11 Ways Artificial Intelligence Will Transform Manufacturing
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Matt Kirchner spent his career running manufacturing companies. Now, he shares his knowledge with listeners of Webinar Wednesday and the TechEd Podcast. In this article, Matt gives us 11 predictions for how artificial intelligence will totally transform manufacturing. To view this article as a video presentation, click here.

Manufacturing Transformations of the Past

You know, there’s a handful of things that have differentiated world class manufacturers from average ones in the last several decades. The organizations that embraced change surged ahead, while the others were left behind. To be clear, it’s not that those left behind weren’t great companies. They may have been. But they were left behind because technology and manufacturing practices changed, and in the wake of that, they had a sense of apathy.

Industrial artificial intelligenceThis is a film we’ve seen before. If we look back 30 years, standardized quality systems were coming of age in manufacturing. Companies that invested in ISO, QS and TS found themselves surging ahead. I ran one of the largest contract metal finishing operations in America for 10 years, from 1998 to 2008. We were the first in our industry anywhere in the country to get ISO registration. Suddenly, we were able to compete for work we had never been able to compete for. Suddenly, we had the interest of large OEMs because we are ISO registered. It allowed us to gap the competition.

It happened again in the zeros when companies started investing in continuous improvement, Kaizen and driving waste out of their systems. These companies were able to drive a ton of cost out of their business models. They could compete on price when they had to. And then they could reinvest in their business with the savings. Suddenly, those companies were able to lurch ahead of other companies that were not making investments in continuous improvement.

Adopt AI or Fall Behind

So here we are in 2021, and I would say that this same sequence is happening. We have industrial companies that see the huge sea change that artificial intelligence will bring to the world of manufacturing. And those companies are the ones – mark my words – that in the next 10 years will gap everybody else.

As I talk to large companies, large OEMs, and Fortune 500 companies, they see this change coming. They’re making huge investments in artificial intelligence, Industry 4.0 and smart technology.

But as we talk to small and medium sized manufacturers, a lot of them are shrugging their shoulders and saying we just don’t see it in our business. Unfortunately, they are doing this at their own peril, because this freight train is coming down the track. The question is whether or not we see it soon enough to adjust our business models to be able to take advantage of what AI and smart technology bring us.

11 Predictions for Industrial Artificial Intelligence

So in this article, I’m sharing 11 predictions of how industrial artificial intelligence will totally change the world of manufacturing in the next 10 years.

#1: Autonomous trucks and vehicles will transport materials from suppliers to production lines to customers

AGVs will use artificial intelligence to transform manufacturing

In ten years, there won’t be truck drivers going from one facility to another to transport goods. And there won’t be fork trucks driving all over our plant floors with drivers on them.

All of this transportation of material will become autonomous in the next 10 years. Trucks will drive themselves from facility to facility to deliver materials. Once there, AGVs (automated guided vehicles) will drive that material around the plant and deliver it to the production line. This will continue until we have completed parts that can be delivered to the end customer.

#2: Using vision systems, robots will load an unload your production equipment

We see this already in a lot of manufacturing facilities where we’re using industrial robots to load and unload manufacturing equipment. But this practice will become ubiquitous in the next 10 years.

Part of the challenge right now of using robots for loading and unloading equipment is that in many cases, people are much better at things like identifying parts and understanding how to place the part in the fixture. Human eyes can see better than a vision system on a robot, at least for now. Using artificial intelligence, that technology will advance drastically so that by 10 years from now, robots will load and unload your production equipment.

#3: Artificial intelligence will tell suppliers exactly what value of materials to produce, inventory and ship

Right now there’s a lot of waste in our supply chain. A customer might need 10 parts, so we make 12 just in case we have two that aren’t quite right. We also have waste in the supply chain of inventory sitting between processes. This runs the risk of obsolescence, damage, and changes in the economy that may affect the pricing structure we should be paying for that material.

Using AI and blockchain technology, if you’re a supplier of materials, you’ll know exactly how much of your material to buy to be able to manufacture whatever it is that you’re providing to your customer. And that customer will know exactly how much to manufacture.

In other words, manufacturers will know exactly what the demand is from the next step in the supply chain all the way down to the end user. This will all happen without people doing anything. We will have artificial intelligence, algorithms, and computer technology analyzing all this data and predicting it for us.

#4: The difference among material suppliers will be who can best predict customer consumption and meet it in real time

We learned in our previous prediction that we will drive waste out of our supply chain because artificial intelligence will tell us exactly how much to produce based on end customer demand.

Well, if that is the case, then our ability to compete for manufacturing customers will be based on who can best predict what their demand will be, and then meet it in real time. There won’t be inventory sitting at the front end of the manufacturing process or, for that matter, at the back end of the manufacturing process. This drives all the cost of carrying inventory out of the model.

#5: Your supplier’s MRP or ERP system will tell your MRP or ERP system that the materials are on the way

Gone will be the emails between people and manufacturing facilities saying, “Hey, we’re shipping the parts,” “Hey, the order is on its way,” or “We need to expedite this,” or “When will this be here?”

All of that will disappear in the next 10 years because AI and our MRP systems will be talking with each other and making those decisions between themselves to drive out all of that waste from the supply chain. So 10 years from now, our MRP system will know exactly what materials are coming from our suppliers. They will know exactly what customer demand and expectations are, so we won’t have people trying to figure that puzzle out anymore from company to company.

#6: Your production lines will schedule themselves

artificial intelligence allows manufacturing operations to schedule themselvesI’ve been in a lot of production planning meetings. They still happen all the time where we get together in the morning and everybody sits around a big table and we talk about what orders are coming in, what orders are late, what orders are being expedited, who’s having problems on which line, what time the parts are going to leave this line so they can get to that line, what time they’re going to leave this department so they can get to that department…

Artificial intelligence will replace the need for these meetings in the next 10 years. There are a lot of complex variables that go into running a manufacturing operation. Industrial AI algorithms will calculate that information and analyze it much, much better than we can. They’ll take everything that those systems know about our manufacturing operations, our customers’ expectations, our processing time, our throughput, our material availability and optimize our production schedule.

#7: Process-based manufacturing will be completed automatically

I’m talking here about heat treating, metal plating, powder coating, food production – any manufacturing environment that relies on complex reactions of materials and processes. All the different variables that go into the manufacturing operation, including titration, analysis, material addition or process change, will be completed automatically.

Right now, we still have people running around taking samples from tanks and performing analyses manually. In the future, all of that will be completed automatically. Smart sensors and devices will gather the needed data in realtime, send it to an algorithm to process, and then decide what changes to make. AI will send that information back to an output device to make the change.

Or even better, given the fact that smart sensors and devices can communicate with each other, we may not even need to send that information up to a network or through a PLC. We could actually take that information and have it communicated sensor-to-sensor or device-to-device. And that will drive out the requirement for bandwidth and the latency that takes place when we send that information over our networks.

#8 Quality defects will be driven out of your manufacturing operations using in-process inspection and digital twins.

Vision technology is advancing to the point where it is getting better at identifying quality defects – and not just dimensional defects, but all types of quality defects. The data gathered by these vision systems and smart sensors will be sent to our digital twin software to analyze. The digital twins will use this information to understand the process, the cause of defects and be able to make changes in the process that remove these defects. As a result, our quality defects will reach zero, and our yield will grow t0 100% in the next ten years.

#9: Leading manufacturers will use artificial intelligence with smart technology to improve margins

Industrial artificial intelligence will help us increase margins30 years ago, manufacturers started using standard work, and later kaizen and continuous improvement practices came along to drive cost out of manufacturing operations. The companies that adopted those practices were able to improve their margins.

Improving margins accomplishes two things. First, it allows us to compete on price when it’s necessary to win a job. And second, when we don’t have to compete on price, we can use that excess cash flow to reinvest in our business. And that allows us to continue to gap those companies that aren’t dropping their costs.

Today, companies that are deploying an Industry 4.0 plan should leverage artificial intelligence technology to continue minimizing their costs and transferring that savings to the customer. That will be the differentiator between manufacturers that win new business and those that wither away.

#10: As we drive down cost, those closest to the customer will win

We’ve already discussed how driving out waste and automating our processes using artificial intelligence will result in lower costs for our customers. Another huge differentiator in winning new business will be how close a manufacturer can be to the customer.

If we can remove waste from our supply chain and transport goods to the customer the fastest, we’ll win new business. Other manufacturers will have to wait for product to come from somewhere else – whether that be in their own state, across the country or even across the globe. With so much disruption in the global supply chain, those who re-shore their supply chain in a cost-efficient, time-efficient manner will be able to deliver better product to the customer in less time.

#11: The differentiator among manufacturing equipment suppliers will be who can embed the right smart technology into their systems

Here’s what I mean by that. If you think about a CNC machine, a piece of metal stamping equipment, a powder coating line, heat treating production…any equipment we’re buying and then implementing in our manufacturing operations, it’s all getting smarter and smarter.

Many manufacturers don’t realize how much smart technology is already embedded in the manufacturing equipment they’re buying. This is technology that can help predict quality issues, predict maintenance needs, give us real-time information about operations, throughput, etc. In many cases, all of that data is already available in your manufacturing equipment. You just don’t know it.

And as that technology continues to evolve and we continue to use more AI in our manufacturing processes to drive out waste, the companies that make the right smart technology available on the manufacturing equipment they’re selling to their customers are the ones that will come out on top.

So there you have it, 11 predictions for how industrial artificial intelligence will transform manufacturing in the next 10 years. AI is going to make a huge huge difference in the future success of manufacturing, so prepare your organization.

But there’s one more thing…

Will People Lose Their Jobs to Artificial Intelligence?

I know what many of you are thinking. “What is going to happen to all of these people who lose their jobs?” As we replace human tasks with artificial intelligence, what happens to that chemist who’s now doing titrations that will someday be done automatically? What happens to the forklift driver who will be replaced by an automated guided vehicle?

Artificial intelligence can add value to human workWill people lose their jobs as a result of artificial intelligence? My answer is…absolutely. Of course artificial intelligence will make some careers obsolete. But this isn’t surprising, nor is it the end of the world as we know it.

The Sloan School at MIT did a study of 1,500 organizations. They asked executives if there are jobs in their organizations today that will go away because of artificial intelligence. Their answer was…absolutely. Artificial intelligence will certainly eliminate jobs. We’d be naive to think they wouldn’t.

But AI will also create a lot of good jobs that leverage our human capabilities in different ways. This is the message for us today as our manufacturing operations transform: we must prepare our workforce for the future of manufacturing technology, and we must prepare our young people for the future of manufacturing technology.

There will be career opportunities in manufacturing for our students that don’t even exist today. Our job is to figure out how we retrain our incumbent workforce to work in that environment. And our job is to figure out how to inspire and prepare our students for tomorrow’s jobs in smart manufacturing.

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