One of the defining characteristics of Industry 4.0 is the smart factory. Not everyone, however, believes the smart factory is a good idea. In fact, Steven L. Blue, President & CEO of Miller Ingenuity, insists smart manufacturing is a dumb idea. “Smart manufacturing has been all the rage in the last few years,” he writes. “And then it was ‘Smart Manufacturing 2.0,’ even though 1.0 was never explained or implemented. These days we are into 4.0.”[1] Unfamiliar with the terms Smart Manufacturing 1.0, 2.0, 3.0, and 4.0, I googled them. I did find the term “smart manufacturing.” Wikipedia explains it this way:
“Smart manufacturing is a broad category of manufacturing that employs computer-integrated manufacturing, high levels of adaptability and rapid design changes, digital information technology, and more flexible technical workforce training. Other goals sometimes include fast changes in production levels based on demand, optimization of the supply chain, efficient production and recyclability. In this concept, as smart factory has interoperable systems, multi-scale dynamic modelling and simulation, intelligent automation, strong cyber security, and networked sensors. The broad definition of smart manufacturing covers many different technologies. Some of the key technologies in the smart manufacturing movement include big data processing capabilities, industrial connectivity devices and services, and advanced robotics.”
What I didn’t find was any discussion about Smart Manufacturing 1.0 through 4.0. Instead, I found plenty of discussions about four Industrial Revolutions, the latest known by the nickname Industry 4.0.
It appears to me that Blue tried to equate the term “Industry 4.0” with the term “smart manufacturing.” They are not the same thing — although, as I noted above, the smart factory is the centerpiece of the Fourth Industrial Revolution. That doesn’t mean that Blue’s concerns should be ignored or dismissed. And what is his greatest concern? It’s that, in an effort to modernize, the important role people play in manufacturing is being ignored. He explains, “Do these smart machines find new ways to improve processes? I doubt that. Do these smart machines innovate new ways to do things? I doubt that. And how do your employees feel about all these smart machines? Do they view them as threats? Probably. Smart manufacturing cannot be very smart if you have ‘dumb’ employees. As long as you treat employees as dumb, I guarantee they will act that way.” He has a point. As any good business consultant will tell you, successful organizations focus simultaneously on people, processes, and technology.
Improving People, Processes, and Technology
Improving your people. Supply chain journalist Robert J. Bowman, asks, “Does the vision of a ‘new normal’ on the factory floor exclude the presence of people at all?”[2] He doesn’t think so. He insists, “Humans are in key ways indispensable. Their judgment remains critical, even in the age of artificial ‘intelligence’ — at least until machines have grown a lot smarter than they are today. To be sure, the human role is changing; people aren’t needed to push buttons or validate the quality of widgets speeding along a production line. But neither are they destined for the metaphorical scrap heap, in all but the simplest manufacturing environments.” That means the human workforce must be educated and trained to work in a technologically advanced factory. Blue writes, “Help them be the smart people they are. Most employees want to be smart and contribute. If they don’t, you probably have the wrong people. Build the foundation for your house before you put the roof on. The foundation of any business is its people. Invest in your people before you invest in smart machines and the so-called factory of the future.”
Improving your processes. Bill Gates once noted, “The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.” Industry journalist Roberto Torres adds, “Experts caution against plugging automation into processes that were inefficient at the outset. Software can go to waste without proper implementation.” In other words, it’s worth both the time and effort to ensure business processes are optimized before automating them. Amy Loomis, research director, Future of Work at IDC, told Torres, “Automating something that doesn’t work well just makes it not work well faster.”
Improving your technology. Once your people and your processes are in place and in order, it’s time to investigate which technologies are going to have the greatest impact on your business going forward. One place to start looking is in the area of cognitive technologies. As I noted in another article, “Throughout the industrial value chain, artificial intelligence (AI) and machine learning (ML) have been adopted at an accelerating rate. According to a 2021 Google Cloud report, 76% of manufacturers have turned to digital enablers and disruptive technologies such as data analytics, cloud, and AI. … As AI-enabled tools continue to evolve, manufacturers need to implement the latest technology and management practices to remain competitive.”[4] Tech journalist Kerem Gülen insists, AI and big data are the driving forces behind Industry 4.0. He explains, “Industrial automation is at the forefront of the application of big data and artificial intelligence in the physical world, spurred by soaring global investment in robots. … Advancements in both sectors are combining to produce machines that are smarter and more competent than before, with robotics serving as a machine’s body and AI serving as a machine’s mind. Robots may now function more freely in unstructured settings like factories or warehouses. They can work more closely with humans on assembly lines, meaning they are no longer limited to simple, repetitive jobs.”[5]
Concluding Thoughts
As manufacturers embrace Industry 4.0 technologies, they need to ensure a business case can be made. Honestly, that’s not too difficult to do — especially when it comes to artificial intelligence. Writing for Toolsgroup, Erin Wagner discusses “five ways manufacturers are uncovering success by using AI to process information faster and perform more complex roles.”[6] Those five use-cases are: 1) Optimizing equipment maintenance; 2) Performing real-time quality checks; 3) Using computer algorithms for design and production planning; 4) Maximizing shop floor productivity; and 5) Leveraging machine learning in supply chain planning.
As I noted in a previous article, business leaders need to understand that there are all sorts of cognitive technologies to investigate. In that article I wrote, “Before implementing a new technology, it is imperative that manufacturers understand that a human-like reasoning AI and ML are different and complementary capabilities, and that the future of AI is taking data analysis one step further by combining computational intelligence with human-like reasoning and decision-making. This next wave is called Autonomous Decision Science™ (ADS®). ADS technology can autonomously analyze data, generate insights and make subtle, contextually informed, judgment-based decisions quickly, accurately and with limited human intervention, and then learn from the results of those decisions. It can effectively reshape the way companies, including manufacturers, structure and optimize their value chain.”[7] The headline of this article asks, “Is Industry 4.0 a smart way forward?” Implemented correctly (i.e., ensuring that people, processes, and technology advance together), the answer is “yes.”
Footnotes
[1] Steven L. Blue, “Why Smart Manufacturing Is a Dumb Idea,” IndustryWeek, 17 October 2022.
[2] Robert J. Bowman, “Is It ‘Lights Out’ for Humans in the Factory?” SupplyChainBrain, 29 June 2020.
[3] Roberto Torres, “To succeed at RPA adoption, don’t automate inefficient processes,” CIO Dive, 5 February 2020.
[4] Stephen DeAngelis, “Why Manufacturers Need to Rethink AI in Supply Chain,” Industry Today, 27 May 2022.
[5] Kerem Gülen, “AI and Big Data are the Driving Forces Behind Industry 4.0,” Dataconomy 7 November 2022.
[6] Erin Wagner, “5 Ways Businesses Are Uncovering Success With AI In Manufacturing,” Toolsgroup Blog, 20 September 2022.
[7] DeAngelis, op. cit.
