WEBVTT 1 00:00:00.160 --> 00:00:02.600 Nobody better than you who can tell us how do 2 00:00:02.680 --> 00:00:06.360 you bridge real world with the digital world and what 3 00:00:06.400 --> 00:00:10.199 you've been doing worldwide and how things are getting transformed. 4 00:00:10.199 --> 00:00:15.439 Back in India, the first telegraph line was drawn between 5 00:00:15.519 --> 00:00:21.000 Calcutta and London and that is a story in itself. 6 00:00:21.120 --> 00:00:24.160 The scale at which India is being growing. 7 00:00:23.920 --> 00:00:25.679 Is completely unprecedented. 8 00:00:25.800 --> 00:00:30.480 Thirty seven thousand kilometers of rail network have been electrified 9 00:00:30.519 --> 00:00:31.760 in the last seven years. 10 00:00:32.079 --> 00:00:33.520 Let we put that in context. 11 00:00:33.799 --> 00:00:37.520 That's equivalent to the entire rail network of Germany from 12 00:00:37.560 --> 00:00:40.840 five hundred and twenty thousand circuit kilometers to over a 13 00:00:40.920 --> 00:00:44.840 million circuit kilometers. There's nowhere else that anything like this 14 00:00:44.920 --> 00:00:47.920 is happening at an unprecedented pace. 15 00:00:48.079 --> 00:00:51.880 When we talk about AI automation in smart factories, how 16 00:00:51.920 --> 00:00:54.520 you are going to be implementing it in industries? What 17 00:00:54.679 --> 00:00:57.520 is the end impact that you are also looking at. 18 00:00:57.840 --> 00:01:00.560 When we went from the bicycle to the motor car, 19 00:01:00.960 --> 00:01:03.520 jobs changed. When we went from the motor car to 20 00:01:03.759 --> 00:01:07.959 the aeroplane, jobs change. When we went from the fax 21 00:01:08.000 --> 00:01:14.159 machine to the telex machine to the internet, productivity change. 22 00:01:14.400 --> 00:01:15.799 I think it's now. 23 00:01:16.480 --> 00:01:19.560 Exciting times and you will see a lot happening in 24 00:01:19.560 --> 00:01:20.760 Siemens in the year's. 25 00:01:20.640 --> 00:01:29.760 Ed Hello on and welcome. You're watching Business Today television. 26 00:01:29.959 --> 00:01:33.519 I'm Sakhalibatryan. This is the Business Today podcast. Today we 27 00:01:33.560 --> 00:01:36.519 bring to you a brand that has one hundred and 28 00:01:36.560 --> 00:01:39.799 sixty years history. It is often known as an Indian 29 00:01:39.840 --> 00:01:44.319 company with a German heritage. The legacy brand called Semens India. 30 00:01:44.480 --> 00:01:46.799 We're going to be talking about it. The company that 31 00:01:46.799 --> 00:01:50.959 has twenty five factories. It also is silently transforming our 32 00:01:51.120 --> 00:01:54.359 everyday life. When we look at it every day, when 33 00:01:54.400 --> 00:01:58.079 you take that travel from a mainrail network, twenty five 34 00:01:58.120 --> 00:02:01.920 percent of that is powered once technology. In fact, forty 35 00:02:01.959 --> 00:02:04.879 percent of our metro cities as well run on Semens 36 00:02:04.959 --> 00:02:08.280 technology as well. And right now we're looking at how 37 00:02:08.400 --> 00:02:14.280 Semens is rewriting the entire India's mobility story, infrastructure and 38 00:02:14.360 --> 00:02:18.479 industries as well in the era of automation and AI. 39 00:02:18.479 --> 00:02:21.439 We're going to be diving deep into what next is 40 00:02:21.479 --> 00:02:23.759 coming in and how Semens is going to be of 41 00:02:23.800 --> 00:02:27.360 course taking the part into India's future growth story. Let's 42 00:02:27.400 --> 00:02:32.280 welcome the person with us from Semens India, none other 43 00:02:32.319 --> 00:02:35.759 than mister Sneil Marthur, the MD and CEO of Semens 44 00:02:35.759 --> 00:02:37.159 in there. We welcome to you, sir, and thank you 45 00:02:37.199 --> 00:02:39.280 so much for coming in onto us studios. 46 00:02:39.479 --> 00:02:41.240 Thank you for having miss Actually. 47 00:02:40.879 --> 00:02:43.479 It's a wonderful pleasure to have you with us and 48 00:02:43.560 --> 00:02:46.240 to talk about this legacy brand. You know, when we 49 00:02:46.319 --> 00:02:49.639 talk about, nobody better than you who can tell us 50 00:02:49.759 --> 00:02:53.400 how do you bridge real world with the digital world 51 00:02:53.520 --> 00:02:56.759 and what you've been doing worldwide and how things are 52 00:02:56.759 --> 00:02:59.599 getting transformed back in India. Could you give us a 53 00:02:59.639 --> 00:03:02.400 sense of how are you doing what you are and 54 00:03:02.439 --> 00:03:05.919 how is it really impacting everyone on ground today? 55 00:03:06.120 --> 00:03:09.680 Absolutely, Thank you so, Stevens. As you rightly mentioned, we've 56 00:03:09.719 --> 00:03:12.360 been here for almost one hundred. 57 00:03:12.159 --> 00:03:14.199 And sixty years. 58 00:03:14.240 --> 00:03:19.800 In fact, the first telegraph line was drawn between Calcutta 59 00:03:20.080 --> 00:03:24.840 and London and that is a story in itself, so 60 00:03:25.360 --> 00:03:28.879 we've had a long history over here. Over the years, 61 00:03:28.960 --> 00:03:32.840 we've been very much integrated into the growth story of India, 62 00:03:33.560 --> 00:03:36.639 and in fact that has accelerated, as we all know, 63 00:03:36.759 --> 00:03:40.280 in the last ten or fifteen years, with a lot happening, 64 00:03:40.319 --> 00:03:45.039 particularly in the area of energy and infrastructure and now 65 00:03:45.080 --> 00:03:49.599 opening up into the private world. The scale at which 66 00:03:49.879 --> 00:03:55.159 India is being growing is completely unprecedented. Thirty seven thousand 67 00:03:55.240 --> 00:03:59.360 kilometers of rail network have been electrified in the last 68 00:03:59.439 --> 00:04:03.080 seven years. Let me put that in context. That's equivalent 69 00:04:03.120 --> 00:04:05.639 to the entire rail network of Germany. 70 00:04:05.919 --> 00:04:06.280 Wow. 71 00:04:06.400 --> 00:04:13.360 Right, we plan to double our energy capacities, right, five 72 00:04:13.439 --> 00:04:16.759 hundred gigawards in the country to over one thousand gigawards 73 00:04:17.040 --> 00:04:18.040 in the next seven. 74 00:04:17.879 --> 00:04:18.560 Or eight years. 75 00:04:18.639 --> 00:04:19.160 Wow. 76 00:04:19.279 --> 00:04:23.439 We plan to double our transmission capacities in the country 77 00:04:23.720 --> 00:04:26.759 from five hundred and twenty thousand circuit kilometers to over 78 00:04:26.800 --> 00:04:30.959 a million circuit kilometers. There's nowhere else said anything like 79 00:04:31.040 --> 00:04:36.199 this is happening at an unprecedented pace. Ninety airport's built 80 00:04:36.240 --> 00:04:39.120 in the last seven years, sixty more coming in the next. 81 00:04:38.920 --> 00:04:42.879 Five years, so it is huge. What's happening now. 82 00:04:43.240 --> 00:04:48.759 We are known as a country as being entrepreneurs and 83 00:04:50.040 --> 00:04:55.560 leapfrogging technologies all the time. We leapfrog the technology from 84 00:04:55.920 --> 00:04:59.920 landline to mobile, We leapfrog the technology from credit card to. 85 00:05:01.399 --> 00:05:01.839 UPI. 86 00:05:02.720 --> 00:05:05.319 And this is the opportunity for us to leap frog 87 00:05:05.920 --> 00:05:09.759 into the AI world. And this is what makes it 88 00:05:09.839 --> 00:05:17.040 so exciting. Physical infrastructure is inert without a digital nervous system, 89 00:05:17.639 --> 00:05:20.439 and that is what we help bring to the table. Right, 90 00:05:20.639 --> 00:05:28.000 we can enable India's high speed growth through digital infrastructure, 91 00:05:28.240 --> 00:05:34.040 bringing in digitalization, bringing in AI, so that the infrastructure 92 00:05:34.199 --> 00:05:38.519 becomes alive and is actually able to provide the greatest 93 00:05:38.560 --> 00:05:42.079 benefits to the users in the country. So I think 94 00:05:42.079 --> 00:05:47.680 that it's exciting times ahead of us, but energy and 95 00:05:47.839 --> 00:05:53.639 infrastructure and the AI is going to completely transform the 96 00:05:53.639 --> 00:05:55.519 way we live our. 97 00:05:55.399 --> 00:05:59.120 Lives here fantastic. I think everybody is talking about AI 98 00:05:59.240 --> 00:06:02.519 quite a bit, but there's a lot of fear around 99 00:06:02.600 --> 00:06:06.279 AI even now, you know, despite it being the biggest 100 00:06:06.319 --> 00:06:09.800 buzzword of the last couple of years. The big fear 101 00:06:09.920 --> 00:06:12.639 is that it's going to be disrupting technology in a 102 00:06:12.720 --> 00:06:16.199 way that you know, a lot of humans might lose 103 00:06:16.240 --> 00:06:21.160 their jobs. When we talk about AI automation in smart factories, 104 00:06:21.199 --> 00:06:23.680 how you are going to be implementing it in industries? 105 00:06:23.959 --> 00:06:27.040 What is the end impact that you are also looking at? 106 00:06:27.480 --> 00:06:31.360 So I think, you know, I am much more positive 107 00:06:31.399 --> 00:06:35.879 and much more optimistic on the question of jobs. I 108 00:06:35.920 --> 00:06:39.399 think jobs will change. They won't go away, but jobs 109 00:06:39.399 --> 00:06:42.639 will change. The nature of jobs will change. When we 110 00:06:42.720 --> 00:06:46.240 went from the bicycle to the motor car, jobs changed 111 00:06:46.279 --> 00:06:48.959 when we went from the motor car to the aeroplane, 112 00:06:49.040 --> 00:06:55.199 jobs change and productivity changed and growth rates changed. Right, 113 00:06:55.279 --> 00:06:59.439 so things became much faster, much more efficient. When we 114 00:06:59.519 --> 00:07:03.319 went from the fax machine to the telex machine to 115 00:07:03.519 --> 00:07:09.079 the internet, productivity change and we became much more efficient 116 00:07:09.639 --> 00:07:14.199 and we were able to do much more with less 117 00:07:14.439 --> 00:07:15.240 in a way. 118 00:07:15.399 --> 00:07:18.040 And I think that's what's going to happen with the AI. 119 00:07:18.800 --> 00:07:23.240 It will open up avenues for us that never existed yesterday. 120 00:07:23.959 --> 00:07:28.040 It will open up opportunities for us, but it will 121 00:07:28.040 --> 00:07:32.639 also challenge us to continuous learning, so we will need 122 00:07:32.680 --> 00:07:35.920 to upscale ourselves. And this is not something that is 123 00:07:35.959 --> 00:07:37.920 going to change overnight. 124 00:07:38.000 --> 00:07:38.959 I think this is going. 125 00:07:38.879 --> 00:07:43.079 To be an evolutionary process where AI will creep into 126 00:07:43.279 --> 00:07:46.240 every bit of our day to day lives. We will 127 00:07:46.279 --> 00:07:49.600 begin to realize, hey, this makes sense for me. This 128 00:07:49.879 --> 00:07:53.920 is able to bring more benefits for me, for my factory, 129 00:07:53.959 --> 00:07:57.639 for my workplace, and we will start adopting it much more. 130 00:07:58.959 --> 00:08:03.439 And that's what we are actually centralized doing within Siemens 131 00:08:03.480 --> 00:08:07.279 as well. You know, when you talk about jen AI, 132 00:08:08.319 --> 00:08:13.720 you're looking more at information language models where if they're 133 00:08:13.839 --> 00:08:17.680 ninety five percent accurate, it doesn't really matter, right, you 134 00:08:17.720 --> 00:08:23.040 may get some inconsistencies in your statements. But on the 135 00:08:23.040 --> 00:08:26.959 industrial side, you can't be ninety five percent. You've got 136 00:08:27.000 --> 00:08:30.199 to be one hundred percent right, because if you're not 137 00:08:30.240 --> 00:08:33.879 one hundred percent accurate, you could have a production line 138 00:08:33.919 --> 00:08:36.480 that stops, you could have an energy grid that trips, 139 00:08:37.039 --> 00:08:39.279 you could have a train that stops on the way. 140 00:08:39.960 --> 00:08:42.960 And this is the way AI is going to impact 141 00:08:43.000 --> 00:08:45.480 our lives. But on the other hand, this is the 142 00:08:45.519 --> 00:08:50.320 opportunity for AI to start bringing in greater benefits for us. 143 00:08:50.399 --> 00:08:53.039 Absolutely. You know, there's this picture that all of us 144 00:08:53.080 --> 00:08:55.639 imagine that you know, maybe just about a few years 145 00:08:55.639 --> 00:08:58.480 from now, we'll have factories that will be run by robots, 146 00:08:59.200 --> 00:09:02.240 you know, which will be functioning instead of humans. Do 147 00:09:02.279 --> 00:09:04.279 you think something of that sort is going to happen 148 00:09:04.519 --> 00:09:08.440 or is there another way how AI is going to 149 00:09:08.480 --> 00:09:10.879 be implementing what happens at factories. 150 00:09:11.159 --> 00:09:13.360 So I don't think we are yet at the stage, 151 00:09:13.399 --> 00:09:15.480 and I think we are a long way off from 152 00:09:15.639 --> 00:09:18.639 dark factories as they call them, where they run on 153 00:09:18.679 --> 00:09:23.120 their own. But again, over there things are happening in 154 00:09:23.240 --> 00:09:27.120 the AI and in the software world that are bringing 155 00:09:27.159 --> 00:09:32.720 in greater efficiencies. So, you know, you talk about hardware, 156 00:09:33.720 --> 00:09:39.799 energy electrification, bringing in hardware machines that run on electrification, 157 00:09:39.919 --> 00:09:43.519 and then you have automation that controls the processes and 158 00:09:44.639 --> 00:09:48.440 manufacturing processes from the shop flow, and then you have 159 00:09:48.519 --> 00:09:52.279 software that actually takes it to the next level, is 160 00:09:52.320 --> 00:09:59.240 able to create a nervous system that enables these hardware 161 00:09:59.360 --> 00:10:02.559 to work my much more efficiently. And then you've got 162 00:10:02.600 --> 00:10:05.159 AI which is way on top of that, which allows 163 00:10:05.200 --> 00:10:08.240 all of this to work on its own and to interact. 164 00:10:08.279 --> 00:10:10.919 So you can have a building which is getting energy 165 00:10:11.480 --> 00:10:15.399 in from the grid, where the energy is adjusted through 166 00:10:15.600 --> 00:10:19.080 the use of AI depending on the consumptions that you require. 167 00:10:19.120 --> 00:10:19.799 In the factory. 168 00:10:20.480 --> 00:10:24.519 Your automation on the factory floor designs the way your 169 00:10:24.600 --> 00:10:29.120 machines move, but at the same time it adjusts and 170 00:10:29.480 --> 00:10:33.919 ensures that AI supports you in making those machines much 171 00:10:33.960 --> 00:10:38.480 more efficient, in ensuring that your inventory controls are better done, 172 00:10:38.759 --> 00:10:44.080 in ensuring that you're much more flexible in preempting trends 173 00:10:44.080 --> 00:10:47.759 that are coming in. In integrating and this is the 174 00:10:47.799 --> 00:10:51.639 beauty of it. If you can integrate electrification, automation and 175 00:10:51.720 --> 00:10:57.200 digitalization onto one platform, that's when you can crack the code, 176 00:10:57.240 --> 00:10:59.600 so to speak. And that is what Semens is able 177 00:10:59.639 --> 00:11:02.399 to do probably the only company in the world that 178 00:11:02.799 --> 00:11:06.559 has an integrated platform as a one tech company that 179 00:11:06.679 --> 00:11:09.799 integrates the electrification, automation and digitalization. 180 00:11:10.200 --> 00:11:12.440 I'm sure a lot of your customers would be looking 181 00:11:12.480 --> 00:11:16.519 at that as a package deal and looking at that 182 00:11:16.799 --> 00:11:20.120 how end to end solutions can be brought into them 183 00:11:20.320 --> 00:11:23.320 just by one company. So when your customers come to you, 184 00:11:23.639 --> 00:11:25.039 what is it that they ask? 185 00:11:25.720 --> 00:11:28.200 So the conversation has changed. It's a very good question. 186 00:11:28.320 --> 00:11:31.039 Conversation has changed. Earlier you used to go to your 187 00:11:31.039 --> 00:11:34.399 customer and say, here's my product, by my product, correct, right, 188 00:11:34.879 --> 00:11:36.720 And now we can go to the customer and we 189 00:11:36.759 --> 00:11:39.720 can say, tell us, your customer, what is your biggest challenge? 190 00:11:39.840 --> 00:11:40.480 Yeah, and he. 191 00:11:40.480 --> 00:11:45.559 Turns around and he says, wastage is my challenge or 192 00:11:46.000 --> 00:11:46.960 energy is my challenge. 193 00:11:47.080 --> 00:11:48.279 Let me give you some examples. 194 00:11:48.360 --> 00:11:52.559 Forty percent of the cost of running a hotel fixed 195 00:11:52.639 --> 00:11:55.759 cost of running a hotel is energy cost. And if 196 00:11:55.759 --> 00:11:58.960 you can bring down that energy cost, that helps the 197 00:11:59.720 --> 00:12:05.200 whole tail operator. Sixty percent of running a cement plant 198 00:12:05.639 --> 00:12:08.879 is energy cost. Now the cost of one bag of 199 00:12:08.960 --> 00:12:14.360 cement is half the price of one bag of Ruddi newspapers. Right, 200 00:12:14.759 --> 00:12:18.000 So now imagine if you can save ten percent of 201 00:12:18.080 --> 00:12:21.240 his energy that goes straight to his bottom line, right, 202 00:12:21.639 --> 00:12:23.799 And this is where you can actually do that. 203 00:12:24.320 --> 00:12:24.639 Now. 204 00:12:24.799 --> 00:12:30.000 If you can short cycle the time from drug research 205 00:12:30.360 --> 00:12:36.159 to drug commercial manufacturing, right, that saves lives. If you 206 00:12:36.320 --> 00:12:41.559 can make travel more efficient, that enables people to move 207 00:12:41.600 --> 00:12:45.879 around the world. And this is the power that AI has. 208 00:12:46.000 --> 00:12:50.240 This is the power linking in hardware and software, combining 209 00:12:50.279 --> 00:12:53.000 the virtual and the real has really on. 210 00:12:53.039 --> 00:12:56.759 Day to day lives of people absolutely, and of industries. 211 00:12:57.159 --> 00:13:00.320 That's a very interesting point when we talk about how 212 00:13:00.399 --> 00:13:04.360 India is envisioning where we want to focus our energies. 213 00:13:05.240 --> 00:13:08.159 Over the last couple of years, we've seen infrastructure and 214 00:13:08.279 --> 00:13:13.840 manufacturing two growth engines that India's policies are focused on, 215 00:13:14.320 --> 00:13:17.159 and that's where a lot of money is flowing into 216 00:13:17.200 --> 00:13:20.120 as well. There is a lot of growth on the 217 00:13:20.159 --> 00:13:23.399 overall GDP coming in from these two pockets as well. 218 00:13:23.519 --> 00:13:26.840 Give us an understanding, how are you contributing in these 219 00:13:26.919 --> 00:13:30.919 two mega spaces that India's focused Absolutely, so. 220 00:13:30.919 --> 00:13:35.679 I spoke earlier about the major increase in energy and 221 00:13:35.879 --> 00:13:39.519 India's plan is to do that in a green manner 222 00:13:40.200 --> 00:13:43.320 and to bring in much more renewables into the mix 223 00:13:43.440 --> 00:13:45.840 of energy here in the country. We want to be 224 00:13:46.000 --> 00:13:49.679 fifty percent renewable energy in the country. Now, that means 225 00:13:49.679 --> 00:13:54.080 the grid becomes unstable, right, and the moment you have that, 226 00:13:54.840 --> 00:13:57.639 you need to stabilize the grid. Because you don't have 227 00:13:57.720 --> 00:13:59.799 sun the whole day long, you need to have it 228 00:13:59.840 --> 00:14:02.679 in at night, the different weather conditions, et cetera. 229 00:14:03.039 --> 00:14:05.840 And you need tools to stabilize the grids. 230 00:14:06.600 --> 00:14:09.960 You need the electricity to come into your homes and 231 00:14:10.000 --> 00:14:14.399 to your offices and into your workplaces, into your factories. 232 00:14:14.799 --> 00:14:20.679 Now very often, very simply put in the morning, everybody 233 00:14:20.720 --> 00:14:25.519 moves from their homes to their workplaces, and energy and 234 00:14:25.639 --> 00:14:29.559 the air conditioning system switch off at home, and you 235 00:14:29.679 --> 00:14:33.679 need complete different power for your workplaces and your factories. 236 00:14:34.279 --> 00:14:39.200 So rather than having double the energy consumption energy at home, 237 00:14:39.600 --> 00:14:43.200 generating an energy in your workplace, wouldn't it be ideal 238 00:14:43.240 --> 00:14:45.720 to move the energy from one part of the city 239 00:14:45.759 --> 00:14:48.720 to the others when there is a need over here 240 00:14:48.759 --> 00:14:51.679 and move it back in the evening, right, And this 241 00:14:51.759 --> 00:14:55.200 is where smart drids come into account. Grids that can 242 00:14:55.320 --> 00:15:01.559 sense weather conditions, can can sense usage patterns, that can 243 00:15:01.679 --> 00:15:05.639 predict the way consumption is actually going to have and 244 00:15:06.440 --> 00:15:10.399 that is the beauty of where trends in AI and 245 00:15:10.480 --> 00:15:14.919 software and engineering can be used in the energy You 246 00:15:14.960 --> 00:15:19.240 look at the manufacturing sphere, India's ambition is to go 247 00:15:19.320 --> 00:15:23.240 from fifteen percent of GDP manufacturing share to twenty five 248 00:15:23.279 --> 00:15:27.080 percent of GDP manufacturing. That's one and a half trillion 249 00:15:27.120 --> 00:15:30.080 dollars of CAPEX coming in in the next five to 250 00:15:30.159 --> 00:15:32.840 seven years. There's no other country in the world that 251 00:15:32.919 --> 00:15:36.720 I know of that has got plans as ambitious as that. 252 00:15:37.360 --> 00:15:40.480 But as you go up the food chain in manufacturing, 253 00:15:40.519 --> 00:15:45.960 you get more and more complex manufacturing coming in semiconductors. 254 00:15:45.120 --> 00:15:47.279 Batteries, fuel cells. 255 00:15:48.440 --> 00:15:52.159 This requires technology at a precision level, which is way 256 00:15:52.240 --> 00:15:59.159 above what normal manufacturing will be. Right now, the average 257 00:16:00.279 --> 00:16:04.039 productivity level in India is seventy five percent. We have 258 00:16:04.080 --> 00:16:07.679 a factory in Germany that has a productivity level of 259 00:16:07.759 --> 00:16:11.360 ninety nine point nine nine percent. Now, there's no way 260 00:16:11.840 --> 00:16:16.759 you can bridge twenty five percent productivity benefit just through 261 00:16:17.000 --> 00:16:22.000 skilling workers. Correct right, technology will be the only enabler, 262 00:16:22.519 --> 00:16:25.639 and this is where we are able to bring technology 263 00:16:26.039 --> 00:16:30.159 that starts from the design phase to the engineering phase 264 00:16:30.600 --> 00:16:35.200 to the manufacturing phase and link it all together. We've 265 00:16:35.240 --> 00:16:41.200 just launched a major application called the eigen Engineering and 266 00:16:41.279 --> 00:16:47.559 this is this is a tool that helps engineers design, 267 00:16:48.360 --> 00:16:53.240 manufacture and a design engineer and operate PLCs. These are 268 00:16:53.360 --> 00:16:58.039 programmable logic controllers that design the automation systems on the 269 00:16:58.039 --> 00:17:01.440 shop flop. Normally, this is a very complex process, takes 270 00:17:01.480 --> 00:17:04.519 a lot of time, et cetera. But you can now 271 00:17:04.920 --> 00:17:08.200 interlink all of that into one with a single tool 272 00:17:08.200 --> 00:17:11.079 with one hundred percent accuracy because you need one hundred 273 00:17:11.119 --> 00:17:15.400 percent productivity. And this is use design. This is done 274 00:17:15.599 --> 00:17:20.920 using physics based models, It is done using experience out 275 00:17:20.960 --> 00:17:25.440 of multiple layers. And the foundation models over there are 276 00:17:25.519 --> 00:17:27.920 completely different and require a lot of. 277 00:17:29.640 --> 00:17:31.279 Engineering work to create. 278 00:17:31.680 --> 00:17:33.960 But those are the kind of things that can be done, 279 00:17:34.440 --> 00:17:36.400 and those are the kind of things that will make 280 00:17:36.599 --> 00:17:40.599 India really competitive. Sure, because a twenty five percent cost 281 00:17:40.759 --> 00:17:44.839 gap is it may even be cheaper to manufacture in 282 00:17:44.880 --> 00:17:48.359 Europe than it is to manufacture in India. The only 283 00:17:48.400 --> 00:17:51.279 way we can be competitive is if we are able 284 00:17:51.279 --> 00:17:54.240 to bridge that gap of twenty five percent through technology. 285 00:17:54.240 --> 00:17:57.960 Absolutely, so, when we talk about industrial AI, I wanted 286 00:17:58.000 --> 00:18:01.079 you to help all our viewers understand where is it 287 00:18:01.720 --> 00:18:07.680 that you are helping reduce costs, improve productivity, and enhance efficiency. 288 00:18:07.759 --> 00:18:10.000 Is it an all three? Is it greater in some 289 00:18:10.160 --> 00:18:11.640 area or the other way? 290 00:18:11.759 --> 00:18:14.519 So they're all interlinked. All the issues that you mentioned 291 00:18:14.519 --> 00:18:15.240 are interlinked. 292 00:18:16.440 --> 00:18:19.599 And I'll bring in a fourth dimension which we should 293 00:18:19.599 --> 00:18:22.720 also discuss, and that is sustainability correctly right, which is 294 00:18:23.359 --> 00:18:28.880 use less resources and use less energy. 295 00:18:29.519 --> 00:18:33.000 So that adds the complexity to the cube. Right. 296 00:18:33.079 --> 00:18:36.240 You want to be flexible in a world which is 297 00:18:36.359 --> 00:18:39.119 very volatile where demands are not really known. 298 00:18:39.160 --> 00:18:40.240 You want to be flexible. 299 00:18:40.799 --> 00:18:45.400 You want to be productive, so your productivity levels have 300 00:18:45.519 --> 00:18:48.920 to be the highest, and you need to be in 301 00:18:49.799 --> 00:18:53.279 a way that your quality standards are world class while 302 00:18:53.359 --> 00:18:57.279 being sustained having a sustainable product. The only way to 303 00:18:57.359 --> 00:19:02.680 do that is through sustainability is through AI and industrial 304 00:19:02.720 --> 00:19:05.599 AI as we call it. And how does that really happen? 305 00:19:06.039 --> 00:19:08.599 As I said, you've got a building which is a factory. 306 00:19:09.839 --> 00:19:13.400 You want to use as optimal amount of energy that 307 00:19:13.839 --> 00:19:17.839 you actually need for the manufacturing operations, and AI can 308 00:19:17.880 --> 00:19:21.559 help you optimize the energy consumption there bringing in the 309 00:19:21.720 --> 00:19:24.680 energy onto the shop floor. Then you need to be 310 00:19:24.759 --> 00:19:30.440 able to design the product, design the machines, design and 311 00:19:30.559 --> 00:19:35.880 engineer the manufacturing process. And then you want it to 312 00:19:36.000 --> 00:19:41.119 loop back and do corrections on its own as the 313 00:19:41.240 --> 00:19:45.799 productive production process actually works. And that's what industrial AI 314 00:19:45.960 --> 00:19:48.880 can do. So now you can actually go into a 315 00:19:48.960 --> 00:19:53.160 digital world, what we call the virtual world. You can 316 00:19:53.279 --> 00:19:58.839 design a product, you can design and engineer the machines, 317 00:19:59.559 --> 00:20:05.079 You can design and engineer the entire manufacturing process, including 318 00:20:05.160 --> 00:20:09.440 what angle people need to bend over in order to manufacture, 319 00:20:09.480 --> 00:20:12.319 where their tools need to be put. And then you 320 00:20:12.440 --> 00:20:18.000 can have a walk through through through augmented reality to 321 00:20:18.119 --> 00:20:21.319 actually see how things are. You can decide you want 322 00:20:21.359 --> 00:20:23.920 the air conditioning at a different part of the building, 323 00:20:24.000 --> 00:20:29.039 et cetera, et cetera. And this entire process is not 324 00:20:29.319 --> 00:20:35.079 done just through CADCM models. This is physics based manufacturing, 325 00:20:35.400 --> 00:20:39.079 physics based models that you actually create. Once you have 326 00:20:39.200 --> 00:20:43.200 built it in the virtual world, you then start constructing 327 00:20:43.240 --> 00:20:47.000 it in the real world right, and that helps you 328 00:20:47.160 --> 00:20:50.680 because you have simulated it, because you have done all 329 00:20:50.759 --> 00:20:54.200 your testing on in the virtual world, you get it 330 00:20:54.279 --> 00:20:57.720 right first time in the real world. Now that brings 331 00:20:57.720 --> 00:21:01.759 you up to fifty times fifty percent faster to the 332 00:21:01.839 --> 00:21:05.720 market than you would normally do. And with the highest 333 00:21:05.799 --> 00:21:09.640 level efficiencies. You get it first time, rightolutely, and then 334 00:21:09.720 --> 00:21:14.400 you link the virtual models with your real manufacturing together, 335 00:21:15.039 --> 00:21:17.400 so that every time you want to make a tweak, 336 00:21:17.880 --> 00:21:20.759 you first test it and do it in the virtual world, 337 00:21:21.519 --> 00:21:23.400 and then you do it in the real world. 338 00:21:23.480 --> 00:21:24.519 And you know what the. 339 00:21:24.440 --> 00:21:27.480 Impact of everything that you do will be because you've 340 00:21:27.519 --> 00:21:30.519 tested it and simulated it in the virtual world, and 341 00:21:30.559 --> 00:21:33.160 then you can put it into the real world. And 342 00:21:33.200 --> 00:21:36.720 when you are able to link these two together, you 343 00:21:36.759 --> 00:21:41.240 are able to slowly raise the optimization levels of productivity 344 00:21:41.799 --> 00:21:44.839 because now you can test everything on the virtual world 345 00:21:45.279 --> 00:21:49.200 and then bring it to life in the real world. Now, 346 00:21:49.200 --> 00:21:51.839 sometime down the line, you realize, hey, I've got a 347 00:21:52.279 --> 00:21:55.680 productivity problem. I used to manufacture one hundred pieces. I'm 348 00:21:55.680 --> 00:22:00.519 down to ninety five. Why did that happen? Yeah, then 349 00:22:00.559 --> 00:22:02.839 you can go back into the virtual world and see 350 00:22:02.839 --> 00:22:07.079 where rewind the tape and say, on this date, at 351 00:22:07.119 --> 00:22:11.920 this time a software upgrade to a robot did not happen. 352 00:22:12.480 --> 00:22:15.799 As a result of that, the efficiency. 353 00:22:15.160 --> 00:22:17.880 Went down on that robot, but that had a knock 354 00:22:17.960 --> 00:22:22.160 on efficiency level all through the all through the manufacturing chain. 355 00:22:22.680 --> 00:22:25.680 And this is where you can then start getting more efficient. 356 00:22:26.519 --> 00:22:30.319 When you get the machines to start learning and have 357 00:22:30.400 --> 00:22:34.799 cognitive capabilities, they start improving themselves as well. 358 00:22:35.279 --> 00:22:38.000 And this is the future of manufacturing. 359 00:22:38.200 --> 00:22:41.480 Well, this is the marvel of engineering and automation. Absolutely 360 00:22:41.640 --> 00:22:44.880 very interesting ideas there. But you talked about something very 361 00:22:45.000 --> 00:22:47.920 important and that is sustainability, which is now I believe 362 00:22:47.960 --> 00:22:51.200 no more an option for a lot of industries, companies, 363 00:22:51.279 --> 00:22:55.680 businesses at large. They have to be sustainable. How are 364 00:22:55.759 --> 00:22:59.720 you helping your customers, you know, when they are of 365 00:22:59.759 --> 00:23:04.279 course looking at investing big in these new AI automation 366 00:23:04.519 --> 00:23:09.079 tools and adopting them at a scale at their businesses, 367 00:23:09.160 --> 00:23:12.240 how are you helping them ensure that they also do 368 00:23:12.279 --> 00:23:13.160 this sustainably. 369 00:23:13.559 --> 00:23:17.599 Well, we do this in three ways. We help our customers. 370 00:23:17.920 --> 00:23:22.920 First measure what their what their emission levels are, then 371 00:23:22.960 --> 00:23:25.920 we help them manage them, and then we help them 372 00:23:25.960 --> 00:23:26.720 monetize them. 373 00:23:26.799 --> 00:23:31.599 So measure, manage, and monetize. And what does that really. 374 00:23:31.319 --> 00:23:36.119 Mean when we can help our customers optimize their energy usage? 375 00:23:36.559 --> 00:23:40.480 I mean, the best, the best energy, green energy is 376 00:23:40.519 --> 00:23:44.359 the energy that you don't use, right, But if you 377 00:23:44.440 --> 00:23:47.519 do have to use energy, can we help you monetize? 378 00:23:47.720 --> 00:23:50.839 Can we help you optimize that energy. And this is 379 00:23:50.880 --> 00:23:56.039 where it becomes critical in a building, for example, there 380 00:23:56.079 --> 00:23:59.160 are energy, there's energy being used everywhere for a whole 381 00:23:59.200 --> 00:23:59.839 lot of stuff. 382 00:24:01.119 --> 00:24:04.880 Can we help you give you the visibility. 383 00:24:04.279 --> 00:24:08.799 Of where a pump or a valve or a light 384 00:24:08.920 --> 00:24:14.160 somewhere is running inefficiently. Right, So we have a command 385 00:24:14.160 --> 00:24:18.039 and control center here in Mumbai where we are controlling 386 00:24:18.119 --> 00:24:22.039 the energy consumption out of one room, not a very 387 00:24:22.119 --> 00:24:26.480 large room, but controlling the energy consumption, monitoring the energy 388 00:24:26.519 --> 00:24:31.599 consumption in close to one thousand, two hundred seamen's offices 389 00:24:32.119 --> 00:24:35.359 around the world, in one hundred and ninety countries. 390 00:24:35.519 --> 00:24:36.920 Now what does that mean. 391 00:24:37.119 --> 00:24:41.839 It means I can compare that there is energy consumption 392 00:24:42.160 --> 00:24:45.440 in country A, which has got a bit in our 393 00:24:45.519 --> 00:24:47.799 office over there, which has got one hundred people in it, 394 00:24:47.920 --> 00:24:51.079 consuming so much energy, and compare it with country B, 395 00:24:51.240 --> 00:24:54.720 which has also got one hundred people, but consuming much more. 396 00:24:54.960 --> 00:24:57.039 And then you go back and you say why is 397 00:24:57.079 --> 00:25:00.920 it consuming more? And you drill down and you say 398 00:25:01.039 --> 00:25:03.440 it's consuming more because there's a leakage in the air 399 00:25:03.480 --> 00:25:06.920 conditioning system there, or there are lights that have been 400 00:25:06.960 --> 00:25:10.240 on in conference rooms longer than they should have. And 401 00:25:10.319 --> 00:25:14.599