By Rick Schreiber
Industrial robots are getting smarter, faster, cheaper—and, as a result, more ubiquitous in manufacturing. In what many are hailing as Industry 4.0, or the fourth industrial revolution, manufacturers of all stripes are facing both new opportunities and new challenges thanks to advances in automation, digitization, augmented reality systems and artificial intelligence.
According to data from the International Federation of Robots (IFR), in 2015, global sales of industrial robots hit a record high of some 248,000 units—a jump of 12 percent over 2014. The IFR estimates that by 2018, there will be approximately 2.3 million such machines deployed in factories around the world. Bank of America/Merrill Lynch estimates that by 2020, the market for industrial robots and artificial intelligence-based systems will be a combined $153 billion.
While the automotive industry still remains the single largest user worldwide, healthcare, food and electronics manufacturers are increasingly relying on robots and automation. Their roles are changing, too. Once relied on almost exclusively for repetitive and potentially dangerous functions like welding and materials handling, “smart machines” and robots are now being used for more sophisticated jobs that require a higher degree of human-like “intelligence,” such as selecting, packaging, inspecting and testing products and assembling extremely small components.
How industrial robots have influenced both productivity and employment worldwide and whether jobs are at risk to the “robot revolution” has long been a subject of debate. A recently published paper from London’s Center for Economic Research, written by George Graetz of Uppsala University and Guy Michaels of the London School of Economics, says that industrial robots have proven to be a “substantial driver” of both economic growth and labor productivity. While the findings are somewhat less conclusive about employment, they seem to indicate that robots increase the need for skilled, more highly paid workers while displacing low- and mid-skilled workers. Certainly, manufacturers will need to hire digital talent to support these emerging technologies and prepare for digital transformation.
Indeed, humans and robots are working together in a more seamless way. Lighter, smaller, more dexterous and sensitive machines can be used more safely with humans while also allowing for greater mobility and flexibility in manufacturing environments. Unlike their stationary ancestors, these newer robots can be moved as needed. True, such “cobots” account for only a small percentage of worldwide sales; not even 5 percent in 2015, according to the Financial Times. These machines, with their relatively small price tags of around $24,000 (compared to multiples of that for larger machines), could be a great boon to smaller manufacturers. Thanks to advances in augmented and virtual reality, machines can also be controlled, monitored and even repaired remotely.
The increased use of automation and robots—along with artificial intelligence, including machine learning—in manufacturing means having a “smart,” adaptable networked factory that brings together data from supply chain and logistics, design, production and even marketing and sales—and of course from machines and devices themselves, from both inside and outside the factory. The Internet of Things, the cloud and Big Data, with their combined and complementary abilities to collect, store and analyze data, have proved to be a boon for machine learning—and vice versa. The more data collected and analyzed, the “smarter” machines will become. The smarter machines become, the more manufacturers can leverage the gains in quality, efficiency and costs.
And the artificial intelligence that powers machine learning helps to ensure that manufacturers can benefit in a variety of ways from the data generated by highly digitized facilities and connected devices, not only identifying process inefficiencies but remediating them. Imagine a piece of machinery that can self-identify when it needs repairs or maintenance before a breakdown occurs. Swiss manufacturer ABB used machine learning techniques to develop a computer-based system that deploys real-time metrics to adjust operations, boosting throughput by as much as 5 percent.
AI and machine learning can unlock a veritable treasure trove of timely customer-related insights, both in the B2B and B2C arenas. These insights, coupled with more adaptable machinery, allow manufacturers to quickly pivot to meet customer needs, better predict supply-and-demand dynamics and optimize the supply chain in real time.
Advances in robotics and automation coupled with cheaper costs have come as manufacturers around the world are facing rising labor costs, greater global competition and an increasingly uncertain economic environment. Yet such advances are not without their price. As manufacturers develop smart products and processes, more data and network entry points are created every day.
The U.S. Department of Homeland Security reported in January that investigations of cyber attacks on the manufacturing sector nearly doubled in the year ended Sept. 30, 2015. In fact, manufacturing was the second-most targeted industry for cyber attacks in 2015, according to IBM. While the industry may have flown under the radar as high-profile attacks against the retail, financial services and healthcare industries made headlines, manufacturers’ information, intellectual property and products have become prime targets for cyber criminals.
Not surprisingly, cyber risk is moving up on manufacturers’ list of priorities, ranking in the top 10 risk factors for the first time in our annual Manufacturing RiskFactor Report. More than 9 in 10 manufacturers (92 percent) cite cybersecurity concerns this year, up 44 percent from 2013. Nearly all (91 percent) also cite operational infrastructure risk, including information systems and implementation of new systems and maintenance.
Is the risk worth the reward? While we’re still in the early aughts of Industry 4.0, missing out on the next major wave of industry innovation is potentially deadly. However, before manufacturers can take the leap into automation and AI, they need to build the foundation for business transformation. Cybersecurity and IT risk considerations must be treated as an integral component of innovation—not an afterthought.
This article originally appeared in BDO USA, LLP’s “Manufacturing & Distribution” newsletter (Summer 2016). Copyright © 2016 BDO USA, LLP. All rights reserved. www.bdo.com
