第四次工业革命（通常称为工业4.0）具有巨大的潜力，可以在众多行业中制造公司来实现产品定制，提供灵活性，以实时满足新需求，并产生更有效的运营。
当工厂为2020年及以后做准备时，我与行业经理Philipp Wallner进行了交谈数学工作，关于2020年推动行业4.0机会的原因，包括拥有足够的高质量数据，对关键的低层沟通，运营优化和性能管理技术的需求。以下概述了我们关于2020年及以后未来工厂趋势的对话。
AI多年来一直是流行语。新兴技术将如何影响明年的行业4.0应用程序？
在2020年，AI将成为灵活生产的推动者。在过去的几年中，自动化行业一直集中在生产线上生产一种独一无二的商品，而没有遇到扩展的转换时间。使用行业4.0，必须完成生产的全部个性化。这意味着无法对机器进行委托，参数化和调整，以重复生产的一种数月甚至数年的特定产品。生产线必须是灵活的。还必须有一个AI，可以根据下一个在生产线上制造的个性化良好来对机进行参数化和调音。
Simulation has played a large role in manufacturing. Are there any evolutions in the technology we can expect as the industry transitions to Industry 4.0?
由于软件的复杂性以及模块化软件组件的可能组合数量越来越多，设计和测试物理机变得更加困难，即使不是不可能。为了反对，公司将对软件进行虚拟调试，以验证没有错误的情况，并根据模拟模型在实体生产线上验证是否达到要求。高精度齿轮研磨机的生产商Reishauer AG等公司已经在使用多域模拟模型来进行虚拟调试。
What advances in network communications will take place with the growth of connected machines?
随着行业向工业4.0和IoT的过渡，将更加重视制定诸如OPC UA TSN之类的统一标准，这将有助于确保机器和工厂模块之间的互连性。为了符合这些标准，几种技术的结合可以使数据能够符合行业范围的标准在制造商之间实时传输，这将确保来自不同供应商的设备无缝地互动。
The emergence of 5G and advanced Wi-Fi will replace inflexible cables— enabling a more flexible factory floor. Machines will not only connect with each other but also to cloud systems where advanced calculation power is running powerful algorithms on business and engineering data.
随着数据和机器连接到云的增加，公司将如何确保正确的数据在正确的时间捕获关键操作状态更新？
Increased calculation power realized by industrial controllers and edge-computing devices, as well as the use of cloud systems, will help achieve a new dimension of software functionality on production systems. Edge computing will enable AI-based algorithms to be better optimized throughout the production line—ensuring notification of faulty operations in time to avoid serious problems while minimizing the consumption of energy. Predictive maintenance will evolve and be able to consider data from multiple factories and equipment from different equipment vendors.
With Industry 4.0, the focus is often on automation and algorithms. But what impact will the industry have on people working in factories in 2020?
智能工程师将有更多机会。MATLAB等更多的技术和工具将使工程师和科学家（不仅仅是数据科学家）能够使用使工业4.0（例如AI）的技术合作。将要求工程师构建模型，处理大型数据集并处理各自的开发工具，以最好地解决上面概述的趋势。公司将寻找熟练的工程师为工业4.0仅反映工厂发展的开始的未来做准备。
As industry manager for the industrial automation and machinery field at MathWorks, Philipp Wallner is responsible for driving the business development of this industry segment that comprises energy production, automation components, and production machines. Prior to joining MathWorks, Philipp worked in the machine builder industry, where he held different engineering and management positions. He has a M.S. in electrical engineering from Graz University of Technology and an executive MBA in project and process management from Salzburg Management and Business School.
