Manufacturing is undergoing digitalization as fast any other industry. In the race to drive down costs, increase efficiency, and improve productivity, the transformation of the manufacturing company is ongoing. One report predicts digitalization could increase productivity in major economies by 25 per cent by 2025. ⁶ Such confidence underpins the technological innovation happening in the sector. Below are highlighted three defining changes, as well as an additional non-technological trend that companies are increasingly considering.

Automation: Robotics

The Covid-19 pandemic accelerated a shift toward robotics that was already happening. Public health measures have required deep cleaning and social distancing, which has meant fewer bodies in a factory, either due to reduced capacity, staggered shifts, or a complete shutdown. To protect against labour disruption or shortages, robots are doing cleaning, maintenance, and routine tasks.¹

Industrial robotics was already showing big growth (see chart). The American Association for Mechanical Engineers predicts robotics to double in size by 2025. Collaborative robots, also known as “cobots”, with their ease-of-use, low-cost human augmentation, are expected to grow the most. More sophisticated robots, such as self-repairing robots and AI-enabled robots, are in development. Robotics experts in the UK built an industrial robot that uses visual recognition and machine learning to make assembly decisions, which will create big cost savings.³

Connectivity: The Industrial Internet of Things

Often associated with consumer goods, such as appliances or vehicles, the Industrial Internet of Things is the same concept but applied to industrial processes. IIoT involves extending the internet to connect it via sensors with various items, typically equipment, products, and raw materials. 31 per cent of manufacturers already incorporate IIoT into their processes, another 34 per cent plan to use it, and 34 per cent will embed IIoT tech into their products.⁴

There are two main benefits to IIoT, which come from giving companies the ability to make informed and strategic decisions based on real-time data. Firstly, it is valuable for its remote monitoring capability, which can translate into faster response times in cases of malfunction or error. Service can also be prepared prior to the technician’s arrival, because the issue is already known. Secondly, IIoT can save costly repairs with predictive maintenance. A pause or breakdown in operations can be extremely expensive, but predictive maintenance can ensure everything continues to run smoothly by spotting problems before they occur.⁴

Digitization: AI, Analytics & Big Data

All the data collected from robots and IIoT is useless if companies cannot adequately store, exchange, and analyze them. From the factory floor to the c-suite, companies are increasingly slicing and dicing data, as real-time data gets uploaded to the cloud to gain a fuller understanding of the whole business.⁴ Real digitalization and an adoption of Industry 4.0, a German concept encapsulating many of the processes outlined in this article, infuses entire companies and the way they make decisions.

Analysts from KPMG argue that, as with robotics, the pandemic has accelerated the automation process. Intelligent document processing, natural language processing, decision management systems, and other innovations are creating “intelligent” businesses. They claim, “Intelligent business process automation … has the power to increase speed, scale, quality and precision of business process execution exponentially while also complementing and augmenting human skills.”²

Digital Twins are another way global manufacturers such as Siemens are supporting flexibility and resiliency. Deloitte sees it as a major trend for 2021.⁵ Digital Twins enable a manufacturer to design, test, and create a digital copy of something before actually building it, saving costs and time-to-market for what would otherwise be a slow and expensive trial-and-error process.⁷

Reshoring: Declining Globalization

Reshoring is another change that started before the pandemic and has accelerated. Already, an estimated 749K jobs returned to the U.S. between 2010 and 2018.⁴ The reasons are numerous: Economies have strengthened in offshored countries, raising wages, but jurisdictions with cheap labour lack capacity for complex manufacturing; the cost of transportation keeps rising; and advanced software and robotics have automated many processes to longer require human intervention.

As 2020 saw severe disruption in many supply chains, especially ones that relied on China, companies looked to build resiliency into their supply chains. Near-sourcing, or local sourcing, brings a business’ operations closer to where its finished product is sold; in manufacturing, it can mean the sourcing of raw materials from domestic suppliers.⁴

SOURCES

1. “A Brighter Future? Automation Trends of 2021.” RoboticsTomorrow, 4 Jan. 2021, roboticstomorrow.com/story/2021/01/a-brighter-future-automation-trends-of-2021-/16068/.
2. “Top 10 Industrial Automation Trends in 2021.” Manufacturing AUTOMATION, 19 Feb. 2021, automationmag.com/top-10-industrial-automation-trends-in-2021/.
3. “Breakthrough’ Robot Can Make Decisions Based on What It Sees.” Drives and Controls Magazine, 21 Jan. 2021, drivesncontrols.com/news/fullstory.php/aid/6614/_91Breakthrough_92_robot_can_make_decisions_based_on_what_it_sees.html.
4. Boggess, Martin. “11 Trends That Will Dominate Manufacturing in 2021.” Hitachi Solutions, www.global.hitachi-solutions.com/blog/top-manufacturing-trends.
5. “2021 Manufacturing Industry Outlook.” Deloitte United States, 25 Feb. 2021, deloitte.com/us/en/pages/energy-and-resources/articles/manufacturing-industry-outlook.html.
6. “The Practical Impact of Digital Manufacturing.” Cambridge Industrial Innovation Policy, 25 July 2019, ciip.group.cam.ac.uk/reports-and-articles/practical-impact-digital-manufacturing/.
7. “Digitalization integrated, not just connected: Digital Twins White Paper.” Siemens. https://assets.new.siemens.com/siemens/assets/api/uuid:4a1b9cac-2a79-4292-8f64-106710be3a27/Digital-Twin-White-Paper-final-3.pdf

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