ABB首席執行官建言人工智慧時代中國製造業升級

ABB集團首席執行官史畢福昨天出席在北京舉行的「中國發展高層論壇」2018年會，並在題為《人工智慧時代的製造業轉型升級》的白皮書中，建議中國利用先進自動化和人工智慧技術加速製造業升級。

Ulrich Spiesshofer, CEO of ABB, attended the China Development Forum 2018 in Beijing, and shared his insights on how to accelerate the upgrading of China』s manufacturing industry through the deployment of advanced automation and artificial intelligence technologies in the White Paper titled Manufacturing in the Age of Artificial Intelligence.

這是史畢福博士連續第5年參加該年度盛會，以全球視角結合ABB的專業知識和成功案例，為中國的可持續發展建言獻策。

ABB集團總裁兼首席執行官史畢福

史畢福指出，自20世紀70年代開始，計算機控制系統的應用推動生產過程自動化水平的不斷提升。近年來，隨著數字技術範疇的迅速擴大，軟體與雲計算、大數據分析以及機器學習等一起，成為了數字技術的重要組成部分。

Spiesshofer pointed out that since the 1970s, production processes have become increasingly automated by computerized control systems. In recent years, software has become a subset of a rapidly expanding range of digital technologies, including cloud computing, big data analytics and machine learning, which refers to the capacity of AI to rewrite its own software in response to new data.

當前，在全球範圍內，大量資本正湧入人工智慧，特別是機器學習領域。漸趨複雜的演算法、日益強大的計算機、激增的數據以及提升的數據存儲性能，為該領域在不久的將來實現質的飛越奠定了基礎。

Today, investment in artificial intelligence, especially in machine learning, is expanding rapidly worldwide. Progressively sophisticated algorithms and more powerful computers, together with the proliferation of data and the affordability of data storage, have increased the possibilities that we will witness a step change in the capacity of AI systems in the near future.

「儘管如此，人工智慧以及其他顛覆性技術主要還是集中於消費領域，要真正實現以科技創新重塑中國經濟，這些前沿技術在工業領域及企業間的大規模應用則更為關鍵。」史畢福表示，「相比消費者相關的數據，機器生成的數據通常更為複雜，多達40%的數據甚至沒有相關性。而企業必須擁有大量的高質量、結構化數據，通過演算法進行處理，除此之外沒有捷徑可循。」

「Machine learning and other disruptive technologies have, to date, primarily been deployed by the consumer goods sector. The widespread application to the industrial and B2B sectors, however, will be a more critical test of the technology』s potential to reshape the economy,」 said Spiesshofer. 「Comparing with consumer-generated data, those generated by machines is often more complicated, and as much as 40 percent of it may prove to be irrelevant. There are no shortcuts available to companies that do not have large amounts of high-quality, structured data that can be processed by an algorithm.」

全球首款真正實現人機協作的雙臂機器人YuMi

革命性的技術創新與製造業的融合充滿挑戰，但潛在的收益無比巨大，能夠幫助企業尋求最優的解決方案，應對積弊，創造價值，比如優化任務流程，實現生產線自動化，減少誤差與浪費，提高生產效率，縮短交付時間以及提升客戶體驗。

While many challenges remain, the potential benefits of this revolutionary innovation for manufacturing are enormous, such as optimizing processes, automating assembly lines, minimizing waste, speeding up delivery time and enhancing customer experience.

史畢福補充表示：「要充分釋放新技術的潛力，企業必須首先實現運營的全面數字化，打造智能工廠，在價值鏈的各個環節生成和傳輸結構化數據。

「To release the full potential, there must be a concerted effort first of all to fully digitize every aspect of a company』s operations, networking them together to create a 『smart factory』 that generates and transmits high-quality structured data about the whole value chain,」 Spiesshofer added.

以工業機器人為例，其在未來製造業中的應用擁有巨大的發展空間。ABB已在機器人領域深耕40餘年，隨著智能組件和感測器技術的進步，我們可以藉助機器學習開發機器人編程的新方式，通過賦予機器人一定的思考和自我學習能力，使其能夠更加靈活地滿足大規模訂製化生產的需求。

Industrial robotics is likely to impact the future manufacturing and it is still a hugely untapped market. ABB has been in the robotics industry for more than 40 years. The development in smart components and sensors makes it possible to use machine learning to develop new ways of programming robots. This is exactly where value can be added. For example, instead of programming, ABB is moving towards teaching robots. The robot will be able to figure out and learn by itself, which will make it more flexible to meet the needs of mass customization.

全球首款真正實現人機協作的雙臂機器人YuMi

ABB還從去年開始攜手IBM，共同開發ABB AbilityTM的機器學習能力。作為ABB面向電力、工業、交通和基礎設施領域的數字化解決方案與平台，ABB AbilityTM聯合IBM Watson計算系統，進一步開發具有機器學習功能的人工智慧解決方案，超越當前單一數據收集功能的互聯繫統，推動工業設備邁入自主認知的新時代。

Last year, ABB joined forces with IBM to develop the machine learning capabilities of its AbilityTM, which comprises ABB』s extensive portfolio of digital solutions for utilities, industry and transport & infrastructure customers. By pairing ABB AbilityTM with IBM』s Watson computing system, ABB is seeking to move beyond current connected systems that simply gather data into a new era of cognitive industrial operations.

中國是當今全球人工智慧開發領域的領跑者之一。在過去數年中，中國政府出台了包括《中國製造2025》、《新一代人工智慧發展規劃》等在內的一系列前瞻性政策規劃，通過部署先進自動化和人工智慧技術促進產業升級轉型，加快建設製造強國。

China is one of the countries that are taking the lead in terms of AI development. Over the past few years, the Chinese government has rolled out a series of forward-looking policies, demonstrating its commitment to comprehensively upgrading its industrial base through the deployment of advanced automation and intelligent technologies.

緊隨中國發展的腳步，ABB推出了ABB AbilityTM數字化解決方案，積極致力於幫助中國客戶實現智能化轉型升級，提升運行時間、提高速度和產量，構建智能工廠，擁抱第四次工業革命浪潮下的前沿技術。

Following this trend, ABB has been committed to helping Chinese customers lay the foundations for smart factories with ABB AbilityTM to boost uptime, speed and yield, and preparing their shop floors to embrace the breakthroughs of the fourth industrial revolution.

人工智慧技術與物理世界日益緊密的聯繫，也會帶來數據安全及倫理道德方面的挑戰。在這個數據賦能的新時代，我們必須充分關注數據共享在創造便利和優勢的同時所面臨的潛在安全風險。建立健全網路安全相關的法律法規以及道德行為準則，將成為人工智慧兼顧發展和風險控制的重要保障。

The closer connection between AI and the physical world also leads to increased exposure of security vulnerabilities and ethical concerns. In the data-enabled era, it is the right time for us to think about the conflict between the advantages of sharing data and the risks of being exposed to from sharing that data. Cyber security regulations and ethical guidance will be a necessary part of the solution to boost its growth while managing its risks.

2018世界經濟論壇年會期間，達沃斯與ABB建立長期合作，為當地公共及私人交通提供充電基礎設施

未來，人工智慧將在重塑中國製造業的征程中發揮重要作用，但真正實現轉型還需要創造積極的發展環境，比如進一步強化《中國製造2025》中「智能製造」的相關內容，制定有效的跨行業標準確保所有數據可被機器讀取和解釋。自動化和機器學習的普及將衍生出大量新的職業種類，教育體系也需要進行改革，加強對高科技創新人才的培養，鼓勵終身學習，以適應新時代的要求，譜寫人工智慧與製造業融合發展的廣闊未來。

Looking forward, AI has the potential to reshape manufacturing in the years to come, yet the right conditions must be created for this transformation, such as accelerating the development of smart manufacturing, establishing rules and standards to ensure all the data generated are machine-readable and building a more sophisticated data ecosystem through cross-boundary collaboration. While the mass deployment of automation and machine learning will create vast new fields of employment, strong measures of recalibrating the educational system should be taken to secure a promising future for AI and manufacturing.

作為國際汽車聯盟電動方程式錦標賽的冠名合作夥伴，ABB積極投身未來可持續發展

ABB（ABBN: SIX Swiss Ex）是全球電氣產品、機器人及運動控制、工業自動化和電網領域的技術領導企業，致力於幫助電力、工業、交通和基礎設施等行業客戶提高業績。基於超過130年的創新歷史，ABB技術全面覆蓋電力和工業自動化價值鏈，應用於從發電端到用電端、從自然資源開採到產成品完工的各種場景，譜寫行業數字化的未來。

ABB (ABBN: SIX Swiss Ex) is a pioneering technology leader in electrification products, robotics and motion, industrial automation and power grids, serving customers in utilities, industry and transport & infrastructure globally. Continuing a history of innovation spanning more than 130 years, ABB today is writing the future of industrial digitalization with two clear value propositions: bringing electricity from any power plant to any plug and automating industries from natural resources to finished products.

作為國際汽車聯盟電動方程式錦標賽的冠名合作夥伴，ABB也積極投身未來可持續發展，拓展電動交通技術疆界。ABB集團業務遍布全球100多個國家和地區，僱員達13.5萬。ABB在中國擁有研發、製造、銷售和工程服務等全方位的業務活動，40家本地企業，1.7萬名員工遍佈於139個城市，線上和線下渠道覆蓋全國300多個城市。

As the title partner of Formula E, the fully-electric international FIA motorsport class, ABB is pushing the boundaries of e-mobility to contribute to a sustainable future. ABB operates in more than 100 countries and has about 135,000 employees. ABB has a full range of business activities in China, including R&D, manufacturing, sales and services, with 17,000 employees located in 139 cities, 40 local companies, and online and offline channels in over 300 cities.

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