By Lance Eliot, the AI Trends Insider
Just about everyone has heard of the Industrial Revolution and how it changed everything.
Fewer know that we have presumably been through several iterations or progressive versions of the Industrial Revolution. Depending upon which research you wish to accept, there have been three industrial revolution instances, and we are either in, on the cusp of, the fourth.
The latest iteration is referred to as the Fourth Industrial Revolution, or some prefer to note it cannily as simply Industry 4.0. If Industry 4.0 isn’t cool enough, there is also the further shortened notation of I4.0. You can go even shorter and use just I4.
If you want to impress your friends and strangers too, you can try mentioning I4 and see what they say. The odds are that unless they realize you are contextually discussing the iterations of the Industrial Revolution, they will probably think you are mentioning a model of an automaker’s particular car, or perhaps referring to an interstate highway. Probably easiest to stick with Industry 4.0 and only switch to saying I4.0 or I4 when among colleagues and debating the ins and outs of this presumed latest iteration of the Industrial Revolution.
The crux of Industry 4.0 is that it contains a grab bag of leading-edge high-tech, including Artificial Intelligence (AI) based systems, robotics, Internet of Things (IoT), smart sensors, Augmented Reality (AR), quantum computing, and the like. This is a smorgasbord of any kind of digital technology and might encompass the proverbial kitchen sink, as it were, in terms of the profusion of advanced machinery to be included.
Another crucial element of Industry 4.0 is that the value chain is intended to be made faster and better through the use of digitalization. Within companies, Industry 4.0 means that internal processes are connected and integrated, doing so via computer-based digitalization. Likewise, the same connectivity and integration go with the suppliers, customers, and other partnering elements in the value chain. This is generally known as vertically and horizontally integrating the value chain.
To what end is the Fourth Industrial Revolution trying to take us?
In theory, this Industry 4.0 is supposed to provide a slew of benefits when it comes to making and distributing products and goods. That would be good all around.
The cost to produce items is said to be reduced, leading commensurately to lowered prices for consumers or at least heightened profits for makers. The goods being produced will be tailored to consumers and not quite so mass-produced and no longer excessively vanilla flavored, allowing for those individualistic one-off customizations at an affordable price. Low-volume production will also become more feasible. You won’t have to have gobs of orders for a product to warrant getting the items produced. Etc.
Massively Distributed Manufacturing Emerging as Part of Industry 4.0
For those that are insiders about the Fourth Industrial Revolution, they typically would mention the emergence of Massively Distributed Manufacturing (MDM) as an integral part of the I4.0 equation or evolution.
What does Massively Distributed Manufacturing portend?
You likely are already familiar with the notion of centralized manufacturing, which ostensibly consists of making a product in essentially one place or locale. Something is produced in a large-scale facility and then shipped out to those desirous of the item produced. This is sometimes tongue-in-cheek considered the castle mentality or mindset of how to make a product (all must come to the mighty castle or palace).
It is as though a fortress is in one spot and that all have to come and eventually arrive there to be involved in the manufacturing process for the particular product at hand. Suppliers need to send all the needed inputs to that manufacturing site (i.e., the castle). When finished goods are ready to go, they have pushed out the backdoor and sent along on their way.
In contrast, we might set up a distributed approach to manufacturing.
Rather than centralizing the whole shebang, we could have part of the manufacturing done in location A, and something else done in location B, and so on. This distributed manufacturing means that there isn’t just the one castle involved. The work and processing are distributed among various locales.
You cannot immediately claim that centralized is necessarily better or worse than decentralized, and nor that decentralized is necessarily better or worse than centralized. Tradeoffs make the choice a significant one and are worthwhile to figure out. You might be wisest to choose centralized manufacturing in some cases. You might be most astute to go with distributed manufacturing in some cases. Neither wins in a hands-down always-right runoff (though, just to mention, an argument is made by some that the distributed approach can be construed as a form of democratization of manufacturing and ought to be heralded accordingly, as will be further mentioned momentarily).
The idea of distributed manufacturing via an Industry 4.0 perspective is that you can distribute or set up manufacturing in many geographically dispersed places. These can be small-scale in size. By a proper and digitized means of connecting and integrating the multiple and distributed manufacturing sites, you can achieve the same kind of heightened volume that a single large-scale manufacturing site might attain.
We’ll add the word “massively” to the notion of this distributed manufacturing, and do so to emphasize that this doesn’t just have to be a few handfuls of dispersed locales. If this is done well, you could have dozens, hundreds, maybe thousands of distributed manufacturing sites and they all will ultimately be doing things that are coordinated and ostensibly seamless. For sites that are considered small-scale, they are typically referred to as micromanufacturing sites.
If you are especially curious how the democratization topic gets intertwined, consider that people heretofore had to perchance live near the centralized manufacturing facility to actively participate in the production process. In this MDM approach, people living in scattered locations throughout a country or region of the world would be able to participate. Jobs for those that live just about anywhere might be made feasible.
The MDM approach has a somewhat hidden factor that many do not give much attention to, namely the shipment of goods.
A product that you might purchase from a centralized manufacturing facility on the East Coast would need to be transported all the way across the country to the West Coast if that is where you lived. Imagine instead that the product was manufactured in your local state or county. The distance traveled to get the item would be relatively short in comparison. You could get the product sooner, assuming all else being equal. The cost associated with the product could be lessened if it had normally included the shipping cost.
These factors are widely touted therefore as an overall advantage of trying to produce goods as close as possible to where they will be utilized or nearest to their points of use. Ergo, the excitement for and push toward Massively Distributed Manufacturing.
Now that we’ve brought up the subtopic about shipping or transportation-related to manufacturing, this opens the door to talking about my favorite topic which is Autonomous Vehicles (AVs).
Moving items from place to place is usually done by a human-driven vehicle of one kind or another.
This of course is not necessarily always the case, since you might have within a manufacturing facility an assembly line robotic-like conveyance system that moves in-process items around and there is no human hand involved. You might also have specialized AVs that are purpose-built for shunting around items within a highly controlled environment. Painted lines for example might clearly be marked on the floors and there are oftentimes guardrails or coned-off areas that the simplistic AVs are programmed to go.
Let’s focus on getting stuff from one manufacturing facility to another.
We are herein interested in inter-transit more so than intra-transit without a specific facility. How are we going to get items from manufacturing locale A to say our manufacturing locale B? Assume that those locations are miles upon miles away from each other. Furthermore, assume that the use of public roadways will be required, and we don’t luckily have exclusively private pathways to traverse on.
One aspect of transit entails going from a manufacturing site to another one. We can also consider the transit required of a supplier sending raw materials or partially finished goods or other items to a manufacturing site. There are plenty of transit needs that will arise. Another would be the transit of getting the completed product to the intended points of use.
Autonomous vehicles could be a boon for undertaking that massive amount of transit needs for massively distributed manufacturing (that sounds catchy).
We could use self-driving cars, self-driving trucks, self-driving drones, self-driving planes, self-driving ships, self-driving submersibles, and all manner of self-driving variations of vehicular systems. They are considered autonomous, or some say fully autonomous, if they do not need a human driver or human pilot at the wheel.
A scenario involving the use of AI-based true self-driving cars will serve handily here as a convenient means to explain how this might work.
Before we get into the scenario, it might be helpful to clarify what is meant by AI-based true self-driving cars.
For my framework about AI autonomous cars, see the link here: https://aitrends.com/ai-insider/framework-ai-self-driving-driverless-cars-big-picture/
Why this is a moonshot effort, see my explanation here: https://aitrends.com/ai-insider/self-driving-car-mother-ai-projects-moonshot/
For more about the levels as a type of Richter scale, see my discussion here: https://aitrends.com/ai-insider/richter-scale-levels-self-driving-cars/
For the argument about bifurcating the levels, see my explanation here: https://aitrends.com/ai-insider/reframing-ai-levels-for-self-driving-cars-bifurcation-of-autonomy/
Understanding The Levels Of Self-Driving Cars
As a clarification, true self-driving cars are ones where the AI drives the car entirely on its own and there isn’t any human assistance during the driving task.
These driverless vehicles are considered Level 4 and Level 5, while a car that requires a human driver to co-share the driving effort is usually considered at Level 2 or Level 3. The cars that co-share the driving task are described as being semi-autonomous, and typically contain a variety of automated add-on’s that are referred to as ADAS (Advanced Driver-Assistance Systems).
There is not yet a true self-driving car at Level 5, which we don’t yet even know if this will be possible to achieve, and nor how long it will take to get there.
Meanwhile, the Level 4 efforts are gradually trying to get some traction by undergoing very narrow and selective public roadway trials, though there is controversy over whether this testing should be allowed per se (we are all life-or-death guinea pigs in an experiment taking place on our highways and byways, some contend).
Since semi-autonomous cars require a human driver, the adoption of those types of cars won’t be markedly different from driving conventional vehicles, so there’s not much new per se to cover about them on this topic (though, as you’ll see in a moment, the points next made are generally applicable).
For semi-autonomous cars, it is important that the public needs to be forewarned about a disturbing aspect that’s been arising lately, namely that despite those human drivers that keep posting videos of themselves falling asleep at the wheel of a Level 2 or Level 3 car, we all need to avoid being misled into believing that the driver can take away their attention from the driving task while driving a semi-autonomous car.
You are the responsible party for the driving actions of the vehicle, regardless of how much automation might be tossed into a Level 2 or Level 3.
For why remote piloting or operating of self-driving cars is generally eschewed, see my explanation here: https://aitrends.com/ai-insider/remote-piloting-is-a-self-driving-car-crutch/
To be wary of fake news about self-driving cars, see my tips here: https://aitrends.com/ai-insider/ai-fake-news-about-self-driving-cars/
The ethical implications of AI driving systems are significant, see my indication here: http://aitrends.com/selfdrivingcars/ethically-ambiguous-self-driving-cars/
Be aware of the pitfalls of normalization of deviance when it comes to self-driving cars, here’s my call to arms: https://aitrends.com/ai-insider/normalization-of-deviance-endangers-ai-self-driving-cars/
Self-Driving Cars And Massively Distributed Manufacturing
For Level 4 and Level 5 true self-driving vehicles, there won’t be a human driver involved in the driving task. All occupants will be passengers; the AI is doing the driving.
One aspect to immediately discuss entails the fact that the AI involved in today’s AI driving systems is not sentient. In other words, the AI is altogether a collective of computer-based programming and algorithms, and most assuredly not able to reason in the same manner that humans can.
Why this added emphasis about the AI not being sentient?
Because I want to underscore that when discussing the role of the AI driving system, I am not ascribing human qualities to the AI. Please be aware that there is an ongoing and dangerous tendency these days to anthropomorphize AI. In essence, people are assigning human-like sentience to today’s AI, despite the undeniable and inarguable fact that no such AI exists as yet.
With that clarification, you can envision that the AI driving system won’t natively somehow “know” about the facets of driving. Driving and all that it entails will need to be programmed as part of the hardware and software of the self-driving car.
Let’s dive into the myriad aspects that come to play on this topic.
Suppose there is a micromanufacturing site near your hometown. They make widgets. And about twenty miles from that site there is an associated manufacturing site that also makes widgets. Turns out they make a ton of widgets. Furthermore, they are part of a larger collective that could be considered a massively distributed manufacturer and are spread throughout the country.
We’ll refer to the micromanufacturing site that is closest to your hometown as Widget Site 1. The other site that is approximately twenty miles away will be labeled as Widget Site 2.
One day, a manager at Widget Site 1 realizes that they are running low on essential supplies that go into making their widgets. Fortunately, Widget Site 2 has an oversupply and willingly will provide the components to Widget Site 1. This is an ongoing reciprocal arrangement, akin to a classic of scratch my back and I’ll scratch yours.
The normal approach would be to have someone working at Widget Site 1 get into a car and drive over to Widget Site 2. Upon getting the needed components loaded into the vehicle, the employee would then drive the materials back over to Widget Site 1. The drive time for this journey is about an hour, plus another half hour to load and unload the vehicle.
The Widget Site 1 manager has to use the precious and limited labor at the manufacturing facility to do this chore. It takes a person that could be working actively in the manufacturing process and instead turns them into a delivery driver. In addition, there are of course the usual risks that are entailed in making such a drive, wherein the person could get regrettably entangled in a car crash or other calamity during the driving chore.
This is where self-driving cars step into the picture.
The manager at Widget Site 1 dispatches one of the self-driving cars that the manufacturing firm owns. Without any need for a human driver, the autonomous vehicle drives over to Widget Site 2. At Widget Site 2, someone loads the components into the vehicle and then signals that it can proceed back to Widget Site 1. If anything goes awry during the driving journey, the AI driving system will automatically alert the manager at Widget Site 1.
Notice that this allows Widget Site 1 to continue working without any disruption by having had to send an employee on this necessary errand. This also avoids any potential issues of the person getting mired in a car accident or similar concern. The AI driving system will do as instructed and drive as expeditiously as feasible to get the materials and return them. No lunch breaks are needed.
A human driver might be tired and not fully attentive to the driving task. A human driver could get waylaid during this chore, perhaps opting to make some side stops to get coffee or do some other non-related errand. And so on.
Now that we’ve covered that singular example, let’s up the ante, as it were.
Imagine that daily trips are being made back and forth between Widget Site 1 and Widget Site 2. There could be lots of good reasons for a frequent series of trips. Multiply all those trips times the amount of labor that would have been required, along with the risks of injury or calamity while on the road, and the resultant total becomes notable.
Thus, on a once-in-a-blue-moon trip basis it might not seem especially significant, but if you multiply things out and are doing this daily, perhaps amounting to thousands of trips per year, it all adds up. The firm reduces the excess cost of labor used for the delivery chore. The firm uses the labor toward the act of manufacturing and doesn’t need to deplete the labor pool by these side trips. Plus, there is lowered risk for the humans that would have been doing the driving.
You can zoom further out and take a sizable macroscopic view.
Pretend that there are dozens of these widget-making manufacturing sites, scattered throughout the US. They are all willing to share with each other as needed. Getting items from one location to another could be quite onerous and costly.
Via the use of autonomous vehicles such as self-driving cars, self-driving trucks, and the like, they can be sending items to each other without the labor required to do so. Another factor is that those lengthier trips would normally necessitate the drivers taking breaks, sleeping overnight and not driving 24×7, etc.
With self-driving vehicles, the AI driving system can operate all of the time. There is no need for breaks or sleep. Of course, refueling of the vehicle would likely be required. Currently, the refueling does tend to involve a human at the pump that connects the fuel to the vehicle, though the latest capabilities are doing away with this aspect and the pump will automatically extend and connect to the AV.
For more details about ODDs, see my indication at this link here: https://www.aitrends.com/ai-insider/amalgamating-of-operational-design-domains-odds-for-ai-self-driving-cars/
On the topic of off-road self-driving cars, here’s my details elicitation: https://www.aitrends.com/ai-insider/off-roading-as-a-challenging-use-case-for-ai-autonomous-cars/
I’ve urged that there must be a Chief Safety Officer at self-driving car makers, here’s the scoop: https://www.aitrends.com/ai-insider/chief-safety-officers-needed-in-ai-the-case-of-ai-self-driving-cars/
Expect that lawsuits are going to gradually become a significant part of the self-driving car industry, see my explanatory details here: http://aitrends.com/selfdrivingcars/self-driving-car-lawsuits-bonanza-ahead/
In a sense, a silent and unnoticed army of self-driving vehicles are bound to become an integral part of Industry 4.0, including as a means of physically interconnecting those MDM sites. The belief is that AVs will run at a lower cost per mile than would the comparable human-driven vehicle. Ergo, there is a multitude of cost savings that will arise.
Some envision an eerie sight of all these self-driving cars and self-driving trucks driving around without any human driver inside. There is no doubt that it will take some getting used to seeing, and at first, the whole shebang will be quite a spectacle. After a while, the odds are that we will all take the matter in stride and the use of AVs for tasks like this will become the new normal.
Do not mistakenly think this will be some Utopian-like future. You can assume that there will be issues, such as:
How will humans that once relied upon driving as their money-making role be able to make a living?
Will self-driving vehicles be subject to difficulties that would not normally confront a human-driven vehicles?
Might hackers be able to take over self-driving vehicles and wreak havoc accordingly?
What happens if a human-driven vehicle crashes with a self-driving vehicle?
On and on.
You can add those considerations to a long list of the issues that are not yet fully known about the emergence of the Fourth Industrial Revolution.
Presumably, once we figure out those answers, we’ll be ready to proceed to Industry 5.0, the next iteration after the vaunted Industry 4.0, and enter into the Fifth Industrial Revolution (seems like we can keep on counting up as we go).
Well, to be cool, let’s just say I5.
Copyright 2021 Dr. Lance Eliot
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