 So please Houston a warm welcome for this dr. Peter Martin Thank you. It's great to be here. I really appreciate the introduction and I the offer to talk to you today and It's really always fun to talk to a group of people that are looking out into the future And we ought to always be looking out into the future and one of the things I I often say is I'm really disappointed that I'm so old Because the future of this industry is going to be fantastic and I'd like to talk a little bit this morning about some of the things We see coming as we move forward When I joined industry in the 1970s in an industrial automation I found this industry to be the most solution oriented industry that I had ever seen. I had come out of IT. I had Spent my time building software that printed reports on green and white paper And I came into an industry where you actually had products that did work that that made things work I loved it and the way the industry worked was fantastic because you'd have a problem a challenge the Suppliers and the clients would get together Solve the problem and then we'd worry about what technology to use it was a solution driven industry the technology was considered to be a Delivery vehicle nothing more, but that all changed and it all changed almost about the time I came into industry and it it reversed and The the driving force behind the change was digital technology all of a sudden we started using Digital technology rather than analog technology and the technology itself was so complex That it required a whole new group of people that spoke a whole new lexicon that didn't understand a whole lot about control And so you had to vernacular going on you had PID P&ID and on the other side you have bits bytes and bandwidth And they couldn't communicate so all of a sudden the industry shifted From a solutions oriented industry to a technology driven industry in that any time a new technology came out There was a race to be the first supplier to implement it in your products because you knew you can sell I Remember during the 1980s expert systems came out I always loved expert systems, you know all of a sudden you could do heuristics Which we had been doing for 15 years, but you could all of a sudden do them in the 80s And so if you could call something an expert system You could sell millions of them it didn't matter whether the problem you were trying to solve was heuristic or algorithmic didn't matter It's an expert system. We can sell it. I remember we had a product called Automate automatic controller tuner it did loop tuning It was really kind of a neat little tool and somebody said by the way we we had it out for about three years we sold maybe four of them and Somebody was sitting in a meeting one day and they say you know, isn't this an expert system? We said well, yeah, they said we'll call it expert automatic controller tuner and we did exact We called it exact we sold a billion of them within a week I mean it was amazing to see what was going on and it's still happening the problem in our industry right now Was with still so technology driven? We haven't flip-flop back and if you don't believe it just look at the plethora of acronyms that are out there right now IOT IOT cyber physical systems You know cloud fog edge all of a sudden is just plethora of technology terms all of which have value But it what we have to do is weed through that and figure out what the value is so that we can get back To be in the solution or in it industry that we started being I mean this is the goal And as I looked at the charter of the open group and opa I said man This is it this is the goal the goal is to get us back It's to use technology to get us back to solving problems so that we can look at what the challenge is We can develop a solution to the challenge and then figure out what the technology is to implement it The fascinating thing was I ran a consulting team for a number of years maybe seven eight years ago in That time frame I found out with the technology we have today if I could go into a plant and figure out what the problem was We have the technology to solve it It may not all cobble together as easy as we like but the technology is not the barrier to success our Imagination is and we've got to start getting back to being that solution oriented Industry that we were you know 30 40 50 years ago man. It's starting to add up So what I wanted to do was to start looking at key drivers is a bunch of key drivers across industry I want to look at four key drivers that I think of making a big impact today First one is the speed of industrial business continues to increase now the speed of business The processes have always been real time But the speed of business is increasing and that's something that a lot of engineers aren't seen They don't quite see the impact that's having because the business folks don't know enough to go down to the engineers and Help them solve their problems. So we want to look at that one second one Of course has opened an interoperable systems huge step forward third one is greatest People are looking for greater business value from their automation investment It used to be in the 70s 80s and 90s with the technology pole All you had to do is come out with something and everybody would buy it today. That's not happening today We want to be able to add value with the solutions We bring forward and finally technology changes are enabling I should say enabling innovation This is the best time to be an innovator in this industry the technology no longer constraints it our minds do So we have to start using our minds a little bit better So let's take a look at the speed of industry in 1990 when I went out and I started talking to executives They considered things like safety and efficiency by the way process control is to improve Operational efficiency so they looked at safety and efficiency as real-time functions environmental Asset management quality management profit management or all management functions So we'll different it will just differentiate between management and real-time real-time is when you make a decision on the Process time cycle on the time constant decide defined by the process Management is when you make a decision on humans time cycles both are important But in 1990 the only two domains that were considered to be real-time was safety and efficiency today Almost every domain has started to slide down into the real-time realm even profitability and a lot of people aren't seeing this but what happened was we had the Deregulation of electric power grids that was the first domino when a domino effect that has hit our industry over the last 15 years And it depends on where you are in the world when the power grids opened up because they opened up at different times in different parts of the world But when the electric power grids opened up All of a sudden the price of electricity started to experience some variability that we've never seen before So matter of fact 20 years ago most industrial plants could set you know buy their Electricity for the same price for an entire year. They just don't negotiate. Oh, it's 12 and a half cents per kilowatt hour done You don't have to control something that's constant Right all of a sudden with the deregulation of the nuclear power grids We had all kinds of new suppliers all kinds of new consumers now We're having new prosumers They're all getting together and the variability in the grid is going up and down and all over the place So the government's had to jump in and start regulating in the United States the price on the open Electricity grid in the United States can change every 15 minutes by law 15 minutes it was once a year 20 years ago now it changes every 15 minutes in Spain It's every five minutes, and it's not because electrons move faster in Spain It's because their government Regulated a little differently in the UK. It's every 20 minutes So the point is all of a sudden a driver behind profitability the price you paint for electricity is showing great variability anything that used electricity in the manufacturer In the production started to show equivalent Variability today in the United States the price of natural gas and the open gas grid changes every 15 minutes shouldn't be a shock When you look at some metals you look at a metal ticker the price of metals such as copper may change once or twice every minute all of a sudden we're in an environment where the raw materials the energy and the production value of the products produced by Manufacturing and production Organizations are changing faster and faster and faster and it's going to get faster yet with outlets like Amazon and Google even the consumer markets are Experiencing interesting variability. I tried to buy a Raspberry Pi a couple months ago on Amazon And I went on it like nine in the morning, and it was $23 but somebody interrupted me so I didn't buy it. I went back at lunch It was $18.95, but somebody interrupted me and I didn't buy so I went back at four o'clock, and it was $22. That's within one day That's a consumer product within one day. So we're seeing an increase in the speed of business now We when you look at this the concept is I Was talking to a vice president from FCP and they said jeez we love the control industry and I said why They said because if you control something do if you can control it control it If you can't control it try to manage it and that's where we are and all of a sudden some business decisions are moving from the business Domain into the real-time domain. That means they're impacting us and we've got to be ready to deal with them We're not you know in the 1970s when the digital computer was introduced We all sat back and said gee wouldn't it be interesting if the OT domain Which is all of a sudden based on digital computers in the IT domain? Based on digital computers what would happen if we connected them together and then everybody said nah And then in the 80s we said let's try it now along comes sim. Do you guys remember sim? Computer integrated manufacturing. No, I'm not the only one old enough to remember sim. I was the vice president of sim At my company. I had no idea what it was after a while as a matter of fact after about two years I finally came up with the definition of sim and the definition was if you connect everything in my plant together something Good is bound to happen And it didn't but we started looking at it, but the driving force today is different We taught connectivity. It's not just connectivity. It's functionality Because when you look at today some functions that were traditional business functions are moving down into the real-time domain And we have to pick them up the the IT folks are struggling with them We understand real-time. We know what real-time is so be aware that the industry has some major Impact hitting it in terms of the speed of business the speed of business is moving to real-time and those people who understand Real-time and control can respond to this by the way, that's us Okay, so that's the first driver the second driver is open and interoperable systems I I had a set of slides. I was going to talk about on this But then I said look at who I'm talking to so I only put one slide up there Okay, open and interoperable systems are a reality They're going to happen. They're going to be there and they should be there The concept is not how we can push more into the platform the con concept is how we can push more functionality You've got platform and you've got functionality in order to drive higher by the way functionality drives value Not platform in order to drive higher levels of value We have to drive higher level of functionality, which means if we can go to open and interoperable systems We can focus on the real issue how to improve functionality the last 40 years We've been focusing on technology. We can flip it around. This is a major step forward The the third business driver is getting greater value from automation investments now to me This has been a driver of mine for years Because when I came into this industry, I said my lord look at this We have computers that can do work and can do it. Well, we have engineers that are really smart that understand control We can make industrial operations that are very complex very difficult to deal with We can help make those run better and better and better and yet over the last 40 years. What I've seen is an enormous commoditization of automation The fight is always on price or cost or life cycle cost The discussion is seldom on the value that these systems can deliver and I find that to be so Disappointing because I believe there's so much value left on the table that we can get huge amounts of value And when you look at why that is you just look at the way Capital investments are measured. This is a classic capital budget Financial profile the bar chart represents the life cycle cost of the investment So you have to pay for it. So the price is there you have to engineer it install it Start it up commission it so at the beginning of the life cycle the cost is high in theory once you've hit start up The cost levels off for a period of time Then as you get toward the end of the life cycle, whatever that is anymore the cost starts going up and up and up Probably spare parts more training things like that classic capital life cycle curve We also have a benefit in theory if you're going to buy capital if you're going to lay capital out there You got to get a benefit from it. We all have to fill out the return on investment forms when we do a capital expenditure I do I do capital expenditures. I buy demo systems for the company And so what happens is when I fill out the form I have a little area in there that says what's the return on investment For this demo system. I go whoa, how do you figure that out for a demo system? So it's easy. It's easy you call the finance guy and you say what's the threshold for Passing a capital investment this year. Oh 32 percent. Ah this demo system is going to give us 35 I couldn't believe it fantastic, right? So then you buy the demo system and fortunately for me nobody ever comes back and asks You know did it get you to 35 percent? But the problem ends up being the financial people are looking they're always looking and if you can't prove the return You never got a return if you can't prove you did it I don't know if any of you with CFOs, but CFOs were among the most J you know, I what it's the right word negative thinking people like I know when it comes to finances in That if you can't prove it you didn't do it Doesn't matter what the truth is truth doesn't matter the fact is you didn't do it So what's the problem with our industry? It's by the way that the difference between the integral of benefit and the integral of cost is what we call return on investment And there's another thing in our industry return on investment. We measure ourselves a return on investment What a shame that is Because what is return on investment when you completely recoup the investment when you get a hundred percent return you stop counting Right, so you're always a negative or a zero You're never a positive so we've we've maintained this image in industry that control systems are always a negative or zero But that's not the big problem. The big problem is the cost Life-cycle cost is somewhat measured If you look most we did a study with ISA where we looked at 87 different projects and 87 out of 87 of them We kind of can figure out the life-cycle cost Maybe not to the penny, but they knew and the benefit is not measured in Our industry especially for brownfield projects when you look at greenfield projects the benefit is kind of binary But in brownfield projects, you know the cost that we always assumed the cost accountants knew what the benefit was They just weren't telling us because that's the way cost accountants are But it's not true. They don't know the fact of the matter is cost accounting systems Do not have the resolution to calculate the benefit for automation. So what do we end up being? We end up being a cost without a benefit By the way, that's the definition of a nuisance. We are a nuisance Unless we can prove we provide a benefit. We're a nuisance And if you're a nuisance they want to pay as little as possible for that solution as Because they're not getting any benefit that they can see that's where we are. That's where our industry is That's what the commoditization is all about So why is that happening? That's happening because cost accounting systems basically measure over a monthly period energy in material in and production value out production out Anything that happens below the plant level is not visible if you go in and you just something really need in a distillation column and you improve the Value of that piece of equipment that unit that asset by a million dollars I'll guarantee you it's something else or everything else in that plant will screw up enough that you'll never see the million dollars Or even if you do there's no way of attributing it back to what you did at the distillation column So what ends up happening? We do some great stuff. It makes some great value and nobody ever sees it So we've got to fix this if we don't fix this we're sunk as an industry We've got to change this and I'm talking about both suppliers and Users of control systems. We all have to be in this together to create value So, how do you do it when I went we went to Harvard University and started looking at this product with? Dr. Robin Cooper who headed up the cost accounting department at the Harvard Business School And he said the problem Peter is we know we should be doing cost accounting in real time But there's no database. There's no data. We can't get a database in real time and I said well, yes You can we have a database we measure a lot of stuff We have senses all over the place and with by the way with iot and openness We're gonna have more and more of them Can we use the flows levels temperatures pressures compositions all those things to model I'm not talking first principle models I'm talking accounting models to model accounting at every cost and value point in the plant sure We're talking cost accounting guys look where engineers we work in in the natural sciences physics Chemistry biology cost accounting is an unnatural science by definition It was invented by humans and by the way, I remember before I came into industry I was a software developer working in a business environment and I remember I had a masters in mathematics at the time And they had to do a square root And they said oh good. There's a mathematician over here. He can figure out. We don't do square roots We can get this mathematician. He'll figure it out. I mean come on this stuff is easy when you look at accounting It's all equations. It's simple equations What we have to do is decompose the equations and right in your controllers. You can calculate real-time accounting models Right in your controllers So if you can do that we can start to show the value but more important we can start to empower Everybody in the operation with that information so when an operator makes a set point change You realize something a set point change is a business decision But it's a business decision when he makes a set point change He'll be able to see did it add value did it detract value and over time They'll be able to learn how to behave in a way that adds the most value to the business by the way It's not just operators maintenance. You want to do a maintenance procedure Let's take a look at when the most profitable time for the company is to go out there and do that maintenance procedure Engineering do we have the right control strategies to maximize profitability if you're not measuring it you can't control it We should know that we're a controls industry so we've got to start measuring So what happens is you measure down at the equipment level at the unit level at the plant level and sooner or later You can converge right up into the cost accounting system But now we're measuring cost accounting and it is cost accounting and so it's very distasteful to engineer So we've got to get over that but we're measuring cost accounting in real time once you start doing that and start seeing the value you can create You're going to realize that engineering is the most valuable Group within any industrial organization. They just aren't able to prove it It's time for us to step up and start proving some of this stuff because I'm telling you the values unbelievable We have experience that says that When we can go in together and solve a problem Without a request for proposal if we're given the degrees of Freedom to figure out what the problem is and then what the solution is our average 100% return on investment comes in it well under three months Three months Your CFO is going to jump out of their chair. They can't make an investment. That's better than that 100% return in three months with Ongoing benefit that means 400% return on the first year if you change their mindset to measure cash flow rather than return So we've got to work in their field and their domain and let them know what we're doing to drive value So greater business value from automation is critical The first element of that is measuring it if you measure it You'll be amazed at how much value you're creating and finally the final one is technology changes I joked about them up front IOT CPS AIO T It's no joke when you see all of these things coming together at the same time you may have a Gut feel that you don't want to pay attention to them You'll be in great trouble if you don't pay attention right now What's happening in industry right now is unlike anything I've ever seen over my 40 or 45 years It says greater than 37 years, but I'm not I keep I got to keep updating that so it's so it's goes that way Technology is no longer becoming a barrier to our success as a matter of fact the way we look at it We looked at technology the way it is and when you think about it The PLC was invented in 1966 Don Clark and I used to go out with our friend Dick Morley on a frequent basis and have lunch with them until he passed about a year and a half ago, I guess I my timings off sometimes and You know he'd talk about that it he'd say, you know something I invented that in 1966 They should be doing something different by now Why are they still doing the same ladder logic and stuff that we invented? 1966 he said I was young then I'm not anymore and DCS is 1970s and every time a new technology comes out. What do we do? We try to make the PLC a little better and the DCS a little better We start with the premise that that's that's what we're stuck with and we're just going to fix it We believe it's time to erase the whiteboard. We've reached a whiteboard moment Rather than starting with a picture of a DCS or a PLC or whatever it is erase the whiteboard We can get to the point where we say in a perfect world if we had no constraints What would it look like? What would it be and you might end up with a very different picture Than what you started with and that's exciting That's an exciting time. This is an exciting time So it's a whiteboard moment and we can take a look at what it really should look like in order to do that I worked again with dawn and a team back at Schneider and we made a decision that we wanted to separate the platform from the function and The reason was we were so hung up for the last 40 years in platform Every time we turned around it was you know expert systems computer integrated manufacturing a faster CPUs Microsoft changed again changed their Upgraded again what they did it last week to do it this year every time you turn around its platform platform platform Platform is a delivery vehicle for function Changing the platform and continually upgrading the platform is good. I'm not saying it's not good But you get the value out of the function So for the last 40 years, I believe that the industry as a whole has spent more time focused on platform and less time Focused on function all the changes that have taken place in technology give us the Opportunity to go back and start focusing on function again In other words, I believe we've got to the point where the platform is no longer a constraint on the solutions we design if you look at The history of the world we have an architecture natural architectures in industrial operations that are often defined by the asset base You've got equipment assets a group at the unit assets a group in the area assets a group into plan assets a group up into enterprise assets It's to find that way and then you look at the control and business systems. We put in architecturally, there's no relationship so we spend a lot of our time engineering solutions that are From one architecture into an architecture that looks nothing like it It takes a lot of engineering class to make that happen. Why did we do that? We didn't do that because we were stupid we did that because the constraints of technology caused us to design systems The way they were designed that we were limited by the constraint of technology. It was perfectly logical If the constraints go away, we can rethink the problem So when we start rethinking the problem and you look at the higher hierarchy of assets It's an interesting thing. So you got it as I said equipment assets They group together into unit assets group together into area assets so on so forth It's interesting when I first joined industry as I told you before I came in I wasn't an engineer my first engineering degree was my first PhD So I came into industry as a mathematician and of course everybody in industry said a mathematician. Oh good. He knows nothing Okay, and that was it by the way That was very good because I could walk into any plant anywhere in the world and say you're right I know nothing explained to me how this plant works and they'd use this they do it just this way We make this we take this raw material in this energy and we produce this product We do it in this unit We do this and by the way the unit is made up of these things and I'm sitting there going Oh every time I got to them I'd end up with this hierarchy and I'd say okay if that's the way it works Let's look at the control system Looks nothing like it We're not constrained by that anymore and by the way when you look at assets we also we ought to also consider the assets of energy material and Production their assets we ought to look at people and if we can take and we can design a control system We are the basic components of the control system or asset centric focused on bringing those assets under complete control and I'll explain what that means in a couple minutes and Then you can do it in an open and interoperable way So you can develop a controller for a compressor Completely control that compressor it links up into a gathering system control system Links up into the gas enterprise control system when you start doing that and each one of those components Each one of those nodes is a self-sufficient system You'd you get a situation where the plant models the automation system the automation system comes from the plant design not the other way around You don't have to waste a lot of engineering trying to cobble together an architecture that looks nothing like the problem you're trying to solve it's natural and Think about it this way We've created Autonomous self-driving automobiles when I say we it wasn't me, but so I got to clarify that Google and Tesla Have created autonomous self-driving automobiles. How? How did they do that? Real-time control They did it through real-time control the mechanism to make a dumb automobile like mine into an autonomous automobile is control We are a control industry That's what we do. We spent too much time being a system industry We got to get back and be a control industry again, and that doesn't mean systems aren't important It means the systems can support whatever model we want So let's go figure out what the model is not what the system is So when you look at it, you've got an extended control object or objects that run within that automobile Make it in an autonomous automobile. Why couldn't we do the same thing? I mean most of our process equipment process units don't drive on the street or at least they're not supposed to and so We don't have that dimension to worry about why can't we turn a compressor into an autonomous self-optimizing asset? Of course we can We have the knowledge to do it. It's control We know how to do that. Why why can't we turn a Pump into an autonomous self-optimizing pump? Of course we can why didn't we do it 40 years ago? Because 40 years ago or 50 years ago when I joined industry I worked on a Fox 230 was the name of the computer I started with with the Fox firm company. It was a digital equipment corporation PDP 11 20 It was 24k of main memory What a beast that was and it had a drum and we controlled whole chemical units with that today my watch Has a million times more intelligence than that computer had and I can go and buy a Raspberry Pi Online that has 10 million times more, but I'm even underestimating way more than that and it cost 18 bucks That's PDP 11 cost 2 million dollars. I couldn't afford back then we couldn't afford to make intelligent cars There were no computers in Volkswagen's back in 1970 If you had a Volkswagen Beetle and wanted to put a computer in just to see if the tires are pumped up and all that stuff The capability existed the computer could work it could do that But it weighed more than the Volkswagen Beetle and you'd have to have a very long extension cord We just didn't have the technology that but the function existed Now that functionality has come down in size price cost heat all the things we needed it to do We're not constrained by technology. I can take a computer That's 10 million times what the PDP 11 was and dedicated to a compressor What could I do what kind of control could I do if I could do that and then if I get all the base assets done I group them together into a unit the difference the delta between the control of each piece of equipment in the unit level control is much Smaller than if you take that approach then you can go to area to plant you can see where we're going with this So openness and interoperability between these asset controllers is critical to make this happen We have to have that to make this happen. That's why the OPAF Organization is so good. So when we look at extended control the control needed to do this We start with the objective functions I'm talking in optimization terminology for control because the ultimate objective of both control and optimization is the exact same thing It's just a different approach to solving the problem We start with the objectives the objectives for an asset an industrial plant or operational efficiency improvement and profitability improvement That's what we're trying to do. That's why we apply control We want operational efficiency improvement and profitability improvement if it has a profitability component to it But we have constraints and the fundamental constraints around any industrial asset will be Reliability risk the risk that it's going to fail Environmental risk and safety risk You need those constraints exist by the way, what are we trying to do today in those areas? We're trying to manage reliability. We're trying to manage environmental and safety risk. These are real-time control problems We always talk about asset performance management asset performance management is good But asset performance control is also critical We got to bring the control function down if we could if we could measure Reliability in real time around an asset if I could predict when that asset is going to fail I may be able to take a control action that causes that failure time window to extend So then I could decide when to do the appropriate maintenance on it Right for example with the compressor. We worked on a few years ago Big reciprocating compressors. We were able to model the compressor It would a it a it was able to tell us eight weeks in advance that it was moving toward a failure point if We immediately slowed the compressor down five percent That eight weeks went out to 16 weeks Then we could look at the contracts that that gas processor had Figure out when I could take that compressor down without having a penalty for missing a contract and we could do the Maintenance at the exact right time. It's a control and a management function not saying asset performance management It's not important. It is what we also have to think of control and by the way We also have a security risk component now The reason I put security risk separate from the other three is security risk is a prerequisite for the system to work It's not a constraint on profitability, but you need the security control by the way today We're looking at firewalls tomorrow. We look at security control at each node Each node will be self-securing and that's the way it should be we'll drive those hackers nuts It's about time we did by the way you put all this together. What do you get? Autonomous self-optimizing industrial assets. It's control. We're control people We know what to do the technologies enabling it now. It's time to move forward So what we when we talk about the Internet of things we like to use the word the Internet of assets in industrial plants It's assets what we're trying to do is get assets to run better if we get all the assets running better the plant and the Enterprise is working better. So in the Internet of assets, you start at the lower end with DCNs and you have these equipment level Autonomous self-optimizing controllers That's where we think that's going and then you group it up You get these unit level agents intelligent agents at the extended control agents and they can control the units It has autonomous self-optimizing way. By the way, I'm when I talk about control I'm going back to my roots of the 1970s when I took control classes in the 1970s The first thing I was taught was there's two types of control automatic and manual Everybody today is saying manual control. That's not control. Yes, it is Putting humans in the loop and giving them the information to make good decisions in the right time frame They're control decisions. So automatic and manual control when we talk about empowerment. We should be empowering to control Why would you empower to do anything else? That's all we're trying to accomplish. Everybody gives everybody all this data. That's not empowerment You empower with the right information Everybody needs to do their job better to control the plant from a profitability efficiency reliability safety and environmental perspective That's what we do plant control agents site control agents enterprise control agents Value chain control agents. You just go up the list and that's the few that's what we believe is going to be happening You take some of the support functions. They go off to the side They should be able to plug in at whatever level the organization requires them to plug in. I Mean they're going to be changing rapidly too and then you empower the humans through those agents And you've got yourself an autonomous self-optimizing business Now might take a little while to get there, but we believe this is the direction and this is why This is why we believe this organization is so important By the way, when you start looking at this my colors didn't work out too well So forgive me the number one vector is production value. We build plants to create production value We want to reduce the variable cost the two real-time components of variable cost or energy and material cost and they are constrained By safety risk environmental risk reliability risk and maybe equipment limits in some industries So we have an optimization problem, but it's a three objective optimization problem My my PhD was an industrial engineering. So optimization was what I focused on We only were able to solve one objective optimization problems We've made the other objectives into constraints and did theory of constraints analysis that takes too long This is a control problem. We've got to start solving this problem to get autonomous self-optimizing Assets at every asset in the plant. We also have to activate our workforce You know as the as a speed of business continues and continues and continues the executive can't possibly make the number of decisions They need to make at the time frame. They were making them 20 years ago. It's impossible So they have to pass decision rights right down to the front line Because there's a time frame gets shorter the front we need more and more people to be performance managers We've got to stop thinking about operators maintenance people as a labor force. They're not a labor force Their performance managers and we should start empowering them to be the performance managers They can be our experiences They can do an awesome job if you give them the right information at the right time to do their job better They can optimize their actions and activities So what we're talking about in the future of automation is an asset control model We're we're based on the incident of assets where the physical model drives the system definition We no longer have this mismatch between system architecture and plant architecture They come together and the assets control themselves autonomously assets and asset sets are Systematized we talk about system of systems in the industrial Internet of things This is how you make a system of systems every one of those nodes is a self-sustaining self-optimizing system control extends from Efficiency only 99% of the control we've applied for the last hundred years has been to drive operational efficiency We're going to expand it. We're going to expand it to reliability risk safety risk environmental risk Profitability and cybersecurity when you do that at each node at each asset you have self-optimizing plants and finally the You'll have the key at characteristics will be cyber physical systems DCNs from an opath point of view Single asset integrity we talked about single loop integrity back in the 70s We'll get to the point where it's single asset integrity so the integrity of the system and the integrity of the asset are matched up and You'll have intelligent control agents that drive autonomous self-optimizing control That is why I started this off by saying I'm very disappointed that I'm old Gotta tell you I came into this industry at the wrong time. I wish I was coming in right now and for those of us who are baby boomers who are soon going to be Vacationing well, I don't want to call it retirement. We're still going to be vacationing. We left a legacy That's a great legacy for the Millennials. We left a legacy. We developed technology that we're lousy at using But the young folks behind us are really good at using our technology So it's time that we passed the mantle we move forward and we drove for Significant operational profitability improvements safely. Thank you very much Presentation there so I also like please take a seat wherever you are. I'll follow your lead. Oh, yeah I don't usually talk about it publicly, but I was an attorney in a former life and So I love the fact that you're not beating up on lawyers, but you're beating up on accountants Yeah, we finished with the lawyers in the 80s. Yeah, that's okay. It's old news in it so can you my first question was can you can you see a way if if if Technology isn't our limiting factor, but imagination is can you find a way to? Create an autonomous self-optimizing industrial asset out of a cost accountant We're working on it. I'll tell you we're working on it. It'll be good I think by the way, you're right I I gave this talk once or something similar and I had a banker come up and said did you do this for my bank, right? And you know, it's every industry has the require says absolutely So we'll dive into dive into the questions Imagine it's 10 years in the future The era of open process automation. How does your firm Schneider Electric? How will it differentiate? Itself from your competitors and how do you think this will change your workforce and their skill sets? Okay, now that's a tough question because it's obviously a business model transformation That has to occur for all the automation supplies has to The way I look at it is almost the first three slides I showed is we have to return to being the control Company that we were in the 1970s I mean when I look at Fox for in the 1970s Honeywell in the 1970s all of the companies Bailey AB You know when you looked at all those companies They had great control talent and the focus was control and that's what we're there for we're there to drive value through control And we were great at it and then we kind of took our eye off the ball a little bit became systems companies Not completely. We still have control capability, but the focus became much more exciting around systems because they cost so much I mean you got to remember we could sell a controller back then for two thousand dollars and a computer for two million Everybody got excited about that. That was an exciting thing. So what we need to do is go back to the future We have to become control companies again our differentiation will be Producing those intelligent control agents for different equipment asset different industries each industry I mean it's almost when you go back to the 70s every one of the controls companies had a list of Fundamental unit operations and how you'd go about controlling them. Here's a line kill. There's a you know distillation call Now we've got to put those into agents That's what we're going to be and I think we'll be competing and it'll be on value I think the the the more value you can drive out of those agents The better off will be and hopefully we won't be commoditized the way we are today. We'll be able to drive on value Okay Let's see At the beginning of the presentation you mentioned some open standards Or referred to open standards and open and interoperable standards. I think it was which ones are you thinking of? In particular and how can they be integrated? Well, you know, it's it's very hard to Nower it down with all the standards that are out there. So that's one of the reasons We've become so heavily involved with the open group and with opa we believe that you know Every time you support another standard it costs a lot of money to support it So it's very critical. We're supporting everything we can support out there and it's very expensive to do that It's very critical that we narrow in and those standards that are going to matter that are going to make a difference And I think the the issue around standards to this point. It's just been connecting things together I think what we need to do is focus on the the nodal separation of function and I think what you're going to find is when you when you look at the asset control model then the Requirements from a communication throughput perspective actually go down the information content goes way up But the requirement between the nodes goes way down So we are working heavily with opa to make the right ones happen And that's a kind of standard of standards approach as well correct bringing. Yeah, so good. Okay Let's see. It's Considering the different dimensions that need to be integrated to automate a whole complex process Which ones are the bigger challenges to automate? Considering all the different platforms and tooling to be integrated. Yeah, you know it If you look at the different levels and which ones are the biggest challenges Process control systems really haven't gone down to the equipment level for control to this point in time We've it was just impractical to do that for most pieces of equipment So I think the challenge is is not really which ones It's how do you approach it and I believe if you approach it bottom up you get the equipment level done And you'd I mean you'd have to do that by working with the equipment suppliers I mean there's a big Not to crack out there because there's millions of equipment suppliers So you'd have to do it in a way that pulled them in once you got that nailed Go into the unit level will be Not as big a step as it is today. It's a huge step today It will not be as big a step And so I think the bottom up path is probably what's more important than which specific ones are More difficult to apply. Okay It's great to see the refraining from platform To functionality and internet of things to internet of assets How do you envisage the way decisions are getting distributed and where humans will get injected either by law or due to fear? Yeah, I mean, I think it's the It's going to be a transition. It's you know, I think we inject humans right now where we don't understand Control models. So for example, we're doing work with real-time profitability control We haven't Completely closed the loop what we found is PID controllers don't work on profitability because PIP at least the P&D terms both depend on the natural period of the loop and a lot of business decisions the period changes with time so Sticking humans in where you don't have the knowledge to close the loop at least at the beginning So you can build your knowledge base to try to model what the humans do Is what where I think they're most suitable? So as you move up that hierarchy really it's the higher levels that the humans are going to start injecting themselves in and I don't see that going away for a long time because Real you know, the reality is we can't it is chaos out there I mean it truly is chaos out there chaos theory is a real thing and You never going to well at least in my lifetime and that may not be saying much But at least in my lifetime you're never going to be able to get to the point where the human isn't part of the equation And I'm not sure you really want to Okay, just got time for for one more What are your thoughts on the impact and challenges of cloud and cloud-based technology on ensuring open standards and interoperability? Well, there's there's a couple of things I you know, I think the concepts behind cloud are very important being able to work in a cloud environment is very important Certainly, you've got security issues that have to be very carefully managed when you move into the cloud I think the biggest danger honestly is is The the getting carried away with the cloud danger, you know, everything's going to be sucked up into the cloud You know, you're going to get some big thunderstorms if that happens But the the reality is we should be honestly looking at where functionality should be To best serve the industrial needs not just put everything in the cloud And when we talk about big data analytics, I see a lot of discussion about people doing big data analytics in the cloud Why big data analytics can be done at every level of that? that hierarchy that we talked about and Really what it's going to be is is a functional mapping. I believe not a physical mapping now That doesn't mean that there's not going to be a lot of value coming out of the cloud I think there will be your prognostics all kinds of great stuff in the cloud But you know, you've got to deal with the security and you have to make sure that you don't get Cloud envy if you will that everything goes up into the cloud He just will stop it there, but thank you very much for giving us a great start. Thank you very much