintage, or be alerted to the possibility of counterfeiting if the bottle had actually been dispatched to a different country. That’s something everyone can raise a glass to.