WEBVTT - Automation – The Brain of Industrial Operations 0:00:02.279 --> 0:00:05.970 Hello and a welcome to the Process Automation podcast. A 0:00:05.970 --> 0:00:09.360 podcast from ABB that shines a light on their process 0:00:09.360 --> 0:00:12.960 automation business area and the work they're doing around the 0:00:12.960 --> 0:00:18.180 world. I'm Fran Scott, maker, presenter and all around engineering 0:00:18.180 --> 0:00:21.870 geek. And across this series we've been exploring the invisible 0:00:21.870 --> 0:00:26.489 force of automation. So that's the incredible processes happening under 0:00:26.489 --> 0:00:30.570 the surface that enable our day- to- day lives from 0:00:30.660 --> 0:00:33.180 the heating in our homes to the water in our 0:00:33.180 --> 0:00:38.820 taps, ABBs technologies are working behind the scenes, orchestrating industrial 0:00:38.820 --> 0:00:44.250 processes, machinery, and systems. Today we are looking at the 0:00:44.250 --> 0:00:50.580 future of process automation. For more than a century, automation 0:00:50.580 --> 0:00:55.260 systems have been absolutely central to empowering industries that provide 0:00:55.260 --> 0:00:59.850 these basic building blocks of our everyday lives. From energy, 0:00:59.850 --> 0:01:06.060 power, water, metals, minerals, chemicals, and transportation, and enabling them 0:01:06.060 --> 0:01:09.660 to scale to meet the needs of a growing population. 0:01:10.620 --> 0:01:14.220 For more than 40 years, ABB has been leading the 0:01:14.220 --> 0:01:18.390 way when it comes to something called distributed control systems 0:01:18.690 --> 0:01:23.310 AKA DCS. Now these are at the heart of the 0:01:23.310 --> 0:01:28.830 largest and most critical operations on our planet. Now, if 0:01:28.830 --> 0:01:32.910 you recall the first episode of this series, I spoke 0:01:32.910 --> 0:01:37.319 to Peter Turk, the president of ABB's process automation business 0:01:37.319 --> 0:01:41.280 area, and we discussed the key role that process automation 0:01:41.280 --> 0:01:44.819 is playing in making the world safer, more efficient, and 0:01:44.819 --> 0:01:49.320 increasingly sustainable. Now, Peter introduced us to many of the 0:01:49.320 --> 0:01:54.360 industries that are benefiting from ABB's work in process automation, 0:01:54.660 --> 0:01:57.390 and over this series we have put those under the 0:01:57.390 --> 0:02:02.970 microscope. Industries like shipping and water to mining and continuous 0:02:02.970 --> 0:02:07.950 emissions monitoring. Today we are going to dive deeper into 0:02:07.950 --> 0:02:12.720 the driving force behind process automation and find out exactly 0:02:12.720 --> 0:02:17.940 how distributed control systems are transforming the future of so 0:02:18.000 --> 0:02:22.169 many industries. To do this, we'll be speaking to Mike 0:02:22.169 --> 0:02:27.690 Williams from Modern Automation Consultant Services based in Boston about 0:02:27.750 --> 0:02:32.549 the workforce of tomorrow. But first we'll hear from Bernhard 0:02:32.580 --> 0:02:37.649 Eschermann, chief Technology Officer for ABB's process automation business area 0:02:37.950 --> 0:02:42.120 about the development and trends that ABB predict will impact 0:02:42.120 --> 0:02:46.889 automation in the future. I started by asking him where 0:02:46.889 --> 0:02:50.310 exactly it is that we see process automation. 0:02:50.880 --> 0:02:53.790 If you look at the industries that we serve, like 0:02:54.000 --> 0:03:00.180 energy, power, water, metals, chemicals, farmer, and so on, typically 0:03:00.180 --> 0:03:04.590 they operate around the clock either with a continuous production 0:03:04.590 --> 0:03:08.760 flow or running a sequence of production batches. So for 0:03:08.760 --> 0:03:12.780 example, if you open the water tap at home, you 0:03:12.780 --> 0:03:16.079 just expect water to flow all the time and without 0:03:16.080 --> 0:03:20.070 interruption. And while all of these commodities are central to 0:03:20.070 --> 0:03:24.810 our everyday lives, they're actually provided with a relatively small 0:03:24.810 --> 0:03:28.950 number of people running such facilities around the clock. And 0:03:28.950 --> 0:03:33.000 the automation systems thus provide a large and growing well 0:03:33.000 --> 0:03:36.480 population with a reliable and cost- effective supply of these 0:03:36.480 --> 0:03:43.680 basic needs. And they optimize productivity, ensure product quality, reduce 0:03:43.680 --> 0:03:49.320 risks to people and the environment and optimize resource and energy consumption. 0:03:50.040 --> 0:03:57.600 Got you, just a few things there that they do, but let's focus in on the distributed 0:03:57.600 --> 0:04:01.380 control system. So DCSs, so can you tell me a bit 0:04:01.380 --> 0:04:03.090 more about how they work? 0:04:03.930 --> 0:04:07.890 Obviously, it's a very abstract subject, so I always try to 0:04:07.890 --> 0:04:11.850 compare that with something that people know. And the thing 0:04:11.850 --> 0:04:15.510 that people usually know best is their own body, and 0:04:15.540 --> 0:04:18.900 the automation system is like the nervous system and the 0:04:18.900 --> 0:04:22.860 brain of the human body. So it collects sensory information 0:04:22.860 --> 0:04:27.330 from all parts of the body and triggers certain reactions. 0:04:27.540 --> 0:04:31.320 Industrial plants are obviously much bigger than human body and 0:04:31.320 --> 0:04:34.620 thus the nervous system in the brain are distributed over 0:04:34.620 --> 0:04:38.880 this large expands, which is why the automation system for 0:04:38.880 --> 0:04:43.470 such industries is known as distributed control system or in 0:04:43.470 --> 0:04:48.510 short DCS. And if you look at these distributed control 0:04:48.510 --> 0:04:52.140 systems, they can be found pretty much anywhere in industry 0:04:52.140 --> 0:04:57.690 where critical processes need to be monitored or controlled, and 0:04:57.930 --> 0:05:03.089 the sensors that they rely on our instruments measuring properties 0:05:03.089 --> 0:05:07.080 like temperature, pressure or flow, and the muscles, if you 0:05:07.080 --> 0:05:10.080 compare that with the human body that they use to 0:05:10.080 --> 0:05:15.810 control the plant or industrial equipment like motors, valves, pumps, 0:05:15.810 --> 0:05:19.110 stuff like that. And in a larger industrial plant, you've 0:05:19.110 --> 0:05:23.279 got tens of thousands of such sensors and actuators. Now 0:05:23.279 --> 0:05:27.929 in between you've got communication networks and industrial grade computers, 0:05:27.930 --> 0:05:31.680 and they actually decide on what needs to be done. 0:05:32.700 --> 0:05:35.790 As an example, to ensure the safety of a process, 0:05:35.790 --> 0:05:39.179 you might measure the pressure in the tank and the 0:05:39.180 --> 0:05:43.680 computer would reduce the flow into the tank and increase 0:05:43.680 --> 0:05:48.479 the flow out of the tank by communicating appropriate signals to 0:05:48.480 --> 0:05:52.800 the equipment connected with the pipes going in and out of the tank. 0:05:53.580 --> 0:05:57.210 And if the pressure becomes too high, obviously that might 0:05:57.300 --> 0:06:01.500 be dangerous, and thus this whole thing has to be 0:06:01.500 --> 0:06:06.180 done with an extremely high reliability of the computer and 0:06:06.180 --> 0:06:12.089 the communication system, which is why multiple redundant components might 0:06:12.089 --> 0:06:15.750 be used. They monitor each other or are able to 0:06:15.750 --> 0:06:21.570 jump in if needed and thus provide for uninterrupted safe 0:06:21.810 --> 0:06:26.070 operation. You also have all of these different levels in 0:06:26.070 --> 0:06:30.600 industrial control system from keeping the pressure in the reaction 0:06:30.600 --> 0:06:35.580 vessel safe through controlling the overall reaction in the vessel 0:06:35.880 --> 0:06:39.239 to control the overall production in a part of the 0:06:39.240 --> 0:06:45.000 plant to coordinate multiple plants. For example, you might need 0:06:45.000 --> 0:06:49.800 the steam output from one plant to feed production in 0:06:49.800 --> 0:06:54.450 another plant, and ultimately you have to decide what specific 0:06:54.450 --> 0:06:58.410 product variant you want to produce anyway, some level you 0:06:58.410 --> 0:07:04.380 move then from automation to human decision making. At this 0:07:04.380 --> 0:07:09.299 interface between automation and humans, it's critical to provide the 0:07:09.300 --> 0:07:14.430 needed information to human people, to the plant operators and 0:07:14.430 --> 0:07:19.440 other staff through computer work stations or so- called human 0:07:19.440 --> 0:07:23.490 machine interfaces, and which are typically located in a so- 0:07:23.490 --> 0:07:28.170 called controlled room. So it has to enable a person 0:07:28.470 --> 0:07:32.730 to deal with the huge complexity of a plant. And another function 0:07:32.730 --> 0:07:37.740 needed in the DCS is to allow for engineering changes as raw materials 0:07:37.740 --> 0:07:43.680 or production processes change over time or certain production equipment 0:07:43.800 --> 0:07:47.100 is replaced. And by the way, the control rooms do 0:07:47.100 --> 0:07:50.760 not necessarily have to be in the plant like on 0:07:50.760 --> 0:07:53.820 an offshore gas platform in rough seas. Instead, you might 0:07:53.820 --> 0:07:57.570 have the operators sit in a cozy office somewhere on that. 0:07:57.930 --> 0:08:03.090 In terms of as industries are obviously developing, how does a 0:08:03.090 --> 0:08:08.250 distributed control system support them? I suppose as they're going 0:08:08.250 --> 0:08:13.290 through this fourth industrial revolution and what I see as this 0:08:13.290 --> 0:08:17.550 up and coming fifth industrial revolution, what is the role 0:08:17.550 --> 0:08:20.010 of the DCS in supporting these changes? 0:08:20.640 --> 0:08:26.460 If you look at these process plants, they live quite a long time and you don't tear 0:08:26.460 --> 0:08:30.660 down and rebuild a chemical plant every five years. While 0:08:30.660 --> 0:08:34.500 on the other hand, you actually have a couple of 0:08:34.500 --> 0:08:38.520 Windows versions during the same timeframe. At the same time, 0:08:38.520 --> 0:08:44.339 market requirements influencing what exactly should be produced are changing 0:08:44.340 --> 0:08:48.179 more and more quickly. And so customers need to renew 0:08:48.179 --> 0:08:54.360 technology to stay competitive, but with this 24/ 7 production, 0:08:54.360 --> 0:08:59.340 they also want to keep producing continuously while technology might 0:08:59.340 --> 0:09:03.240 be updated, even if it's only for the newest cybersecurity 0:09:03.240 --> 0:09:09.179 patches. And ABB has always provided new capabilities to meet 0:09:09.179 --> 0:09:14.880 these changing needs of the time while preserving the investments 0:09:14.880 --> 0:09:18.599 that customers have already made in their plants. That's one 0:09:18.600 --> 0:09:21.059 of the reasons I guess that ABB has built and 0:09:21.059 --> 0:09:24.689 maintained the leadership position in DCS over the last 40 0:09:24.690 --> 0:09:27.540 years and has been a number one choice according to 0:09:27.900 --> 0:09:32.250 market analysis for more than 20 years. If you look 0:09:32.250 --> 0:09:34.920 in the future, one of the newer development central to 0:09:34.920 --> 0:09:39.030 the fourth industrial revolution is a much higher level of 0:09:39.030 --> 0:09:45.599 flexibility. For example, you want to produce personalized medication that 0:09:46.020 --> 0:09:49.679 is not the standard medication for everybody, but just for 0:09:49.679 --> 0:09:53.640 one person. We've also been working on the use of 0:09:53.940 --> 0:09:59.100 artificial intelligence and machine learning to augment human's capabilities for 0:09:59.100 --> 0:10:02.490 decision making that allow them to focus on the higher 0:10:02.490 --> 0:10:06.870 level decisions that I described. Another development that we've been 0:10:06.870 --> 0:10:11.640 supporting is the digitalization of industries. With the control system 0:10:11.640 --> 0:10:14.849 having all of these inputs from the sensors, there are 0:10:14.910 --> 0:10:19.199 huge amounts of data available on the operation of a 0:10:19.200 --> 0:10:22.920 plant. And an obvious move is to bring the data 0:10:22.920 --> 0:10:27.390 out of the control system to analyze it based on 0:10:27.390 --> 0:10:32.100 this to optimize the overall production or the energy efficiency 0:10:32.100 --> 0:10:36.390 or whatever of the production. And in order to combine 0:10:36.390 --> 0:10:41.340 the ability to adapt to these technologies quickly while having 0:10:41.340 --> 0:10:46.320 a very reliable production that should not be interrupted, our 0:10:46.320 --> 0:10:49.829 concept is to have a very stable and robust inner 0:10:49.830 --> 0:10:53.970 core of the system that can be extended however, by 0:10:53.970 --> 0:10:59.040 additional capabilities without creating risks on the basic operations and 0:10:59.040 --> 0:10:59.730 their safety. 0:11:00.090 --> 0:11:02.490 With all the changes that we're seeing in the industry 0:11:02.490 --> 0:11:06.120 and technology, we are already seeing I suppose a new 0:11:06.179 --> 0:11:12.420 generation of digital industrial workforce so people, so could you 0:11:12.420 --> 0:11:18.270 tell me how this digital workforce are influencing the developments 0:11:18.300 --> 0:11:23.160 of future distributed control systems? So what are they seeing 0:11:23.160 --> 0:11:26.130 that's happening now and how are they, I suppose, swaying 0:11:26.130 --> 0:11:27.001 the developments of the future? 0:11:27.001 --> 0:11:31.800 Yeah. If I look at my children, and that's probably true 0:11:31.800 --> 0:11:35.700 for a lot of this generation Y or the generation 0:11:35.760 --> 0:11:39.780 Z employees, they are digital natives that are used to 0:11:39.780 --> 0:11:45.179 interact with technology without ever reading a manual or going 0:11:45.179 --> 0:11:48.690 through a training. And on the other hand, they don't 0:11:48.690 --> 0:11:53.250 have the 20 to 30 year experience that the baby boomers have 0:11:53.250 --> 0:11:57.240 accumulated that have been operating these plants over the last 20, 0:11:57.450 --> 0:12:02.940 30 years. And thus, the automation system has to provide 0:12:03.510 --> 0:12:09.449 support and interaction patterns that this generation is used to 0:12:10.050 --> 0:12:14.100 as an example, rather than people scanning through long alarm 0:12:14.100 --> 0:12:20.460 lists, the system has to identify critical situations by finding 0:12:20.460 --> 0:12:26.160 anomalies autonomously, by looking at the data stream, dig out 0:12:26.220 --> 0:12:31.080 automatically what mitigated such a situation in the past, and 0:12:31.080 --> 0:12:34.230 maybe offer the operator to also simulate the result of 0:12:34.230 --> 0:12:39.030 an action before actually doing something. And this is exactly 0:12:39.030 --> 0:12:43.380 where AI and machine learning in today's technology can help. 0:12:44.580 --> 0:12:49.170 There is no doubt that we are seeing machine learning and AI 0:12:49.230 --> 0:12:52.980 integrated into our lives, and as we look to the 0:12:52.980 --> 0:12:56.520 future, we can see that how we work is also 0:12:56.520 --> 0:13:01.110 changing. I spoke to Mike Williams from Modern Automation Consultant 0:13:01.110 --> 0:13:06.089 Services to ask where process automation and distributed control systems 0:13:06.330 --> 0:13:07.410 come into this? 0:13:09.660 --> 0:13:13.950 It's very important when you look at autonomous operations, essentially 0:13:13.950 --> 0:13:17.819 taking yourself on a journey from manual to automated and 0:13:17.820 --> 0:13:22.679 ultimately fully autonomous solutions, you must look at that as 0:13:22.679 --> 0:13:26.460 an investment and future proofing means making sure that that 0:13:26.460 --> 0:13:31.080 investment is spent wisely. The definition of future proofing is 0:13:31.080 --> 0:13:35.400 the ability to expand and adapt to the business changes 0:13:35.490 --> 0:13:39.450 without wholesale rip and replacement of those legacy systems. This 0:13:39.450 --> 0:13:43.319 is very important from an economic standpoint. It permits the 0:13:43.320 --> 0:13:47.640 end user or customer to implement new or upgrade old 0:13:47.640 --> 0:13:54.000 functionality incrementally, no big bangs here, investment incrementally to achieve 0:13:54.720 --> 0:13:59.760 business requirements, which do change over time. Future proofing allows 0:13:59.760 --> 0:14:02.579 the business to lower the business risk and increase the 0:14:02.580 --> 0:14:08.189 return on investment without the fear of becoming obsolete or non- competitive. 0:14:08.309 --> 0:14:11.040 So what you're saying is the DCS in a way 0:14:11.280 --> 0:14:16.829 laser a digital foundation that can then be added to 0:14:16.830 --> 0:14:20.550 bit by bit as new technology comes on the scene? 0:14:20.940 --> 0:14:26.760 That's absolutely correct. And fundamentally, the attributes of a future- proof 0:14:26.760 --> 0:14:34.230 system address the issues of horizontal and vertical integration, specifically 0:14:34.230 --> 0:14:38.670 horizontally the ability to scale or add to shop floor 0:14:38.670 --> 0:14:45.180 devices over time, and also vertical integration or extensibility upward 0:14:45.270 --> 0:14:50.040 from sensor to the boardroom from a communications application interaction 0:14:50.040 --> 0:14:54.420 capability. This interaction may involve not only the shop floor, 0:14:54.420 --> 0:14:58.230 but it may involve design, engineering, supply chain, financial, and 0:14:58.230 --> 0:14:59.850 even research and development. 0:15:00.240 --> 0:15:04.920 So what you're saying is there's this holistic approach, all 0:15:04.920 --> 0:15:08.910 levels of technology and all levels of people as well 0:15:08.910 --> 0:15:11.790 I suppose because along with the changes in industry and 0:15:11.790 --> 0:15:16.830 technology, we are already seeing the workforce adapting into, I 0:15:16.830 --> 0:15:22.860 suppose, the next generation of digital industrial workforce. So how 0:15:22.860 --> 0:15:28.470 are the developments in the technology changing the industrial workforce 0:15:28.980 --> 0:15:31.590 so changing the people themselves, I suppose? 0:15:31.860 --> 0:15:35.190 You've probably heard of something called the Industrial Revolution 4.0 or 0:15:36.150 --> 0:15:40.890 Industry 4. 0. We've entered a new age of digital 0:15:40.890 --> 0:15:46.770 transformation where computers are fundamentally being substituted for actual human 0:15:46.770 --> 0:15:50.910 beings. This is because of the need or requirement for 0:15:50.910 --> 0:15:56.489 higher computational and communications capabilities. And the question that you're 0:15:56.490 --> 0:15:59.790 asking is how do we navigate from what is a human- 0:15:59.790 --> 0:16:05.609 centric environment forward into a computer centric or autonomous plant 0:16:05.640 --> 0:16:10.800 operations environment using the new technologies? Quite honestly, the result 0:16:10.800 --> 0:16:14.880 of digital transformation simply is that physical tasks are being 0:16:14.880 --> 0:16:21.390 replaced with logical execution executed by remote devices. So simply 0:16:21.390 --> 0:16:25.260 put the answer is traditional operators are now going to 0:16:25.260 --> 0:16:30.450 become knowledge workers, and these knowledge workers will be using 0:16:30.450 --> 0:16:36.060 computers augmenting their human cognitive abilities to solve very complex 0:16:36.060 --> 0:16:39.390 problems which they could not solve on their own. And 0:16:39.390 --> 0:16:45.210 these complex problems are situations like abnormal equipment operation or 0:16:45.210 --> 0:16:49.050 suboptimal situations where the equipment is not performing as built 0:16:49.050 --> 0:16:53.910 well as it could. With these new digital transformation tools 0:16:53.910 --> 0:16:57.690 and techniques. Human beings who are still in the decision 0:16:57.690 --> 0:17:02.190 making loop can make these decisions quicker with better accuracy 0:17:02.220 --> 0:17:07.859 and less variability. Essentially, you're translating less hands into more 0:17:07.859 --> 0:17:13.710 heads. So the need for human beings is accentuated and 0:17:13.710 --> 0:17:17.100 the span of control of the human operator is going 0:17:17.100 --> 0:17:22.200 to increase resulting in less human error and more importantly, 0:17:22.230 --> 0:17:27.780 less human beings in the hazardous environments which exists in 0:17:27.780 --> 0:17:31.740 the process industries, thus improving the quality of life while 0:17:31.740 --> 0:17:34.379 increasing in productivity, safety, and quality. 0:17:34.710 --> 0:17:38.790 And I suppose the next stage of automation is the 0:17:38.790 --> 0:17:44.310 introduction of machine learning and artificial intelligence. So how will these 0:17:44.310 --> 0:17:46.410 become part of these systems? 0:17:46.980 --> 0:17:51.180 That's a very good question and is not well understood 0:17:51.330 --> 0:17:56.310 in the marketplace today. I like to use a maturity 0:17:56.310 --> 0:18:00.780 matrix called the level of autonomy, which starts with fundamentally 0:18:01.080 --> 0:18:05.880 totally manual operations and evolves as DCS control systems have 0:18:05.880 --> 0:18:12.000 evolved through time over a five distinctive capabilities or levels 0:18:12.000 --> 0:18:16.050 of autonomy from zero to five. When you're talking about 0:18:16.050 --> 0:18:21.240 technologies like artificial intelligence and machine learning, what you're trying 0:18:21.240 --> 0:18:26.609 to accomplish is even more sophisticated tasks than simple loop 0:18:26.609 --> 0:18:32.910 control and understand the interdependence of equipment not only with 0:18:32.910 --> 0:18:37.530 the human being, but machine to machine, using advanced mathematics 0:18:37.530 --> 0:18:42.090 and statistics to predict the future, not just the current 0:18:42.180 --> 0:18:45.690 situation, but predict the future and be able to optimize 0:18:46.080 --> 0:18:53.640 the processes to achieve the maximum result. An example here 0:18:53.640 --> 0:19:00.030 might be quite useful. You've heard about autonomous vehicles, autonomous 0:19:00.030 --> 0:19:05.850 automobiles, multiple sensing devices are mounted on the car and 0:19:06.119 --> 0:19:09.600 continuous calculations are made to ensure that the vehicle operates 0:19:09.600 --> 0:19:14.070 safely in an optimum manner. The same example exists in 0:19:14.070 --> 0:19:18.000 the process industries, and the objective here is to use 0:19:18.030 --> 0:19:23.790 artificial intelligence and machine learning to perform similar duties as 0:19:24.000 --> 0:19:27.179 an example, to extend the meantime to failure of a 0:19:27.180 --> 0:19:32.580 piece of equipment, thus avoiding unplanned downtime, which disrupts the 0:19:32.580 --> 0:19:38.520 customer fulfillment process, minimize the maintenance costs, and even improve 0:19:38.520 --> 0:19:42.119 the quality of the product that's being manufactured. Now, I'd like 0:19:42.119 --> 0:19:45.330 to remind you at this particular point in time, one 0:19:45.330 --> 0:19:49.679 should always remember that a sound level three autonomous DCS 0:19:49.680 --> 0:19:55.020 foundation is required to enable the advanced capabilities of artificial 0:19:55.020 --> 0:19:59.040 intelligence and machine learning. I have a saying that I like to 0:19:59.550 --> 0:20:05.700 tell my clients. Actionable intelligence has zero value unless it 0:20:05.700 --> 0:20:08.640 is acted upon in the correct context, in a timely 0:20:08.640 --> 0:20:12.659 manner. This is the role, the action is the role of the 0:20:12.930 --> 0:20:19.020 DCS, and the intelligence is provided by artificial intelligence and 0:20:19.020 --> 0:20:20.880 machine learning capabilities. 0:20:21.119 --> 0:20:25.109 So if we looked at this I suppose zoomed out, 0:20:25.350 --> 0:20:29.220 what are the key benefits of all of this? 0:20:30.450 --> 0:20:35.670 The benefits of artificial intelligence and machine learning are in 0:20:35.670 --> 0:20:41.820 the process industry, specifically related to process safety, product quality, 0:20:42.270 --> 0:20:46.469 the ability to improve the productivity without eliminating the human 0:20:46.470 --> 0:20:51.330 being, elevating the human consciousness and being able to achieve, 0:20:51.720 --> 0:20:56.310 most importantly, our sustainability goals, which is our right to 0:20:56.310 --> 0:21:02.609 operate or permit to operate. So one of the emerging 0:21:02.609 --> 0:21:06.600 issues out there, benefits of higher levels of automation and 0:21:06.600 --> 0:21:11.910 artificial intelligence, is to achieve our sustainability goals to protect 0:21:11.910 --> 0:21:15.359 our planet. Let me give you an example. Process plants 0:21:15.359 --> 0:21:20.850 are huge consumers of energy and water resources required to 0:21:20.850 --> 0:21:26.340 sustain human life. Consuming these resources in a responsible manner 0:21:26.760 --> 0:21:31.920 is the objective of companies today. More than 80% of 0:21:31.920 --> 0:21:37.950 the C- suite executive officers see sustainability is a prime 0:21:37.950 --> 0:21:42.630 objective of them remaining in business and being profitable. To 0:21:42.630 --> 0:21:47.820 achieve this automation and an advanced autonomous solutions like AI 0:21:47.820 --> 0:21:51.660 and machine learning are required to meet these business objectives. 0:21:51.660 --> 0:21:55.379 Such an important part of it, is sustainability not just from a 0:21:55.380 --> 0:21:59.640 planet friendly point of view, but from a continuous production 0:21:59.640 --> 0:22:02.250 point of view as well with things like the pandemic 0:22:02.250 --> 0:22:07.260 that showed us that automating your processes meant that they 0:22:07.260 --> 0:22:10.050 could continue in a way that if they were manual, 0:22:10.050 --> 0:22:11.010 they just wouldn't be able to. 0:22:11.369 --> 0:22:17.459 Right, the process industries exist to improve the standard of 0:22:17.460 --> 0:22:21.869 living and those things that we enjoy as part of 0:22:21.869 --> 0:22:27.180 our livelihoods. And to achieve this in an economical way 0:22:27.900 --> 0:22:33.869 and meet the objectives of sustainability, we believe in the 0:22:33.869 --> 0:22:40.560 process industries that automation or the in industrial re revolution 0:22:41.369 --> 0:22:45.990 4.0 is absolutely essential. The digital transformation is absolutely essential 0:22:46.320 --> 0:22:48.210 to achieve mankind's goals. 0:22:48.210 --> 0:22:59.640 I absolutely couldn't agree more. And it's not just the digital 0:22:59.640 --> 0:23:04.470 workforce that process automation is transforming. This technology can also 0:23:04.470 --> 0:23:09.210 be used for so many industries. So it's back to 0:23:09.210 --> 0:23:13.229 Bernhard for a final word on how a ABB's technology 0:23:13.260 --> 0:23:18.359 is transforming industries from energy right through to the world 0:23:18.359 --> 0:23:19.110 of fashion. 0:23:20.160 --> 0:23:23.280 Obviously, two of the most important topics to make human 0:23:23.280 --> 0:23:30.359 life more sustainable are circularity to avoid waste creation and 0:23:30.420 --> 0:23:34.710 reducing carbon emissions by increasing energy efficiency and the use 0:23:34.710 --> 0:23:38.820 of renewable energies. Renew Cell is focused on the first 0:23:38.820 --> 0:23:43.230 of these aspects. It's a fast growing Swedish company specializing 0:23:43.230 --> 0:23:47.640 in textile to textile recycling. So they close the loop 0:23:48.119 --> 0:23:52.680 when garments are worn out or no longer wanted. Some 0:23:52.680 --> 0:23:56.040 are obviously sold secondhand or used as hand me downs, 0:23:56.040 --> 0:24:00.570 but the vast majority today ends up in landfills or 0:24:00.570 --> 0:24:05.310 are incinerated. And what Renew Cell is doing is that 0:24:05.670 --> 0:24:10.560 they are changing that with a new technology by dissolving 0:24:10.590 --> 0:24:14.580 the used cotton and other natural fibers into a new 0:24:14.609 --> 0:24:19.320 biodegradable raw material, which is called Renew Cell pulp. And 0:24:19.320 --> 0:24:23.730 that can be turned again into textile fiber and thus 0:24:23.730 --> 0:24:28.169 goes into this textile production cycle again. They are using a 0:24:28.170 --> 0:24:32.669 number of ABB technologies among those ECS that enables the 0:24:32.670 --> 0:24:38.190 production to be as resource efficient as possible with less 0:24:38.190 --> 0:24:40.350 material consumption and reduced waste. 0:24:40.770 --> 0:24:45.810 Gosh, that sounds fascinating. And that is the very definition of a 0:24:45.810 --> 0:24:48.180 circular economy right there, isn't it? 0:24:48.300 --> 0:24:53.640 Yeah. And obviously while you circulate garments in this case, 0:24:53.700 --> 0:24:58.230 obviously the process uses energy. And so this is exactly 0:24:58.230 --> 0:25:01.710 where you also have to look at the second aspect that this 0:25:01.710 --> 0:25:06.840 whole process becomes as energy efficient as possible and hopefully 0:25:06.900 --> 0:25:08.880 uses renewable energy to be driven. 0:25:09.600 --> 0:25:14.880 Yeah, and exactly switching the conversation now onto energy usage, 0:25:14.880 --> 0:25:19.859 because energy is the largest consumer of natural resources and 0:25:19.859 --> 0:25:24.389 when it comes to industrial plants, I suppose shifting to 0:25:24.390 --> 0:25:28.980 electricity and so having that potential of using renewables I 0:25:28.980 --> 0:25:32.280 suppose is part of the solution but could you tell 0:25:32.280 --> 0:25:37.770 me briefly what role the DCSs would play in enabling this 0:25:37.859 --> 0:25:39.570 clean energy transition? 0:25:39.960 --> 0:25:44.100 Yeah, again, I try to use an example from everyday 0:25:44.100 --> 0:25:48.780 life. Let's assume you sit at home and want to 0:25:48.840 --> 0:25:52.109 mainly use electricity from the solar panels that you have 0:25:52.109 --> 0:25:56.609 on your roof, and then you've got certain electricity loads 0:25:56.609 --> 0:26:00.210 like right now your computer that probably don't want to 0:26:00.210 --> 0:26:06.420 switch off. Then you've got other loads like the refrigerator, 0:26:07.080 --> 0:26:09.090 you can switch that off for a certain amount of 0:26:09.090 --> 0:26:13.800 time, but probably not too long. And you've got other 0:26:13.800 --> 0:26:18.330 things like your sauna that you might decide, okay, I 0:26:18.390 --> 0:26:20.729 don't want to operate at this point in time because 0:26:20.730 --> 0:26:24.959 there's no sun right now. And all of these decisions 0:26:25.109 --> 0:26:28.830 are now decisions that you take, but you've got hundreds 0:26:28.830 --> 0:26:32.580 of similar decisions to take in an industrial plant that 0:26:32.580 --> 0:26:37.379 uses both conventional and renewable energy resources. And at the 0:26:37.380 --> 0:26:40.980 same time, obviously, the plant needs to produce something to 0:26:41.160 --> 0:26:46.679 create a payback for operating plant. Another example that you 0:26:46.680 --> 0:26:50.910 can actually look at is this topic of carbon capture 0:26:50.910 --> 0:26:55.080 and storage, trying to get CO2 out of the air 0:26:55.410 --> 0:26:58.949 and moving the carbon out of that in a safe 0:26:58.950 --> 0:27:02.430 place where it can be stored forever. This is a 0:27:02.820 --> 0:27:08.700 technologically very complex process that needs lots of equipment that 0:27:08.700 --> 0:27:12.240 again, needs to be controlled in the best possible fashion 0:27:12.240 --> 0:27:16.859 and as energy efficient as possible. So again, it's a 0:27:16.859 --> 0:27:20.160 typical application for a distributed control system. 0:27:20.910 --> 0:27:25.560 So when it comes to the future, Bernhard, what excites 0:27:25.560 --> 0:27:28.200 you, I suppose, when it comes to DCSs and also 0:27:28.200 --> 0:27:30.179 process automation in general? 0:27:30.450 --> 0:27:33.510 Fran, if I think back 20 years ago, computer and 0:27:33.510 --> 0:27:37.140 communication technology created a lot of constraints that we had 0:27:37.140 --> 0:27:39.810 to deal with and that we had to build the 0:27:39.810 --> 0:27:44.010 system around. And now most of these bottlenecks are gone. 0:27:44.640 --> 0:27:47.910 So we've got all of these great new technologies at 0:27:47.910 --> 0:27:55.050 our disposal, powerful computers, powerful communication systems, AI, machine learning, 0:27:55.109 --> 0:28:00.840 augmented reality, all of these things that means that instead 0:28:00.840 --> 0:28:04.890 of focusing on the constraints of the technology, we can 0:28:04.890 --> 0:28:08.129 really focus on creating value from this technology now. 0:28:11.640 --> 0:28:13.649 What a pleasure it was to speak to both Mike 0:28:13.650 --> 0:28:16.979 and Bernhard about these distributed control systems and what an 0:28:17.010 --> 0:28:21.030 insight they gave me and hopefully you about how these 0:28:21.030 --> 0:28:25.619 systems are at the heart of process automation and these 0:28:26.010 --> 0:28:29.730 systems that we all take for granted and take advantage 0:28:29.730 --> 0:28:34.530 of, and also how these DCSs can future proof these 0:28:34.680 --> 0:28:40.410 processes, so they're there for this growing population. But unfortunately, 0:28:40.410 --> 0:28:43.770 that is it for this episode. Of course, a massive 0:28:43.770 --> 0:28:47.310 thank you to Mike Williams and Bernhard Eschermann for their 0:28:47.310 --> 0:28:52.020 brilliant insight and expertise. I'm Fran Scott, and the Process 0:28:52.020 --> 0:28:56.160 Automation podcast is a Fresh Air Production for ABB. Follow 0:28:56.160 --> 0:28:59.610 or subscribe now for free wherever you get your podcasts 0:28:59.610 --> 0:29:01.200 so you never miss an episode.