Artificial intelligence in manufacturing: Lean vs. Industry 4.0

The role of artificial intelligence in manufacturing

AI is helping manufacturers navigate through uncertainty, empowering them to be more reactive, more agile, and more consistent with their decision making. However, there’s much more to AI than shiny robots on your factory floor and some of the other applications that first spring to mind when people talk about 4.0. 

In fact, it’s some of these common connotations that lead many manufacturers to view AI as something not entirely tangible. Many of those we speak to claim that AI and 4.0 sound positive and are on their future roadmap, but their data, their current technology landscape, and their thinking are not in a place yet to even consider AI.

While this attitude is legitimate, and AI can be indeed seen as a part of Industry 4.0, I think a more fruitful way of conceptualizing AI in the manufacturing sector is more in the lineage of how manufacturers now see Lean; something that is the core fabric of their organization, and is a must-have skill set to compete in the modern world.

Consequently, by viewing AI under the lens of a process improvement technique or philosophy akin to Lean, the pitfalls of having AI as an ‘expensive toy’ or delaying an AI implementation can be avoided, and can propel manufacturing into the next competitive paradigm – just as Lean has done.

Artificial intelligence in manufacturing: some similarities with Lean

Through conversations I’ve had with many of Peak’s manufacturing customers, I’ve noticed a number of both surface and deeper similarities between AI and Lean. Here’s some information on just two of those similarities…

Changing the way organizations compete

The introduction of Lean demonstrated that you could follow multiple operational objectives simultaneously, which was contrary to the proceeding logic within industry. I would argue that AI does exactly the same, potentially much faster and much more dramatically than Lean. At a high level, you can basically say that with AI, you can switch from one operating objective to another in more or less a flip of switch! This allows organizations to operate the most efficiently, whilst still achieving end user value.

Enabling humans to work smarter, not harder

Another key feature of the nature of Lean is to cognitively reduce the burden on organization members. The classic example of this is the use of visual management techniques such as Kanban systems to signal pull within the shop floor.

Lean designs systems around shop floor operators and does not give them hard rules to follow and then berate them for not doing it. We have seen the use of AI to follow Lean’s lead of reducing cognitive strain, but in a slightly different way. It takes complex data and combines it in such a way that it gives a simple output to the business user for them to make the right decision.

Further reading on this topic

In my view, AI is analogous and complementary to Lean thinking in manufacturing. Although technological advances have been key throughout the sector’s history, they’ve all led to the enablement of new ways of thinking; new ways of looking at production systems and the way manufacturers are organized by paradigms like Fordism, Taylorism, and Lean. Decision Intelligence is the next chapter of that journey.

My new whitepaper, AI in the lens of Lean, not Industry 4.0, is now available to download if you’re interested in exploring this topic in more depth. In the guide, I delve deeper into similarities between AI and Lean, and introduce you to the benefits of Decision Intelligence – the commercial application of AI to optimize decision making in businesses. I hope you find it interesting and look forward to hearing your thoughts!