This is a reference to the market research report that the department purchased for us that was just loaded with all kinds of information. I mean, more than we can fit in a semester and it is used with permission so you can- I will make PDFs of all these slide decks and put them on D2L each week. We have a wide open license so you can take these slides with you and use them however you want. So, the slide deck, I tried to define what other learning outcomes are, one, to define what industry 4.0 means, understand what the precursors and the enabling factors are then enabled. What's taking place right now, is transformation line of manufacturing and so forth that I alluded to and some of these folks were just speaking about. Understanding all the business considerations, the benefits. Understanding these influencing factors, market dynamics, drivers and restraints, opportunities and challenges many markets face or have these forces at play in varying degrees, those things that are trying to push technology solutions and ideas forward and there are challenges and resistance to change that pushback against that adoption. A few words on the technical proposition about why this makes sense from a technical perspective understanding the growth potentials which are pretty dramatic when you see the numbers, be coming up here. We'll look at what I think are the key application areas that I highlighted that were on there on the right side of that slide where I had medical and retail in the middle that I didn't quite personally consider industrial and that's again a decision on the call that I made who the top players are so you probably know some of them but we're going to try to get all those companies out there so you can go and look at their websites and look for job opportunities at these places because there's so much growth there there's going to be a tremendous amount of hiring that takes place. So, Cisco, I think this was this was from McRock Capital in not markets and markets. I think the CEO was quoted as only one percent of the world's devices was last year 2017, connected the opportunity for new business to be created that will help industries derive value from all of the data that will be available, saying that there's tremendous potential there. Shell oil has developed what they call smart wells so they put sensors down the hole where they're extracting hydrocarbons and they monitor reservoir dynamics of water flow, gas movements, pressure changes, compaction and they're realizing substantial savings in their oilfields. GE utilities, they suffer- I was pretty surprised in the US to find out that the US utility suffer $200 billion in annual electrical losses due to theft, people stealing electricity. It's a huge number. So GE, its product called True Grid, provide situational awareness with actual line data, monitoring the line data and reducing their financial risk by truing up conventional building processes with smart meters and the data to back that up to match that with the actual consumption and they can pinpoint where theft is occurring as well as identifying billing and metering error, so, the utility industry can save a lot of money. I heard a story one time about a farmer that had those high tension wires running across this property and he went out and took some wire and wrapped it around a tube of cardboard and ran it through an inverter to turn on a light or something and they eventually found it because they were able to notice that little bit of that additional loss or maybe he was running a pump to pump water or something that they were able to identify it. These are some comments from a company called Accenture. These are just some highlights that they felt that these were like executives must-do kind of notions. So, they believe that these business leaders are under some pressure to increase production that they need to create hybrid business models and we have some good examples coming up later in the semester. Sure one of them has to do with a tire company which I particularly like, I just thought it was fabulous adaptation. They want to fuel innovation within side their company they want to empower their employees to think of new ways to be creative, how to create new products, how to create new services. They want to transform the workplac. we saw one of the gentlemen in the video talk about increase in white-collar jobs on the factory floor within the industrial environment and transforming the workforce. I particularly like this one also, Rio Tinto was a gravel and sand operation in Perth Australia and there's no operators that sit in the vehicles. All the operators sit on this remote command center and work with data analysts to orchestrate the actions of these huge drills and excavators and earth movers and dump trucks to conduct their business and there's nobody in the big machines, that's pretty cool. Of course, these are instrumented, they know right where it is, they know how much material is in the back of the dump truck and they know right where it is and they can transport it from point A to point B. It's a lot about what trimble does, also trimble's much like that. Folks at Accenture thought it was important for business leaders, CEOs and the leaders of companies to think unconventionally about what is valuable to customers and it's changing and it's really comes down to this statement as to be the most valuable information provider. Why do we like our cell phones? Why are we addicted to our cell phones? What do cell phones do for us? Gives information from worldwide. Yes. It's this enormous funnel of information that we can craft to our own liking. Sometimes too much Facebook post, Facebook post, shut that off, it's huge. It used to be the business model for decades was build the best product and compete on the product, sell the product. The world is transforming before our eyes to put much more emphasis on the value of information and data. I heard an executive say that data is the new currency not dollars or yen or whatever. I had to think about that for a little while but it sunk and I get it now. Three capabilities to master within the industrial IoT's basis, intelligent machine applications, analytics and sensor driven computing and we're going to see how that works over the course of this semester. Our good friend Wikipedia, everybody, your brother goes there. Industry 4.0, that's a term coined by the Germans I believe, and they refer to it as the Fourth Industrial Revolution. So we had, First Industrial Revolution was mechanization with water and steam-powered devices steam engines and Henry Ford and others came along and defined this mass production assembly line idea. The third was computer automation, but these were just brute force like the gentleman in the video said, just doing heavy tasks like picking this heavy thing up and holding it in place during a car assembly and in a car assembly line so a human being wouldn't have to do that heavy lifting for instance. But there was no real intelligence or any kind of analytics, it just grabbed apart and it just put it over in place and wait for it to get welded into place and then it would go get the next one and so forth. So it was offloading physical labor and to strong machines. The fourth one are the cyber-physical systems which leverage off of what was done in the computer and automation world, but it's highly, highly instrumented with wireless sensors, data collection, data analytics, machine learning, and this is what is transforming the business in the manufacturing world and these are the segments that we're going to look at. So there's an Industry 4.0 Workgroup, we'll see that there's a number of these consortiums that are formed. The Industry 4.0 Workgroup puts forth four design principles, first one is interoperability to connect and communicate via the Internet and we'll see this is actually one of those restraints in the IoT because there are an enormous number of communication protocols legacy and new and emerging protocols that are all vying for space or dominance or adoption in this entire ecosystem. But ideally, you'd want any device to be able to talk to any other device and collect all that data and take a look at it. Information transparency, this is the ability to create a virtual copy of a physical system. I alluded to system using system C to create a virtual model of a physical system and feed it with data from the real system and you could modify that data to see how the physical system response to changes in that data. Technical assistance to provide support to humans by aggregating information into visualizations, perform safe operations that are unpleasant or too exhausting and or are unsafe for human beings. Decentralized decisions, the ability of cyber physical systems to make decisions on their own. This might be an intelligent embedded system receiving data from some sensors and making a decision all on it's own to speed up production or slow down production. It may run diagnostics on itself and detect that it's going to fail, so it will alert the operators that the component within itself is about to fail, instead of waiting for a component to actually fail, it predicts that it's going to fail and reports it so a service can be done and the manufacturing line, for instance, can stay up and the more that line stays up, and when you think about it, if a manufacturing process is running 24-7 and some part of it goes down and then get behind and they're delivering their product to their customer for the period of time that it takes them to implement the fixes and they might have to order parts that need to come from halfway around the world or something. So if a system can identify that ahead of time before a product or a piece breaks down, that's huge. So, now let's take it into Industry 4.0 and the smart factory. So Industry 4.0 comes out of Germany, like most things out of Germany it comes out of a consortium. They're very planful group of people, I don't know if you know that, but the Germans are very planful. They also tend to try to make decisions in a way that creates standards and they all follow the standards. But Industry 4.0 is the fourth major reset in the history of factory in factory automation. So just a little background, Industry 1.0 was mechanical production powered by steam and water. 2.0 was in the 19th century, this was the assembly line four. Industry 3.0 was the first use of computers and automation. In this world they're called programmable logic controllers, but they're really just specialized computers for factory automation. Industry 4.0 is intelligent production incorporated with the Internet of Things, cloud technology, and big data. So the ability to collect information, the ability to share information, and the ability to use that information to make better decisions and to be more productive and also to be far more decentralized in the way you control things and the way that you make decisions. So the big things that have changed is that Industry 3.0 was a very centralized control structure. So you had a supercomputer PLC that was talking to relatively unintelligent actuators and sensors, and it was very much go do that thing. I'm telling you to go do it, go do it. In the New World Industry 4.0, the sensors are collecting information, providing it back to the distributed controller, and in some cases directly to the cloud so that you can monitor activity, and so that you can share information in ways that you haven't been able to do before, and I'll give you an example of how that happens. So a lot more connectivity, a lot more sensitivity to build to demand as opposed to build to inventory. As a result, there's a lot of investment in sensors, a lot of investment in intelligent actuators and whenever it's economically feasible, the notion of every actuator and every sensor having an IP address is the simplest way to think of it, is it everything can potentially be a source of information for you. So an example that comes to mind is there's an application where remote tank monitoring, for example, it used to be that when you has tanks, so this could be natural gas tanks, somebody would get in their truck and they would drive around and they would check how much gas was in the tank and they would record it on a piece of paper and they bring it back to the office and that was how you determine whether or not to fill the tank up again. Those tanks all now have a level sensor with a Wi-Fi device that goes back directly. That person who used to drive the truck around and check doesn't need to be there anymore. It's all connected. So, these are the the terms I use. So the Industrial Internet of Things, Industry 4.0, and Smart factory. Industry 4.0 is what most Europeans call it. If you're in Europe, call it Industry 4.0 and you'll be welcomed. Because that means you're sort of sensitized, and you're acclimated to the whole Germanic community, and they'll understand what you're talking about. Smart Factory tends to be more used in the United States. They're the same thing. It's exactly the same thing. Think of them as interchangeable, they're not really different. Industry 4.0 is just more European, Smart Factory is more US. The Industrial Internet of Things is really just the extension of the Internet of Things as it relates to leveraging the IP address and leveraging the data that exists in the factory. So, what are the major benefits of Industry 4.0? The number one by far is improved productivity, and it's predominantly improved productivity through flexibility and through sharing of information. Second is the ability to have more customized manufacturing. The safety one is interesting, and quite frankly as a direct result of fewer people in the factory. So, if you have a lights-out factory, you don't have any safety concerns, and being able to manufacture on an autonomous basis is very helpful. Then the last is the access for data. So let me walk you through, and I think this is the easiest way to help you understand, how the Smart Factory works. So starting with On Machine and On Data. The controller itself is connected to all these actuators and all these sensors, and the biggest challenge that you have in the machine is how do you modify or change it over from one to the other. In the old days, it was entirely mechanical. If you're going to run, I'll give you an example, Procter and Gamble was a large customer of mine, and in the old days they had one variable speed drive, and they had a mechanical linkage to that variable speed drive to make a product. So let's use diapers as an example. They would make diapers, and they would make them for days or weeks, and then they might change over if there was another version of the diaper. I remember when I first met them, I think they had two or three versions of diapers that they made, and they would set it up for two weeks at a time, put it into finished good inventory. Well, over time, their marketing department convinced them that for us to compete, we need more than two or three versions of diapers. We need, I think they actually went up to 50. Those 50 included, I'm going to date myself, but there used to be a TV show for kids called Barney, or there used to be one called Zoboomafoo or whatever, but they needed to have all these versions of diapers, and therefore the change over time had to change dramatically. They also, by the way, introduced adult diapers, which was a whole new category, and they had to do more changeover. So, with the Smart Factory, and through the connection of the controller and the sensors and the actuators, you have much better ability to reduce change over time, and increase your flexibility. The other advantage is preventative maintenance. So, on these machines, you have a whole wide range of actuators, the ones you saw in the movie. They're either hydraulic, they're pneumatic, or they're electronic. These actuators, like anything, need to be maintained. The sensors can feed information back to the machine, and they can make certain that the machine can be maintained in advance of a breakdown. Unplanned maintenance is the biggest impact to OEE in most factories. So you got changeovers and impact OEE, but unplanned maintenance is a big issue for OEE. By looking at this information, whether it's vibration, temperature, in some cases, it could be the hydraulic fluid, this is all monitored, and you're able to maintain it in advance. Then you get to machines talking to other machines. The obvious question is, "Why would you care about that?" Well, in the old days, the machines before Lean came about, you would build as much of some item subcomponent as you could without consideration to what the next machine down the line was, even though that would drive overall production. The machines are now talking to each other such that if a machine stops, it automatically tells all the other machines to stop as well. Because there's no reason for those machines to continue building product if the machine they're going to send the parts to is not running. So they are now communicating with each other about whether or not they're having problems, and if they are having problems to change. They're also commuting changeover to each other so, believe it or not, these machines are actually sending information to each other about what I need down the line next and whether or not my machine is running. The third is the machine to the back office. So, most people may not know this but one of the longest dwell times or cycle time considerations in getting a product out of the factory is the amount of time it takes the order to get from customer service to the cell. It doesn't make a lot of sense, but it's actually a pretty big issue. This is now all connected. So in a Smart Factory, if you place an order as a customer, the order will go directly to the machine that builds it. So the tennis shoe example I gave you, that's all automated. So it goes directly from the website to the machine. In fact, there's a customer we have that is now building a shoe within 15 minutes of receiving the order on the internet. Can you imagine that? It used to take them a day to get it from the telephone to the factory. This is going directly there. It's also allowing you to get information back from the factory to the back office to be able to analyze how the factory is running. Then the last is factory to factory. So, if you're a large global company and you've got multiple locations that can build the same products, sometimes you may have a capacity constraint of one area and you need to offload that production to another factory. They're now communicating with other factories. So, A factory will signal to another factory that we're at capacity and to begin manufacturing those other products at the other factory. These are all things that would have required sort of human interaction or human intervention in a reactive way in the past, and this is becoming very proactive and very automated. Now, the technology that's pervasive in all this is Ethernet. So Ethernet is the mode of communication that everybody's using. It's obviously what's been used in the LAN environment and the enterprise environment for a long time. Adoption in the factory is increasing. It's still relatively underpenetrated compared to some of the legacy proprietary communication devices, but if you go on a factory floor you'll see a bit of a smorgasbord of communications. You'll see a lot of legacy standards, but you'll see a lot more Ethernet going forward. Ethernet is a wonderful technology in that allows you to do things relatively easily, relatively inexpensively. It allows you to leverage off-the-shelf technology that comes out of the IT environment. So whether it's Cisco or HP products, they're all Ethernet based products, and that's a huge help. It also allows for remote access. So, we're going to talk in a moment but one of the major benefits of the Internet of Things, and one of the major benefits of Industry 4.0, is the fact that people can do things remotely they couldn't do before.
