1 00:00:00,880 --> 00:00:03,040 Welcome back to the automation podcast. My name 2 00:00:03,040 --> 00:00:05,120 is Sean Tierney from Insights and Automation, and 3 00:00:05,120 --> 00:00:07,200 I wanna thank you for tuning back in 4 00:00:07,200 --> 00:00:09,519 this week. In this episode, I meet up 5 00:00:09,519 --> 00:00:10,980 with Dante Vaccaro 6 00:00:11,279 --> 00:00:13,539 from Schneider Electric to talk about digitization 7 00:00:14,314 --> 00:00:16,074 as well as to talk about trends in 8 00:00:16,074 --> 00:00:17,054 industrial automation. 9 00:00:17,434 --> 00:00:19,355 Dante, thank you for coming on the show. 10 00:00:19,355 --> 00:00:21,434 It's great to have you here, and let 11 00:00:21,434 --> 00:00:23,535 me let you introduce yourself to our audience, 12 00:00:23,675 --> 00:00:25,195 and then we'll get into the topic we 13 00:00:25,195 --> 00:00:27,195 wanna talk about. Yeah. No problem, Sean. Thanks 14 00:00:27,195 --> 00:00:29,035 for having me on, and thanks for attending 15 00:00:29,035 --> 00:00:30,699 our event here. It's It's, really nice to 16 00:00:30,699 --> 00:00:32,539 have you here to check out the latest 17 00:00:32,539 --> 00:00:34,559 and greatest. But my name is Dante Vaccaro. 18 00:00:34,619 --> 00:00:37,579 So, I work as a digital transformation specialist 19 00:00:37,579 --> 00:00:39,739 within Schneider Electric. So what I do is 20 00:00:39,739 --> 00:00:40,479 help companies, 21 00:00:41,739 --> 00:00:43,039 create digital roadmaps 22 00:00:44,375 --> 00:00:47,015 aligned to, like, business strategic business outcomes and 23 00:00:47,015 --> 00:00:49,034 then how to scale those across their 24 00:00:49,574 --> 00:00:50,074 organizations. 25 00:00:50,375 --> 00:00:52,394 Right? So we take into consideration 26 00:00:52,695 --> 00:00:54,074 people, process, technology 27 00:00:54,614 --> 00:00:56,934 to align your operating model with a data 28 00:00:56,934 --> 00:00:57,835 driven approach. 29 00:00:58,149 --> 00:01:00,550 Now my background, I've been with Schneider now 30 00:01:00,550 --> 00:01:03,429 for nine years. But prior to that, I've 31 00:01:03,429 --> 00:01:05,510 worked in automation my whole life. So I've 32 00:01:05,510 --> 00:01:08,469 done everything from working for OEMs to motion 33 00:01:08,469 --> 00:01:09,530 centric automation 34 00:01:09,829 --> 00:01:10,569 to PLCs, 35 00:01:11,704 --> 00:01:14,364 and then eventually gravitated more into the software 36 00:01:14,424 --> 00:01:16,604 space, which is kinda where I sit now. 37 00:01:17,064 --> 00:01:18,905 Yeah. And so our audience is made up 38 00:01:18,905 --> 00:01:20,924 of those controls engineers. They're programming 39 00:01:21,545 --> 00:01:25,079 PLCs that creating HMI systems, SCADA systems. You 40 00:01:25,079 --> 00:01:26,840 know, some of them are using Schneider. Some 41 00:01:26,840 --> 00:01:27,739 are using Aviva. 42 00:01:28,280 --> 00:01:29,099 And so 43 00:01:29,560 --> 00:01:31,319 for them, they've heard a lot of different 44 00:01:31,319 --> 00:01:32,140 things about 45 00:01:32,599 --> 00:01:33,659 digital transformations, 46 00:01:34,119 --> 00:01:34,619 digitization, 47 00:01:35,399 --> 00:01:35,899 digitalization, 48 00:01:36,200 --> 00:01:38,759 you know, all these buzzwords they hear, but 49 00:01:38,759 --> 00:01:40,619 you're actually working with 50 00:01:40,975 --> 00:01:42,834 customers to help them find solutions. 51 00:01:43,135 --> 00:01:45,635 Can you give us an example of, 52 00:01:46,015 --> 00:01:47,694 like, what that would look like? Like, what 53 00:01:47,694 --> 00:01:51,395 what challenges are you solving for your customers? 54 00:01:51,694 --> 00:01:53,234 Yeah. So great question. 55 00:01:54,019 --> 00:01:55,780 So digital transformation, like you said, is a 56 00:01:55,780 --> 00:01:58,599 big buzzword. Right? So people have different interpretations 57 00:01:58,979 --> 00:02:00,819 of what it is, what it means, and 58 00:02:00,819 --> 00:02:01,799 how it is. So, 59 00:02:02,659 --> 00:02:05,219 essentially, what digital transformation is, it's not a 60 00:02:05,219 --> 00:02:07,875 product. It's not a software integration. It's really 61 00:02:07,875 --> 00:02:09,974 a strategy where we go from 62 00:02:11,074 --> 00:02:13,314 living in the dark and being reactive to 63 00:02:13,314 --> 00:02:15,094 data driven in real time. 64 00:02:15,474 --> 00:02:18,455 So it's really about maintaining a digital continuity 65 00:02:18,835 --> 00:02:22,700 across both operations and IT. So operational technology 66 00:02:22,760 --> 00:02:23,500 to IT 67 00:02:23,879 --> 00:02:26,840 to gain actionable insights to what's going on 68 00:02:26,840 --> 00:02:27,659 within your 69 00:02:28,120 --> 00:02:29,659 supply chain or operations. 70 00:02:30,120 --> 00:02:31,719 So it's not just focused to the floor, 71 00:02:31,719 --> 00:02:34,215 but it's it's the collective strategy that we're 72 00:02:34,294 --> 00:02:36,074 we're going to apply to become 73 00:02:36,534 --> 00:02:38,074 more agile in our operations. 74 00:02:38,854 --> 00:02:41,354 Yeah. And that's, I mean, that's important. Back 75 00:02:41,495 --> 00:02:43,495 when this whole industry really get started late 76 00:02:43,495 --> 00:02:43,995 sixties 77 00:02:44,375 --> 00:02:46,715 with, you know, the Modicon o '84 78 00:02:46,935 --> 00:02:49,629 and all the other products out there And 79 00:02:49,629 --> 00:02:51,790 evolved over the years, you know, forty years 80 00:02:51,790 --> 00:02:54,189 ago, we had companies like, you know, Wonderware 81 00:02:54,189 --> 00:02:56,110 InTouch. We had OSI Pi and other great 82 00:02:56,110 --> 00:02:57,090 companies being, 83 00:02:57,550 --> 00:02:58,050 founded. 84 00:02:59,389 --> 00:03:00,770 You know, we didn't have networks. 85 00:03:01,115 --> 00:03:03,594 We didn't have, you know, Modbus or, you 86 00:03:03,594 --> 00:03:05,915 know, Data Highway. They were not networks as 87 00:03:05,915 --> 00:03:08,074 we know them today, as we as evolved 88 00:03:08,074 --> 00:03:09,455 in the front office. But 89 00:03:09,754 --> 00:03:12,335 today, on the plant floor, we almost, 90 00:03:13,275 --> 00:03:14,254 in all applications, 91 00:03:14,689 --> 00:03:17,090 find Ethernet. Right? Yeah. Whether it be modbus 92 00:03:17,090 --> 00:03:19,569 TCP, Ethernet IP, you know, or other types 93 00:03:19,569 --> 00:03:21,729 of Ethernet. But it's this common standard that 94 00:03:21,729 --> 00:03:23,030 people can now use 95 00:03:23,409 --> 00:03:25,169 to get their data. Right? And so my 96 00:03:25,169 --> 00:03:27,490 audience would be very familiar with, like, data 97 00:03:27,490 --> 00:03:29,889 collection through, like, an OSI pi Mhmm. Or, 98 00:03:30,604 --> 00:03:32,465 you know, maybe a SCADA system 99 00:03:32,844 --> 00:03:35,004 based on InTouch or something else like that, 100 00:03:35,004 --> 00:03:37,405 another product like that. So the infrastructure there 101 00:03:37,405 --> 00:03:40,125 is the connectivity is there, but turning that 102 00:03:40,125 --> 00:03:41,905 data into something that's useful 103 00:03:42,284 --> 00:03:44,685 more than just a trend on the screen. 104 00:03:44,685 --> 00:03:45,185 Right? 105 00:03:46,370 --> 00:03:48,370 I think that's kinda what you're doing. Right? 106 00:03:48,370 --> 00:03:49,990 Can you talk a little bit about 107 00:03:50,530 --> 00:03:52,530 what the what the give me an example. 108 00:03:52,530 --> 00:03:55,189 Like, Tom, let's talk about a transformation itself. 109 00:03:55,250 --> 00:03:57,729 Okay. How did you utilize their infrastructure? I'm 110 00:03:57,729 --> 00:03:59,650 assuming most of your customers already have that 111 00:03:59,650 --> 00:04:00,150 infrastructure. 112 00:04:00,615 --> 00:04:02,694 How do you utilize that infrastructure to to 113 00:04:02,694 --> 00:04:03,194 to 114 00:04:04,215 --> 00:04:06,294 face it, to solve a challenge a customer's 115 00:04:06,294 --> 00:04:08,215 having? Yeah. So the goal is obviously not 116 00:04:08,215 --> 00:04:10,135 to rip and and replace. Right? It's really 117 00:04:10,135 --> 00:04:11,655 just to assess kinda where you are, 118 00:04:12,294 --> 00:04:13,594 your baseline situation 119 00:04:14,000 --> 00:04:15,060 as far as technology, 120 00:04:15,360 --> 00:04:18,160 as far as, like, your operating model. But 121 00:04:18,160 --> 00:04:19,139 we have to align 122 00:04:19,519 --> 00:04:22,079 the the goal to a strategic outcome. So 123 00:04:22,079 --> 00:04:23,759 I can give you a couple different instances. 124 00:04:23,759 --> 00:04:25,519 So I have a lot of customers right 125 00:04:25,519 --> 00:04:26,259 now that 126 00:04:26,615 --> 00:04:27,675 are having issues 127 00:04:28,055 --> 00:04:28,555 with 128 00:04:29,175 --> 00:04:32,055 maintaining plans from a centralized engineering team. So 129 00:04:32,055 --> 00:04:34,694 it's harder to get controls engineers and different 130 00:04:34,694 --> 00:04:35,194 resources, 131 00:04:36,214 --> 00:04:37,654 that are out there, but they need to 132 00:04:37,654 --> 00:04:40,295 understand what's going on into their their plants 133 00:04:40,295 --> 00:04:41,915 at real time. This could be 134 00:04:42,259 --> 00:04:43,079 whether it's, 135 00:04:43,459 --> 00:04:46,100 centralized maintenance teams, it could be centralized energy 136 00:04:46,100 --> 00:04:47,620 teams. But the goal is we need to 137 00:04:47,620 --> 00:04:49,939 see what's going on in the plan. Now 138 00:04:49,939 --> 00:04:52,579 if I'm a large organization, depending on how 139 00:04:52,579 --> 00:04:54,100 many plants I have, I have to roll 140 00:04:54,100 --> 00:04:56,194 up all that data and I have to 141 00:04:56,274 --> 00:04:58,294 I can't control what I don't measure. Right? 142 00:04:58,595 --> 00:04:59,095 So 143 00:04:59,474 --> 00:05:01,235 the idea is to figure out, okay, what 144 00:05:01,235 --> 00:05:03,394 is that strategic initiative? Is it are you 145 00:05:03,394 --> 00:05:05,714 struggling with quality optimization? So I'll give you 146 00:05:05,714 --> 00:05:07,394 one now where we have customers that have 147 00:05:07,394 --> 00:05:09,930 very varying quality that they're trying to optimize 148 00:05:09,930 --> 00:05:12,189 to reduce the standard deviation of that product. 149 00:05:12,490 --> 00:05:14,410 K. So we have a business imperative. We 150 00:05:14,410 --> 00:05:14,910 must, 151 00:05:16,250 --> 00:05:17,389 must fix our quality 152 00:05:17,850 --> 00:05:18,430 to then 153 00:05:19,610 --> 00:05:22,350 reduce the standard deviation to sell, like, a 154 00:05:22,894 --> 00:05:24,894 higher moisture content product. Right. Because you sell 155 00:05:24,894 --> 00:05:26,334 by weight. I want to sell tons. I 156 00:05:26,334 --> 00:05:27,694 don't want to over dry or under dry 157 00:05:27,694 --> 00:05:28,194 because 158 00:05:28,735 --> 00:05:30,894 that goes against two or three different things 159 00:05:30,894 --> 00:05:32,175 that I'm doing. If I use too much 160 00:05:32,175 --> 00:05:34,834 energy to that, it hits my sustainability goal. 161 00:05:35,659 --> 00:05:38,379 If I overdrive the product, I'm selling more 162 00:05:38,379 --> 00:05:41,039 physical product to to get out and, 163 00:05:42,139 --> 00:05:44,459 accomplish that. So the the idea is you 164 00:05:44,459 --> 00:05:46,875 connect the strategy with whatever that business 165 00:05:47,435 --> 00:05:49,675 imperative is, and then we work backwards from 166 00:05:49,675 --> 00:05:51,435 there. Okay. In order to achieve this, right, 167 00:05:51,435 --> 00:05:51,935 what 168 00:05:52,875 --> 00:05:55,115 how do we develop use cases that align 169 00:05:55,115 --> 00:05:57,535 to that strategic goal? And then what technologies, 170 00:05:58,795 --> 00:06:00,555 infrastructure can we put in place to make 171 00:06:00,555 --> 00:06:02,310 that happen? And then the next part of 172 00:06:03,110 --> 00:06:05,189 that is once we have we're connected, we're 173 00:06:05,189 --> 00:06:07,129 collected, we're analyzing, we're acting, 174 00:06:07,589 --> 00:06:09,110 how are we actually going to respond to 175 00:06:09,110 --> 00:06:11,189 that? Who is responsible for that data? How 176 00:06:11,189 --> 00:06:13,269 does what we're seeing get tied back into 177 00:06:13,269 --> 00:06:14,089 those processes? 178 00:06:14,629 --> 00:06:17,269 So the digital strategy enables your operating model. 179 00:06:17,269 --> 00:06:19,574 So So if I'm running continuous improvement, I'll 180 00:06:19,574 --> 00:06:21,095 give you another example. I have a lot 181 00:06:21,095 --> 00:06:22,295 of people that come to me and they're 182 00:06:22,295 --> 00:06:24,535 like, our digital transformation is we need to 183 00:06:24,535 --> 00:06:26,314 monitor OE in real time. 184 00:06:26,615 --> 00:06:28,375 I'm like, okay, great. OE is a good 185 00:06:28,375 --> 00:06:30,535 starting point, but what's your plan for that? 186 00:06:30,535 --> 00:06:32,459 Like, what do you mean? Like, if we 187 00:06:32,600 --> 00:06:34,699 if we just monitor OEE, we're gonna 188 00:06:35,240 --> 00:06:37,480 increase 5% efficiencies. I was like, that's like 189 00:06:37,480 --> 00:06:38,919 buying a scale and trying to lose weight. 190 00:06:38,919 --> 00:06:40,600 Right? If I step on that scale every 191 00:06:40,600 --> 00:06:42,860 five minutes, am I gonna lose weight? 192 00:06:43,160 --> 00:06:44,834 It's like and they just look at each 193 00:06:44,834 --> 00:06:46,834 other. It's about that moment. It's like you 194 00:06:46,834 --> 00:06:48,935 have to focus on the drivers, right? The 195 00:06:49,074 --> 00:06:51,574 drivers are diet and exercise and manufacturing. 196 00:06:52,194 --> 00:06:53,634 It could be a people problem. It could 197 00:06:53,634 --> 00:06:55,314 be a training problem. It could be a 198 00:06:55,314 --> 00:06:57,949 reliability problem. But the idea is that you 199 00:06:57,949 --> 00:07:00,189 build the strategy over time. So I start 200 00:07:00,189 --> 00:07:02,290 with my baselining. Right? What am I doing? 201 00:07:02,590 --> 00:07:03,410 What's causing 202 00:07:03,710 --> 00:07:04,770 getting my Pareto 203 00:07:05,310 --> 00:07:06,610 analysis of downtime? 204 00:07:06,990 --> 00:07:09,389 And then I work cross functionally with teams 205 00:07:09,389 --> 00:07:11,235 to determine how I'm going to do this. 206 00:07:11,474 --> 00:07:13,414 And this is where that closed loop, 207 00:07:13,954 --> 00:07:16,995 continuous improvement methodology comes in. Right? So I 208 00:07:16,995 --> 00:07:18,914 look at my Pareto and let's say I 209 00:07:18,914 --> 00:07:21,235 have infeed jams on a packaging line or 210 00:07:21,235 --> 00:07:23,175 something like that. And I see that repetitively 211 00:07:23,394 --> 00:07:24,375 and it's causing 212 00:07:25,110 --> 00:07:27,770 50% of my downtime or something like that 213 00:07:28,310 --> 00:07:30,790 that I have. I'm gonna then my my 214 00:07:30,790 --> 00:07:32,870 continuous improvement people are gonna work with my 215 00:07:32,870 --> 00:07:35,270 controls engineers to figure out or mechanical engineers 216 00:07:35,270 --> 00:07:37,395 depending on if it is it a control 217 00:07:37,395 --> 00:07:39,235 function issue or is it a mechanical issue 218 00:07:39,235 --> 00:07:41,235 and come together with the solution to close 219 00:07:41,235 --> 00:07:42,615 that. So that's 220 00:07:43,074 --> 00:07:43,895 kind of like 221 00:07:44,595 --> 00:07:46,835 a long winded response to yours, but I'm 222 00:07:46,835 --> 00:07:48,675 just going over, like, some of the ways 223 00:07:48,675 --> 00:07:50,819 that we approach it. Oh, that's excellent. I 224 00:07:50,819 --> 00:07:52,819 think, you know, if we go back twenty 225 00:07:52,819 --> 00:07:54,600 five years, maybe twenty years, 226 00:07:54,979 --> 00:07:56,180 well, you know, people would come to us 227 00:07:56,180 --> 00:07:57,860 and say, I need to collect data. I 228 00:07:57,860 --> 00:07:59,540 need to have all this data. And then 229 00:07:59,540 --> 00:08:01,060 you would go on a few years later, 230 00:08:01,060 --> 00:08:02,660 and they had all this data. Maybe it 231 00:08:02,660 --> 00:08:05,264 was in OSIpi or InTouch had data logged 232 00:08:05,264 --> 00:08:07,185 it, but they weren't using it. And it 233 00:08:07,185 --> 00:08:08,705 was actually causing them a lot of problems 234 00:08:08,705 --> 00:08:10,625 because they were running out of, you know, 235 00:08:10,625 --> 00:08:12,884 storage space Oh, yeah. Especially back then. 236 00:08:13,264 --> 00:08:15,024 And so the the point was, hey. You 237 00:08:15,024 --> 00:08:16,625 need some analytics. You need that you need 238 00:08:16,625 --> 00:08:18,305 a reporting package to go on top of 239 00:08:18,305 --> 00:08:20,149 that. You need to start using just don't 240 00:08:20,149 --> 00:08:21,670 collect data and never use it. You need 241 00:08:21,670 --> 00:08:22,330 to actually, 242 00:08:22,949 --> 00:08:24,870 you know, use that data. When you're talking 243 00:08:24,870 --> 00:08:27,910 about OEE, having the ability having the Pareto 244 00:08:27,910 --> 00:08:29,830 chart saying, hey. This is your number one 245 00:08:29,990 --> 00:08:31,430 this this is your number one, two, three, 246 00:08:31,430 --> 00:08:34,455 four, and five causes for downtime. Just having 247 00:08:34,455 --> 00:08:36,134 that is not enough. You have to take 248 00:08:36,134 --> 00:08:38,134 action from that. So I definitely hear where 249 00:08:38,134 --> 00:08:40,455 you're coming from that. And, you know, one 250 00:08:40,455 --> 00:08:41,115 of the things 251 00:08:41,495 --> 00:08:43,414 you know, it's so easy, especially, I'm from 252 00:08:43,414 --> 00:08:45,335 the Northeast. Right? So I think you're from 253 00:08:45,335 --> 00:08:47,595 PA? Pittsburgh. Pittsburgh. Right? Born and raised. 254 00:08:48,110 --> 00:08:50,029 So a lot of what, a lot in 255 00:08:50,029 --> 00:08:51,870 the Northeast, we get a I think it's 256 00:08:51,870 --> 00:08:53,389 rightly so. A lot of us can be 257 00:08:53,389 --> 00:08:55,310 cynical at times. Right? And so one of 258 00:08:55,310 --> 00:08:56,910 the questions I like to ask, so in 259 00:08:56,910 --> 00:08:58,750 the work you're doing, you're touching a lot 260 00:08:58,750 --> 00:08:59,730 of different customers, 261 00:09:00,125 --> 00:09:01,884 plus you're touching a lot of different product 262 00:09:01,884 --> 00:09:04,445 groups within Schneider. Right? Mhmm. And so I 263 00:09:04,445 --> 00:09:06,304 wanna ask you, like, 264 00:09:07,325 --> 00:09:09,565 what are some of the positive trends you're 265 00:09:09,565 --> 00:09:12,065 seeing? Like, we all know, you know, 266 00:09:12,620 --> 00:09:14,220 maybe my my I have to use a 267 00:09:14,220 --> 00:09:15,820 different notch on my belt or I have 268 00:09:15,820 --> 00:09:17,419 to loosen my collar or I can't fit 269 00:09:17,419 --> 00:09:19,179 my tie on, but those are those are 270 00:09:19,179 --> 00:09:21,019 trends I think we all deal with. But 271 00:09:21,019 --> 00:09:21,759 what about, 272 00:09:22,539 --> 00:09:24,940 positive trends? What positive trends are you seeing 273 00:09:24,940 --> 00:09:26,699 out there with your customers and within your 274 00:09:26,699 --> 00:09:27,199 company? 275 00:09:27,865 --> 00:09:28,524 I think, 276 00:09:29,225 --> 00:09:31,144 it really comes down to how we're gonna 277 00:09:31,144 --> 00:09:33,625 leverage data. And now what we're seeing is, 278 00:09:33,625 --> 00:09:36,184 like, everybody wants an AI strategy right now. 279 00:09:36,184 --> 00:09:37,865 So when we say trends, like, I I 280 00:09:37,865 --> 00:09:40,600 hate to get buzzwordy, but it's there's practical 281 00:09:40,600 --> 00:09:43,019 uses of AI. I think AI became mainstream 282 00:09:43,159 --> 00:09:45,319 with generative AI, which is just one form 283 00:09:45,319 --> 00:09:48,039 of that. There's been tried, tested, improved versions 284 00:09:48,039 --> 00:09:49,579 of that within manufacturing, 285 00:09:50,120 --> 00:09:50,978 such as like multivariable predictive control or when 286 00:09:50,978 --> 00:09:51,794 we get into like regular machine learning algorithms, 287 00:09:54,115 --> 00:09:56,534 regular machine learning algorithms. But I think 288 00:09:56,914 --> 00:09:59,654 what I see Schneider doing is really separating 289 00:09:59,794 --> 00:10:01,894 the portfolio up to producers, 290 00:10:02,834 --> 00:10:03,334 aggregators, 291 00:10:03,714 --> 00:10:05,254 and consumers of data. 292 00:10:05,669 --> 00:10:07,269 So a lot of the innovation that you 293 00:10:07,269 --> 00:10:09,129 see down in the product side is 294 00:10:09,509 --> 00:10:11,610 tons of register values of data. 295 00:10:12,149 --> 00:10:13,909 Like, how many times have you seen people 296 00:10:14,070 --> 00:10:16,629 like our variable frequency drive, there's probably, I 297 00:10:16,629 --> 00:10:18,950 don't know, a thousand different tags you can 298 00:10:18,950 --> 00:10:21,365 pull out of that. And most people hook 299 00:10:21,365 --> 00:10:22,485 it up with a four to 20 in 300 00:10:22,485 --> 00:10:24,644 and out. Right? But there's, like, water loss 301 00:10:24,644 --> 00:10:26,804 detection algorithms in there that tell you when 302 00:10:26,804 --> 00:10:28,004 you're losing stuff. There's, 303 00:10:29,284 --> 00:10:32,084 other, like, alarms, kilowatt hour consumptions if you 304 00:10:32,084 --> 00:10:34,884 wanna trend any of that data. Like, there's 305 00:10:34,884 --> 00:10:36,839 a ton of metadata that contains in the 306 00:10:36,839 --> 00:10:39,559 products that manufacturers are making today. There's just 307 00:10:39,559 --> 00:10:42,759 nothing leveraged well to understand that. So I 308 00:10:42,759 --> 00:10:45,579 would say AI is the trend. Data enables 309 00:10:45,799 --> 00:10:47,579 AI history, organization, 310 00:10:47,959 --> 00:10:48,459 contextualization. 311 00:10:49,399 --> 00:10:51,455 And from a control engineering perspective, 312 00:10:52,075 --> 00:10:55,054 maintaining, like, a discipline on data ontology is 313 00:10:55,115 --> 00:10:56,894 super critical in this part. 314 00:10:57,514 --> 00:10:58,875 Yeah. Could you go into that a little 315 00:10:58,875 --> 00:11:01,295 bit more? Yeah. So On ontology. 316 00:11:01,754 --> 00:11:03,674 Ontology. So think about it as, like, our 317 00:11:03,674 --> 00:11:05,490 data and tagging naming structures. 318 00:11:08,610 --> 00:11:10,149 Structure or standard to follow. 319 00:11:10,850 --> 00:11:14,289 And where we see some issues and whether 320 00:11:14,289 --> 00:11:15,970 it's AI or whether it's just trying to 321 00:11:15,970 --> 00:11:17,990 get someone like these operational KPIs 322 00:11:18,610 --> 00:11:19,589 is that oftentimes 323 00:11:20,434 --> 00:11:22,355 the detractor from that is, you know, the 324 00:11:22,355 --> 00:11:24,674 sins of our fathers on the control side 325 00:11:24,674 --> 00:11:25,174 where 326 00:11:25,634 --> 00:11:27,315 it's been hurry up and get the system 327 00:11:27,315 --> 00:11:29,154 up and running. You have two days, just 328 00:11:29,154 --> 00:11:30,774 get it. So we don't have 329 00:11:31,154 --> 00:11:33,975 discipline and structures and hierarchies and PLCs 330 00:11:34,595 --> 00:11:36,779 are usually flat. Right? So how do we 331 00:11:36,779 --> 00:11:39,100 normalize that and how do we understand where 332 00:11:39,100 --> 00:11:41,100 that data is coming from? Because as I 333 00:11:41,100 --> 00:11:43,019 start to compound the value of that data 334 00:11:43,019 --> 00:11:45,820 and start to create, like, relational relationships of 335 00:11:45,820 --> 00:11:48,379 what I'm pulling out across the the value 336 00:11:48,379 --> 00:11:50,299 train, I need to know where it's coming 337 00:11:50,299 --> 00:11:52,475 from. And without, like, that ontological 338 00:11:53,654 --> 00:11:56,215 discipline, right, like, the the naming structures, it's 339 00:11:56,215 --> 00:11:58,455 very hard to figure out and scale stuff 340 00:11:58,455 --> 00:12:00,215 because I don't know where that is. So 341 00:12:00,215 --> 00:12:01,975 if every tag is named pump, but I 342 00:12:01,975 --> 00:12:04,540 don't know what machine it's coming from, it's 343 00:12:04,540 --> 00:12:06,000 very hard to create like 344 00:12:06,339 --> 00:12:06,839 the 345 00:12:07,179 --> 00:12:08,320 repeatable template. 346 00:12:09,019 --> 00:12:11,580 So that's like one of the the key 347 00:12:11,580 --> 00:12:15,179 limiter limiting factors of that. Now that also 348 00:12:15,179 --> 00:12:17,945 transpires onto the OEM side too because if 349 00:12:17,945 --> 00:12:19,465 I buy a piece of skid equipment, right, 350 00:12:19,465 --> 00:12:21,164 it's on address. It's just a ransom 351 00:12:21,625 --> 00:12:24,284 wash program that gets in there. So 352 00:12:25,144 --> 00:12:27,485 a lot of, you know, what control engineers 353 00:12:27,544 --> 00:12:29,865 or what end users do is like you 354 00:12:29,865 --> 00:12:31,865 have to be specific on on what you 355 00:12:31,865 --> 00:12:34,129 want there. Right? So there has to be 356 00:12:34,129 --> 00:12:35,889 things to follow. But my my word of 357 00:12:35,889 --> 00:12:36,870 advice is 358 00:12:37,970 --> 00:12:38,789 there's some 359 00:12:39,250 --> 00:12:42,049 extra work that is that needs to be 360 00:12:42,049 --> 00:12:43,110 done at the beginning 361 00:12:43,649 --> 00:12:44,789 phases for 362 00:12:45,330 --> 00:12:47,350 the proper structures of your tags. 363 00:12:47,795 --> 00:12:49,875 It will pay dividends down the line. If 364 00:12:49,875 --> 00:12:52,434 not, you're spending all half your time overcoming 365 00:12:52,434 --> 00:12:55,095 technical debt that you've inherited or 366 00:12:55,475 --> 00:12:56,615 decided to overlook. 367 00:12:57,394 --> 00:13:00,295 Yeah. I think, the integrators who are watching 368 00:13:00,355 --> 00:13:02,535 and the and and a lot of OEMs 369 00:13:02,675 --> 00:13:04,039 too, they know the importance 370 00:13:04,659 --> 00:13:06,580 of having some naming conventions and a lot 371 00:13:06,580 --> 00:13:07,559 of very large, 372 00:13:08,100 --> 00:13:10,899 you know, greenfield plants also too. They'll they'll 373 00:13:10,899 --> 00:13:13,299 put these standards out to the, you know, 374 00:13:13,299 --> 00:13:15,960 the the OEM supply and equipment and skids. 375 00:13:16,514 --> 00:13:19,074 And it's so very important because even from 376 00:13:19,074 --> 00:13:21,475 a training aspect of your personnel, your maintenance 377 00:13:21,475 --> 00:13:22,615 technicians, your electricians, 378 00:13:23,154 --> 00:13:24,674 but also if you start thinking like I 379 00:13:24,674 --> 00:13:26,355 was just on the planet floor talking to 380 00:13:26,355 --> 00:13:28,049 Kareem and Mahua and, 381 00:13:28,529 --> 00:13:30,230 you know, you start looking at AI. 382 00:13:31,409 --> 00:13:33,330 Right? But if you ask AI to create 383 00:13:33,330 --> 00:13:35,330 a routine for you, right, that's gonna interface 384 00:13:35,330 --> 00:13:37,669 with this new BFD you just got from 385 00:13:37,809 --> 00:13:38,309 Schneider, 386 00:13:39,169 --> 00:13:40,769 you want it to have the right naming 387 00:13:40,769 --> 00:13:42,794 convention from your company. And if it's just 388 00:13:42,794 --> 00:13:45,674 used as some random naming convention, nobody's trained 389 00:13:45,674 --> 00:13:46,875 on that. So I I can see it's 390 00:13:46,875 --> 00:13:48,095 important. But for brownfields, 391 00:13:48,554 --> 00:13:49,914 I can see that can be a daunting 392 00:13:49,914 --> 00:13:51,134 task as well because, 393 00:13:51,914 --> 00:13:53,934 like you said, you have a legacy 394 00:13:54,475 --> 00:13:56,554 plant full of equipment that was developed over 395 00:13:56,554 --> 00:13:59,679 time by different individuals and different integrators, different 396 00:13:59,679 --> 00:14:01,600 OEMs. So that could that can be I 397 00:14:01,600 --> 00:14:03,679 can I I can that can be pretty 398 00:14:03,679 --> 00:14:04,080 pretty, 399 00:14:04,799 --> 00:14:06,559 a daunting task to get that right? But, 400 00:14:06,559 --> 00:14:08,480 of course, you can always abstract that in 401 00:14:08,480 --> 00:14:09,620 the software layer. 402 00:14:11,154 --> 00:14:12,355 You know, I thought that I think that's 403 00:14:12,355 --> 00:14:14,054 really interesting. I you know, 404 00:14:14,434 --> 00:14:15,875 I guess what I'd like to ask you 405 00:14:15,875 --> 00:14:16,615 now is, 406 00:14:17,154 --> 00:14:18,514 you know, I was on the like I 407 00:14:18,514 --> 00:14:20,134 said, I was on the show floor, 408 00:14:20,674 --> 00:14:22,355 walking around, seeing all the great products you 409 00:14:22,355 --> 00:14:23,955 guys have out there. I've actually had a 410 00:14:23,955 --> 00:14:25,394 chance to do some hands on with some 411 00:14:25,394 --> 00:14:28,000 of those products. Thanks to partnering with Schneider 412 00:14:28,000 --> 00:14:28,960 to do that. 413 00:14:29,440 --> 00:14:31,840 But from your from your thought process, you 414 00:14:31,840 --> 00:14:34,019 know, in what you do, right, 415 00:14:34,399 --> 00:14:36,639 when you look at those, products on the 416 00:14:36,639 --> 00:14:38,259 show floor today, which ones 417 00:14:38,639 --> 00:14:40,320 do you think of when you're thinking about 418 00:14:40,320 --> 00:14:41,460 the digital transformation? 419 00:14:42,264 --> 00:14:44,365 Which ones do you come up mind first? 420 00:14:45,464 --> 00:14:46,824 I mean, there's a lot that comes into 421 00:14:46,824 --> 00:14:48,504 mind. Right? Because I'm a PLC guy by 422 00:14:48,504 --> 00:14:50,264 heart, so I always go back to that. 423 00:14:50,264 --> 00:14:51,245 I also like, 424 00:14:51,704 --> 00:14:53,384 high performance stuff. So one of the things 425 00:14:53,384 --> 00:14:55,799 I like is, like, the, m six sixty, 426 00:14:55,799 --> 00:14:58,200 like the new motion controller. I mean, you're 427 00:14:58,200 --> 00:15:00,440 talking 300 axes of coordinated motion in a 428 00:15:00,440 --> 00:15:03,159 single controller. Like, that one makes me happy 429 00:15:03,159 --> 00:15:06,039 because think about simplifying the architecture within a 430 00:15:06,039 --> 00:15:10,054 plant, multi lines, multi accesses of coordinated motion, 431 00:15:10,054 --> 00:15:12,534 like, pretty pretty neat design. So I think 432 00:15:12,534 --> 00:15:14,294 there's a lot of innovation and power that 433 00:15:14,294 --> 00:15:16,215 comes out of there, and it's fast. So 434 00:15:16,215 --> 00:15:17,894 I like that. But I also like, 435 00:15:18,215 --> 00:15:19,575 what we're doing with some of the other 436 00:15:19,575 --> 00:15:22,019 products, just some of the metadata that's contained 437 00:15:22,019 --> 00:15:24,019 within them. Okay. So, like, even on motor 438 00:15:24,019 --> 00:15:26,420 controls, right, it's always been, like, on off 439 00:15:26,420 --> 00:15:28,259 overload. But the TSYS Island, I don't know 440 00:15:28,259 --> 00:15:29,540 if you had a chance to play with 441 00:15:29,540 --> 00:15:30,820 that. Yes. We've had them on the show. 442 00:15:30,820 --> 00:15:32,420 That's a pretty cool little product as well 443 00:15:32,420 --> 00:15:33,960 too. Right? So there's predictive 444 00:15:34,565 --> 00:15:36,745 algorithms that are in there. You can see, 445 00:15:37,605 --> 00:15:39,784 cycle time. So all that, like, if I'm 446 00:15:40,004 --> 00:15:40,504 driving 447 00:15:40,964 --> 00:15:41,544 a reliability 448 00:15:42,085 --> 00:15:44,825 play or I want, asset performance management, 449 00:15:46,245 --> 00:15:48,884 it's like a insignificant cost in the value 450 00:15:48,884 --> 00:15:51,320 that it delivers from that little platform. So 451 00:15:51,320 --> 00:15:52,600 I'm starting to see, like, a lot of 452 00:15:52,600 --> 00:15:54,279 these little things that we're doing to solve 453 00:15:54,279 --> 00:15:56,700 these problems that are data rich 454 00:15:57,240 --> 00:15:58,379 that can be leveraged 455 00:15:58,759 --> 00:16:01,320 to drive other initiatives as well that I 456 00:16:01,320 --> 00:16:03,024 don't think a lot of people see that 457 00:16:03,024 --> 00:16:04,704 right now because it's just this is the 458 00:16:04,704 --> 00:16:06,644 way we've we've always done it. 459 00:16:07,184 --> 00:16:08,704 Yeah. That makes a lot of sense. You 460 00:16:08,704 --> 00:16:11,044 know, I'm wondering if somebody is listening. Right? 461 00:16:11,105 --> 00:16:12,544 And they're like, you know, I wanna I 462 00:16:12,544 --> 00:16:14,384 wanna implement this. This I love what they're 463 00:16:14,384 --> 00:16:17,100 talking about. I wanna implement this in my 464 00:16:17,100 --> 00:16:18,620 plan. I mean, I can just tell them 465 00:16:18,620 --> 00:16:20,220 to call you. But, I mean, what what 466 00:16:20,220 --> 00:16:21,659 would be some of their first steps that 467 00:16:21,659 --> 00:16:23,899 they would wanna do before they maybe set 468 00:16:23,899 --> 00:16:25,500 an appointment with you or your one of 469 00:16:25,500 --> 00:16:27,580 your colleagues at Schneider? Yeah. So I think 470 00:16:27,580 --> 00:16:29,325 the key to one of the reasons that 471 00:16:29,325 --> 00:16:32,205 digital transformations fail is there's no leadership commitment. 472 00:16:32,205 --> 00:16:33,884 So it's not a it's not done in 473 00:16:33,884 --> 00:16:36,125 a vacuum. Right? And it's not just playing 474 00:16:36,125 --> 00:16:38,044 with technology. The key is to getting it 475 00:16:38,044 --> 00:16:40,924 to scale to solve repeatable problems across the 476 00:16:40,924 --> 00:16:41,424 organization. 477 00:16:42,289 --> 00:16:45,009 And that so I always conflate the 80% 478 00:16:45,009 --> 00:16:46,769 should be consistent and standard. And if you 479 00:16:46,769 --> 00:16:48,789 look at Schneider Electric's digital transformation 480 00:16:49,169 --> 00:16:52,049 story, they've scaled, they started their smart factory 481 00:16:52,049 --> 00:16:53,589 program 2018, 482 00:16:54,284 --> 00:16:55,024 started with 483 00:16:55,644 --> 00:16:58,365 11 factories and scaled to 150 484 00:16:58,365 --> 00:17:00,125 today. So a short period of time, seven 485 00:17:00,125 --> 00:17:01,985 years taking COVID into consideration. 486 00:17:02,605 --> 00:17:04,765 We now have what we would evaluate as 487 00:17:04,765 --> 00:17:05,825 a 150 488 00:17:06,299 --> 00:17:09,120 smart factories. Seven of those are world economic 489 00:17:09,180 --> 00:17:10,240 lighthouse facilities. 490 00:17:10,860 --> 00:17:12,940 But the key to that scale is common 491 00:17:12,940 --> 00:17:17,100 consistent core across that. So our VP that 492 00:17:17,100 --> 00:17:18,860 went through that likes to say it was 493 00:17:18,860 --> 00:17:21,605 a boring transformation. If you go to any 494 00:17:21,605 --> 00:17:23,684 plant around the country, they look exactly the 495 00:17:23,684 --> 00:17:26,345 same. The same technology, the same use cases. 496 00:17:26,404 --> 00:17:27,865 So 80% is, 497 00:17:28,884 --> 00:17:31,684 consistent across how we're gonna operate our plants, 498 00:17:31,684 --> 00:17:34,019 how we're gonna calculate OEE, how we're gonna 499 00:17:34,339 --> 00:17:34,839 run 500 00:17:35,380 --> 00:17:36,200 our manufacturing 501 00:17:36,580 --> 00:17:39,320 system, which is our, you know, manufacturing bible. 502 00:17:39,460 --> 00:17:42,099 And then 20% is more customer nichey to 503 00:17:42,099 --> 00:17:42,839 that location. 504 00:17:43,380 --> 00:17:44,660 So a lot of people wanna do the 505 00:17:44,660 --> 00:17:47,474 the nichey one offs, but it's about understanding 506 00:17:47,474 --> 00:17:49,154 like where the business has to go. So 507 00:17:49,154 --> 00:17:51,075 if I'm a control engineer and I'm being 508 00:17:51,075 --> 00:17:52,134 tasked with this, 509 00:17:52,434 --> 00:17:53,955 I want to get aligned with where the 510 00:17:53,955 --> 00:17:56,115 business is going. I want to be tied 511 00:17:56,115 --> 00:17:58,355 in with operational excellence to figure out how 512 00:17:58,355 --> 00:17:59,894 they're running continuous improvement. 513 00:18:00,200 --> 00:18:02,599 I want to simplify my designs before I 514 00:18:02,599 --> 00:18:03,819 start to transform, 515 00:18:04,759 --> 00:18:07,000 because a lot of times, right, we got 516 00:18:07,000 --> 00:18:09,640 clunky systems that aren't as efficient. So I 517 00:18:09,640 --> 00:18:11,099 don't want to automate inefficiencies. 518 00:18:11,880 --> 00:18:14,804 So simplify, standardize, digitize. Right? But it's it's 519 00:18:14,804 --> 00:18:17,365 really getting a clear definition of where the 520 00:18:17,365 --> 00:18:19,204 company is and where it wants to go, 521 00:18:19,204 --> 00:18:21,144 and then aligning to that strategy. 522 00:18:22,005 --> 00:18:23,525 And I didn't ask you beforehand if we 523 00:18:23,525 --> 00:18:24,884 could talk about this, but would it be 524 00:18:24,884 --> 00:18:26,579 okay for you to mention your podcast? 525 00:18:26,980 --> 00:18:28,819 Oh, yeah. So I run a podcast on 526 00:18:28,819 --> 00:18:31,319 digital transformation. It's called Practitioners Unplugged. 527 00:18:31,779 --> 00:18:33,720 You can find me on LinkedIn, Dante Vaquero, 528 00:18:34,179 --> 00:18:36,440 or on Industrial Sage. But, 529 00:18:36,899 --> 00:18:38,980 really, the the basis of that podcast is 530 00:18:38,980 --> 00:18:40,440 just to talk digital transformation 531 00:18:40,845 --> 00:18:43,644 stories. Right? What works? What doesn't work? Learn 532 00:18:43,644 --> 00:18:45,964 about different industries. We don't focus as much 533 00:18:45,964 --> 00:18:47,644 on the technology, but, hey, how do we 534 00:18:47,644 --> 00:18:48,704 sell this to leadership? 535 00:18:50,125 --> 00:18:53,184 What what are what works well? What doesn't? 536 00:18:53,404 --> 00:18:55,005 What importance does it have to have a 537 00:18:55,005 --> 00:18:56,544 sound manufacturing philosophy? 538 00:18:57,190 --> 00:18:58,710 So we just try to, you know, get 539 00:18:58,710 --> 00:19:01,110 stories from the front lines and don't really 540 00:19:01,110 --> 00:19:04,230 push product or software, but it's it's just 541 00:19:04,230 --> 00:19:06,630 a community to connect on with people going 542 00:19:06,630 --> 00:19:09,610 through struggles to to talk and figure out 543 00:19:09,750 --> 00:19:11,269 how do we learn from the past or 544 00:19:11,269 --> 00:19:11,769 not. 545 00:19:12,445 --> 00:19:13,884 Well, I think too, if you're gonna make 546 00:19:13,884 --> 00:19:15,724 a proposal up a management, it's good to 547 00:19:15,724 --> 00:19:17,164 have that kind of to be able to 548 00:19:17,164 --> 00:19:18,305 hear those kinds of stories. 549 00:19:19,085 --> 00:19:21,164 Because, the the day of just putting AI 550 00:19:21,164 --> 00:19:23,404 in something and getting it approved, those days 551 00:19:23,404 --> 00:19:25,599 are coming to an end. And, you know, 552 00:19:25,599 --> 00:19:27,359 budgets are getting tightened. In some places, they 553 00:19:27,359 --> 00:19:28,720 get an open, and other places, they get 554 00:19:28,720 --> 00:19:30,819 in tightened. So, you know, being able 555 00:19:31,440 --> 00:19:33,039 to spend you know, have more of that 556 00:19:33,039 --> 00:19:34,640 information from your pockets, I think, would be 557 00:19:34,640 --> 00:19:36,799 extremely helpful, which is why I appreciate you 558 00:19:36,799 --> 00:19:38,454 sharing that. You know, I, 559 00:19:38,934 --> 00:19:40,214 come to the end of my list here, 560 00:19:40,214 --> 00:19:41,994 and I'd like to end this, you know, 561 00:19:43,095 --> 00:19:45,815 these podcasts by kinda looking forward and saying, 562 00:19:45,815 --> 00:19:47,654 you know, what do you see coming down 563 00:19:47,654 --> 00:19:49,255 the pike? And it doesn't have to be 564 00:19:49,255 --> 00:19:50,234 limited to 565 00:19:50,774 --> 00:19:51,914 digital transformations 566 00:19:52,774 --> 00:19:54,910 per se, but just, you know, if we 567 00:19:54,910 --> 00:19:56,509 had a crystal ball and we were looking 568 00:19:56,509 --> 00:19:57,009 out, 569 00:19:57,309 --> 00:19:59,950 you know, next year, two, three, what are 570 00:19:59,950 --> 00:20:01,730 some of the trends you're seeing? 571 00:20:02,590 --> 00:20:05,470 I would say the biggest focus now is 572 00:20:05,470 --> 00:20:06,289 gonna be, 573 00:20:06,775 --> 00:20:08,075 like, increased automation 574 00:20:08,535 --> 00:20:10,634 and more agentic AI. 575 00:20:11,174 --> 00:20:13,494 So if you look at that, like, MCP 576 00:20:13,494 --> 00:20:15,255 protocol is starting to pick up a little 577 00:20:15,255 --> 00:20:16,554 bit, model chain protocol. 578 00:20:17,654 --> 00:20:20,529 And what the agentic aspect of that allows 579 00:20:20,529 --> 00:20:22,390 you to do is run lower, 580 00:20:23,890 --> 00:20:26,130 let's call it lower bandwidth models, right? So 581 00:20:26,130 --> 00:20:28,369 I can create smaller agents that are trained 582 00:20:28,369 --> 00:20:30,369 on subsets of data instead of like this 583 00:20:30,369 --> 00:20:32,690 big monolithic chat gbt thing. So, you know, 584 00:20:32,690 --> 00:20:34,724 when we query chat gbt, it scans the 585 00:20:34,724 --> 00:20:37,765 whole entire Internet, but here you create agent 586 00:20:37,765 --> 00:20:38,744 to agent interactions. 587 00:20:39,204 --> 00:20:41,125 So I have a quarterback agent that goes 588 00:20:41,125 --> 00:20:43,605 out to individual expert agents within my plan. 589 00:20:43,605 --> 00:20:45,045 So I could have a quality agent, I 590 00:20:45,045 --> 00:20:46,105 could have a asset, 591 00:20:46,724 --> 00:20:47,785 predictive analytics 592 00:20:48,179 --> 00:20:48,679 agent. 593 00:20:49,059 --> 00:20:51,220 And I ask the system what's going on, 594 00:20:51,220 --> 00:20:53,159 and I get the information I want back. 595 00:20:53,220 --> 00:20:54,899 So I think the landscape is gonna change 596 00:20:54,899 --> 00:20:56,419 over the next couple of years as this 597 00:20:56,419 --> 00:20:59,379 technology evolves. But the the MCP protocol and 598 00:20:59,379 --> 00:21:02,039 the agentic AI on the industrial floor, 599 00:21:02,744 --> 00:21:04,984 I think it in the infancy stages, we'll 600 00:21:04,984 --> 00:21:08,025 come back in an advisory capacity, but three, 601 00:21:08,025 --> 00:21:09,865 four years down the road, it might take 602 00:21:09,865 --> 00:21:11,325 control of, like, operations. 603 00:21:13,305 --> 00:21:15,250 Yeah. And I think, and and I I 604 00:21:15,250 --> 00:21:17,009 think too, another trend will be maybe people 605 00:21:17,009 --> 00:21:19,269 will understand AI better because I think, 606 00:21:19,809 --> 00:21:22,470 as you kinda alluded to earlier, AI today, 607 00:21:22,929 --> 00:21:24,450 a lot of people just think of chat 608 00:21:24,450 --> 00:21:26,769 GPT. Right? So that that's what they think 609 00:21:26,769 --> 00:21:28,450 AI is. I I was on vacation a 610 00:21:28,450 --> 00:21:30,275 couple years ago, and a gentleman, 611 00:21:30,734 --> 00:21:33,215 recently retired from business, was telling me that 612 00:21:33,215 --> 00:21:34,755 AIs were programming themselves. 613 00:21:35,375 --> 00:21:37,535 And so, you know, the difference between machine 614 00:21:37,535 --> 00:21:40,174 learning and AI and the different types like 615 00:21:40,174 --> 00:21:43,075 generic general, general AI versus other AI, 616 00:21:43,440 --> 00:21:45,279 I think that's important. There's a learning curve 617 00:21:45,279 --> 00:21:47,440 I think we're all on. Yeah. And I 618 00:21:47,440 --> 00:21:48,720 also think too and have you found this 619 00:21:48,799 --> 00:21:50,079 and I know I'm kinda going off the 620 00:21:50,079 --> 00:21:51,759 topic here a little bit, but have you 621 00:21:51,759 --> 00:21:54,159 found that people you're educating people on AI? 622 00:21:54,159 --> 00:21:56,419 Because a lot of times people are applying 623 00:21:56,480 --> 00:21:58,914 AI, even the buzzword AI. Look back like 624 00:21:58,914 --> 00:22:02,034 smartphones, smart TVs. Everything was smart. I always 625 00:22:02,034 --> 00:22:03,794 told my wife, none of this is smart. 626 00:22:03,794 --> 00:22:06,194 Yeah. They just have apps that doesn't make 627 00:22:06,194 --> 00:22:08,674 them smart. But, are you finding you're spending 628 00:22:08,674 --> 00:22:10,994 a lot of time educating people on AI 629 00:22:10,994 --> 00:22:13,029 and what is and what isn't in the 630 00:22:13,029 --> 00:22:15,029 different types of AI? Yeah. We spend a 631 00:22:15,029 --> 00:22:16,309 little bit of time on that. I think 632 00:22:16,309 --> 00:22:18,710 everybody says our CEO wants an AI strategy, 633 00:22:18,710 --> 00:22:20,390 so we have to pull it out. And 634 00:22:20,390 --> 00:22:21,910 it goes back to that onto the logic 635 00:22:22,070 --> 00:22:24,325 onto the logical discussion. Right? If you don't 636 00:22:24,325 --> 00:22:25,944 have the data, you don't have organization, 637 00:22:26,404 --> 00:22:27,625 history, context, 638 00:22:28,404 --> 00:22:29,924 you're not gonna get what you want out. 639 00:22:29,924 --> 00:22:30,964 Right? So if I don't know where the 640 00:22:30,964 --> 00:22:32,644 data is coming from, I don't have a 641 00:22:32,644 --> 00:22:33,144 reference 642 00:22:33,524 --> 00:22:36,164 of history. How am I supposed to model 643 00:22:36,164 --> 00:22:38,319 something out of that? So it's chicken or 644 00:22:38,319 --> 00:22:39,919 the egg. Yeah. But we need AI. It's 645 00:22:39,919 --> 00:22:42,240 not that simple. Right? It doesn't work without 646 00:22:42,240 --> 00:22:44,079 data. So you have to have a plan 647 00:22:44,079 --> 00:22:46,000 for your data. There are steps to follow 648 00:22:46,000 --> 00:22:46,659 to that, 649 00:22:47,119 --> 00:22:49,619 you know, historization, organization, contextualization, 650 00:22:50,079 --> 00:22:51,919 and then analytics can go on top of 651 00:22:51,919 --> 00:22:53,565 that. But if I don't know where it's 652 00:22:53,565 --> 00:22:55,265 coming from, what it means, then 653 00:22:55,724 --> 00:22:57,724 you have, you know, crap in crap out. 654 00:22:57,724 --> 00:22:59,804 Right? So that's just what it is. Right? 655 00:22:59,804 --> 00:23:01,105 We've seen people prompt 656 00:23:01,484 --> 00:23:02,924 chat GBT and like, I don't like what 657 00:23:02,924 --> 00:23:04,065 I got out. You said, 658 00:23:04,444 --> 00:23:06,204 what's the weather like today? So it doesn't 659 00:23:06,204 --> 00:23:07,319 know what city you're in, 660 00:23:07,799 --> 00:23:09,960 where you're at. So, again, it's like you 661 00:23:09,960 --> 00:23:11,720 have to prepare for it. So I I 662 00:23:11,720 --> 00:23:13,240 tried to take a step back. It's like, 663 00:23:13,240 --> 00:23:15,639 okay. You haven't done steps. You you're not 664 00:23:15,639 --> 00:23:17,319 even in industry four point o yet. Right? 665 00:23:17,319 --> 00:23:18,440 So you don't even have any of this 666 00:23:18,440 --> 00:23:20,440 information. So how are you just gonna jump 667 00:23:20,440 --> 00:23:22,220 ahead? It's not magic. Right? 668 00:23:22,679 --> 00:23:22,964 Yep. 669 00:23:23,924 --> 00:23:25,525 Well, that's it for my questions. Was there 670 00:23:25,525 --> 00:23:26,964 anything else you wanted to mention before we 671 00:23:26,964 --> 00:23:29,044 wrap it up? Any other anything, maybe, we 672 00:23:29,044 --> 00:23:30,184 talked about your podcast. 673 00:23:30,565 --> 00:23:33,605 Maybe, talk about, any any events coming up. 674 00:23:33,605 --> 00:23:35,125 Are you doing any sessions here at the 675 00:23:35,125 --> 00:23:36,900 show that people can look up afterwards? 676 00:23:37,200 --> 00:23:38,720 I'm not doing any sessions. I'm recording a 677 00:23:38,720 --> 00:23:40,640 couple podcasts that are gonna be out here. 678 00:23:40,640 --> 00:23:43,359 So, we had a CEO that we just 679 00:23:43,359 --> 00:23:45,380 interviewed this morning on interoperability. 680 00:23:45,759 --> 00:23:47,940 So how to sell the concept of interoperability, 681 00:23:48,400 --> 00:23:49,835 another buzz word, guys. 682 00:23:50,615 --> 00:23:52,294 So we we unpack what that means and 683 00:23:52,294 --> 00:23:53,815 how to sell that to leadership in in 684 00:23:53,815 --> 00:23:55,335 that episode, and we have a couple other 685 00:23:55,335 --> 00:23:56,954 things that we're doing. But, 686 00:23:57,575 --> 00:23:59,674 yeah, I'm involved in the community. 687 00:24:00,134 --> 00:24:01,837 I love manufacturing. My mission is to help, 688 00:24:01,837 --> 00:24:03,034 like, US manufacturing excel and 689 00:24:05,340 --> 00:24:06,940 and get back to that resurgence because I 690 00:24:06,940 --> 00:24:08,940 I really believe that, you know, technology can 691 00:24:08,940 --> 00:24:09,440 help 692 00:24:09,820 --> 00:24:11,259 all of these issues that we have. So 693 00:24:11,259 --> 00:24:13,279 this is really what I'm passionate with, automation, 694 00:24:13,740 --> 00:24:14,720 digital transformation. 695 00:24:15,180 --> 00:24:16,859 And thank you so much for coming out, 696 00:24:16,859 --> 00:24:18,704 spending the time, and inviting me on your 697 00:24:18,704 --> 00:24:20,384 show. Oh, thank you for coming on the 698 00:24:20,384 --> 00:24:21,984 show and letting me interview you. Well, I 699 00:24:21,984 --> 00:24:23,585 hope you enjoyed that episode. I wanna thank 700 00:24:23,585 --> 00:24:25,105 Dante for coming on the show to talk 701 00:24:25,105 --> 00:24:26,325 to us about digitization, 702 00:24:27,265 --> 00:24:28,325 trends in automation, 703 00:24:28,704 --> 00:24:30,625 and about his podcast as well. Check that 704 00:24:30,625 --> 00:24:31,684 out if you're interested. 705 00:24:32,019 --> 00:24:33,859 And, I also wanna thank Schneider who not 706 00:24:33,859 --> 00:24:35,539 only sponsored this episode to us so we 707 00:24:35,539 --> 00:24:37,220 could release it to you ad free, but 708 00:24:37,220 --> 00:24:39,140 also flew me out to their event so 709 00:24:39,140 --> 00:24:40,200 I could actually record 710 00:24:40,500 --> 00:24:42,259 all of these episodes that will be coming 711 00:24:42,259 --> 00:24:43,559 out in the coming weeks. 712 00:24:43,888 --> 00:24:45,408 With that said, I do wanna thank you 713 00:24:45,408 --> 00:24:47,408 again for tuning in this week. I wanna 714 00:24:47,408 --> 00:24:49,648 wish you all good health and happiness. And 715 00:24:49,648 --> 00:24:51,028 until next time, my friends, 716 00:24:51,888 --> 00:24:52,388 peace.