Delivering Modern Manufacturing Outcomes with AI at the Edge

hello everyone thank you for joining our webinar I'm Jacob Smith I'm an engagement associate with mxd I'm going to get us kicked off here um so thanks again for joining we are here to talk about delivering modern manufacturing outcomes with AI at the edge with our co-sponsor here Google Cloud before we begin I just wanted to do a couple of housekeeping items so uh If you experience any technical difficulties or like to communicate with mxd staff or fellow attendees the webinar please use the chat box in your go to webinar panel in addition please feel free to submit any questions you may have throughout the webinar uh we will be taking audience questions toward the end if time allows otherwise we'll follow up after um with some answers to your questions and finally this webinar is being recorded so we will be making the video and slides available on our Platforms in the coming weeks and with that out of the way I'd like to um just briefly introduce our partner organiz ations who are helping us out with the webinar today so you see up on the screen here Fabian dubbu manufacturing industry manager at Google Cloud Dario saltier senior project manager product manager excuse me at Google Cloud distributed Google distributed cloud with UGA Google cloud and then Derek Bley VP of products at Clear object um so that's our partner organizations and then I'd also like to introduce our CTO here at mxd federo shamella he's going to give give us just a couple um quick notes about who mxd is and then get us uh kicked off here with our program so federo if you'd like to turn your camera on and get us started here there you are yeah good afternoon everyone thank you so much for joining super excited you know webinars uh were something we did quite a bit uh many years ago so it's exciting to be back and and be uh doing this webinar with all of you um let's get this presentation started uh so really for those that may not know we are um mxd which stands for manufacturing times digital we are the N nation's digital uh manufacturing and cyber security Institute so what do we do we strengthen National Security and economic Prosperity by increasing us manufacturing competitiveness by advancing adoption of digital manufacturing let's go to the next slide I want to just highlight what manufacturing USA is we're a part of that this was started back after 2008 economic collapse President Obama really saw the need to drive Innovation across our manufacturing industry there are 17 manufacturing Innovation institutes in all uh nine which are funded and sponsored by the Department of Defense of which we are one of them there are seven that are funded by the department of energy and Nimble as you see there on the bottom right corner which is f uh sponsored by Department of Commerce there will be two additional institutes coming over the next year one focused on digital twins for Semiconductor manufacturing as well as one in AI for manufacturing resilience this ecosystem is here to help you the manufacturers understand how to leverage these Technologies and really want to focus uh on the next slide what mxd does specifically to help manufactur Drive adoption for digital manufacturing first and most important is convening the ecosystem much like with this webinar today bringing in the experts to talk about the issues uh facing manufacturers in this case understanding cloud and how to leverage uh these Technologies with AI at the edge so I'm really looking forward to our partners speaking towards that um the second is by advancing Technology Innovation and adoption so as we explain these Technologies as we understand through our convening what the issues are we will fund projects to support um the development of those uh adoption capabilities and provide manufacturers with those requisite skill sets and finally we Empower our Workforce we look to the future of what manufacturing holds we have uh two hiring guides that describe over 400 roles in uh manufacturing for digital and cyber security and we really look to defining what those skill sets are and the requirements so as we hear about uh today Ai and other things how are those roles critical to where manufacturers need to be and what are the skill sets required so uh as I said today it's really about understanding uh Cloud leveraging the tools and we're so excited to have our partners I now would like to introduce Dario who's going to talk a little bit about what uh Google is doing in this space Ario I'm going to turn it over to you thank you federo can we go to next okay so manufacturers today face several challenges that modern technology particularly Cloud Edge Computing and generative AI can help address first many manufacturing sectors are experiencing significant labor shortages Edge Computing can enable real-time monitoring and optimization of manufacturing processes reducing the need for manual intervention generative AI can reduce training times and improve performance by facilitating sharing best practices across workers it can also automate some repetitive task freeing up people for more complex and valuable roles second ensuring consistent product quality is a constant challenge for manufacturers Edge Computing can enable realtime quality inspections and adjustment on the production line this could be coupled with generative AI to analyze vast amount of production data to identify patterns and anomalies that might indicate quality issues with a natural language interface allowing for early intervention and prevention third manufacturers are under increasing pressure to reduce their environmental impact AG Computing platforms can track and analyze energy consumption and Emissions data which coupled with generative AI can help in identifying Improvement opportunities to optimize processes and minimize waste and resource consumption finally as manufacturers adopt more connected Technologies they become become increasingly vulnerable to cyber attacks Cloud providers offer robust security features to protect sensitive data and systems however Edge Computing can isolate critical production processes from the wider Network reducing even further the risk of disruption from a Cyber attack next slide please so how Google is helping to solve these issues Google distributed cloud is a cloud native platform for running applications on the edge it is fully managed with the centralized management plane providing a unified approach for developing and running Solutions across cloud and on premises this helps to extend the cloud while reducing TCO for on Prem operations it is deploy Deployable across a hybrid topology with Integrated Security and compliance for transport apps data and access management our manufacturing customers are leveraging Google scale and expertise to modernize their infrastructure in an agile and cost efficient manner they're also leveraging our Rich Partner ecosystem like clear object who have a permanent demo running on Google DED Cloud at mxd Derek will share now more details about their Solutions yeah thanks Dar appreciate it uh as Dario mentions we're a Google Premiere partner so we're leveraging Google Technologies um some of our own software to really deliver and and AI uh Solutions I thought what better way to kind of show what we're talking about here uh in this webinar than an actual demonstration this demonstration uh I'd recommend anyone go see it's running live at the mxd facility uh in this you're seeing our AI uh software from Clear object running on the Google distributed Cloud Edge Hardware uh in this instance we've used our software to customize an AI model in this instance it's uh interactive demo uh which is doing a few things ultimately identifying these cans in the line the distance between those in real time as well as the defects uh you can interactively kind of add some defects um in this same demonstration you can see how that information is leveraged in a hybrid architecture with Google Cloud leveraging the cortex framework where data is being seamlessly uh presented um back to a user in a way that they can leverage gener of AI technology to ask questions about that information information minimizing the need to have that operator really understand how to perform a structured data query or an understanding of even the overall uh database structure itself or the customization of uh bi dashboards for every Edge use case um and we're seeing operators uh who are Partners um deliver these Solutions in Real uh real time uh delivering value of 500 % Roi we've seen reduction in CO2 emissions all by leveraging Edge based uh technology the the second demonstration uh that's going to be pulled up here uh is just another example of how there's a broad range of application this example specifically demonstrates in a manufacturing process around Granite you might look at this and say okay well how's a AI system going to help me here uh in this case you can think that the heat uh from the flame the cooling from the water and the line speed uh can impact the overall quality of that uh operator or customer in this case wanted to really understand how do I better how can I measure this right this is an old piece of technology I don't have software we implemented with an edge-based Vision system uh that allowed that operator in real time to understand both the flame intensity uh the water percentage and line speed uh with an automated process control where you can actually take the insides from this Edge system tie that directly to a PLC for either operator driven um action or like I said automated process control where that PLC is actually making changes to that leveraging the Google Cloud platform um and again the cortex framework you could think about how you might introduce a few of these systems across your line um leveraging both Vision other standard Hardware sensors pulling all that information in um and providing an insights back to users similar back to that first demonstration where then you can provide generative AI Solutions as well uh that allow your operators to understand what's happening these are just a few examples like I said there's broad range um that we're seeing across many industries of manufacturing for this solution I'll hand it back to freder Rico as we uh get started here with some of the panel discussion thanks Derek yeah and I'll invite all the panelists to to get on camera it's I'm really excited to start this conversation with all of you to discuss how we deliver modern manufacturing outcomes with AI at the edge we're going to focus on use cases modernizing infrastructure Ai and security and then we're going to wrap up with the what the future will bring and I have to say we've had a really good discussion between the four of us leading up to the event um you know talking about what are the issues obstacles uh obstacles and possibilities so Fabian I want to start with you uh what does Modern manufacturing what does that modern manufacturing center look like and how should decision makers prioritize uh use cases for them yeah thank you thank you Federico so you know first we understand what modern manufacturing center is is it meaning some some our customers are out ofd manufacturing I don't think so what I think is like we need to understand how they can apply and this technology is advanced technology to innovate like you said when you made the introduction on what the objective at mxd is and this is why we chose to be present at mxd with our partner here clear object and you know display and showcase some of this capability that Derek showed you in the video Dario summarized really well what the challenge that these Manufacturing Company are facing to become more modern so typically what focus on understanding where they're starting from so when we sit down with the customer what are the objective that they might have in terms of transforming their business it could be a very specific Niche solution that they're looking at like visual inspection or it could be you know a full digital strategy that they want to put in place so we'll start there and then we'll show them how they can apply some of these technology like Edge Computing or AI at the edge to solve some of this problem so I would think most of the things that our customer bring to us are around quality control so you notice that the video of D helps the workforce to be connected to what's happening in real time the beauty of you know Edge Computing paired with let's say private 5G is going to be enabling the manufacturing company to gain a lot of insight of what's happening at the equipment level but share in real time and translate that Insight of what's happening at the equipment level to a worker a worker that could have studied a week ago and with that knowledge that is gained what they're gaining is agility and speed okay because today they're doing it the problem they're doing it with Mees system PLM system Erp system qms system limb system it's all good except we can accelerate with the Advent of age computing you understand we are delivering just to be clear we're delivering Google Cloud on Prem Google dist cloud is Google Cloud in your facility so you're getting the way we design those chips the way we do the workload with AI on those chips they they've been trained and and and the performance of the chip is 30% more efficient than anything else out there so you're getting on your ESG call so I'm going to stop here but it's all up to the customer to tell us I have a cost optimization problem I have you know warehousing and inventory so then we'll start looking how we can deploy the solution thank you no that's a great point it's as we see and often when we have visitors at mxc right start with what the problem is and I don't know Derek there may be some other things I know you talked about Roi and and showed that a little bit but what are some other things that that decision makers have to do to prioritize um with the use cases yeah you know it's a great topic uh customers a lot of times you know they're coming to us here's our problems hey you know you guys are the experts help us put a solution together uh but really hey you know what the first question we always ask okay based on those problems how do we start to prioritize those you know all the customers are looking for those hey high value low effort um right and so that's where a lot of this technology enables a lot of those Solutions where that effort has really gone down um so the Google distributed you know the GDC and its technology really enabling edge-based uh analytics to become more readily available uh to those customers is is really important um and you know when we when we talk with some of those customers they are now starting to talk about hey what does a modern use case look like in 2030 when we talk about lights out manufacturing um what is that going to require right and we talk about well you're going to need Edge Computing um you know not all this you know both security and bandwidth and everything else right all this information can't be going just to the cloud we've got to think about what makes sense to really be occurring there um you know in those demonstrations that you saw um what's happening in the edge is is the insights that are needed directly for those operators to make decisions that's really where we you know try to help our customers understand that's when we talk about Edge that's what you want you want to drive those actions that you know need realtime um analytics to be done so that the actions can be taken whether by operator or like we discussed automated process control the visualization through a web application like you did see you know that can that that's more of a web based that could be distributed to anyone um again with the Google technology that allows hey anyone around the globe can see how this manufacturing facility that's where I talked about the lights out right a centralized location understanding how things are performing you can see exactly what that AI system uh is doing which also helps helps with adoption right it's no longer a black box but ultimately a better understanding of what that edge-based system is doing great all right so from use cases we'll move to the next theme to modernizing infrastructure often a scary topic so so Dario uh what are some of the ways that manufacturers can approach this challenge when they're thinking about modernizing what that means maybe talk a little bit about that yes sure so as I mentioned earlier uh Google couples a fully managed offering where we are bringing the our scale and expertise and even take care of remotely monitoring your infrastructure with the Rich Partner ecosystem that brings a proven solutions for different verticals not just manufacturing but this enables manufacturers to embrace the these transformational efforts but at the same time reduce the complexity and the time it takes to modernize their infrastructure uh at the end this result in a higher success rate uh much quicker realization of benefits and going forward a lower TCO great and Derek maybe also you know because you've dealt with it with some of the use cases what are some of the things that you see uh that are helpful for manufacturers to to approach understanding how to modernize yeah um so you know again this goes back to what is the problem and what are the phases of which we can help solve Sol that problem uh so I definitely say hey you don't have to tackle uh you know modernizing your entire infrastructure uh recommend starting hey one one use case right let's let's solve that one use case let's understand what is the hardware required for that given use case um you know with the idea of knowing okay what we put in place has to be scalable so as we start to roll this out it works that is benefit of the GDC right you've got all of the backing of Google really making sure that we can run run those and it scales required um providing all the hardware um and infrastructure as necessary to run these systems and then you know a big thing that we see specifically based here in the Midwest is a lot of our customers uh have old equipment right 100- year old equipment they don't want to invest in brand new uh Million Dollar Plus Capital uh just to get the latest technology uh and we tell them that that's no longer needed right uh with a lot of this Leverage um you know the GDC uh our Solutions based on top of that really allows you to get the latest and greatest capabilities from a lot of these systems using um your you know standard cameras uh Hardware sensors combining that technology with these Edge analytics so now your old equipment um you have an understanding of how it's operating you can uh make sure you know how to operate that equipment using all that greatest uh new tech uh new tech that we've provided on the old equipment yeah that that is something that again we show here on the floor and not just in the space where Google's at but you know really showing how Legacy equipment can be used and capturing that data and I think this goes well with our next theme around Ai and I I'll start with you Fabian but uh thinking about that knowing that we we we talk about this what are some of the ways that customers can innovate with AI right because it's it's one thing to kind of do one or twos or these Pilots but really as we think about that and we're modernizing and and talking to folks about you know the importance of data maybe just some examples of how people are starting to innovate with that yes so the the first thing in Innovation is like you know are we allowing the manufacturing company to meet their customers expectation you know so that means again can we allow them to get faster to meet the requirement of the customer uh can they be nimble so if the customer change or let's say they want custom order of something and there's a change order or M very small unit of one they're going to need to be able to make realtime decision so again going back to the worker like Derek mentioned if somebody has all the equipment you can still leverage you know Edge Computing and AI to learn if a worker is adding value or no value to the process itself so there's a lot of analysis that you can now run at the edge that previously you couldn't do you didn't know what was happening after the production start until the productiv Finish it's able to analyze what is happening at the production line level based on what the humans are performing you can leverage that computer vision for safety purpose or you know protecting your assets protecting even your IP there's a lot of things that you can do that will allow you to optimize that production process then if you think about this can you feed this back in that information to whever designed the product so that they understand that it might create some bottleneck at the manufacturing level and then ideally what you want to Leverage is you know obviously all these technology added to one another are going to really make a really big transformation so now you do Edge comp Computing AI at the edge you do cloud and Analysis cloud computing you're able to create that framework and reach that industry for that the digal thread where everything is connected ideally obviously there is a lot more that's happening in a manufacturing plant and a a factory there is a lot of things regarding material flow human you know and warehousing and inventory you might be bringing some agv an autonomous vehicle you might leverage you know Edge Computing to be able to run all of this now let's go even further at one point you'll talk about virtual PLC so we're starting seeing this where you can create a virtual PLC and have it sit at the edge run your factory with just basically that pizza box okay so there is a one point of need where physical Hardware is going to cannot like become less relevant so no super exciting and Derek maybe just something that caught my eye in your second presentation of the first one that 50% reduction in CO2 maybe talk a little bit about energy management as it pertains the AI or or some other applications that really got me excited yeah no I mean it's a great area it's one that we're proud to you know be able to stand behind and in in Google as well of really of you know where that came into is understanding hey where I'm using raw materials um and how can I optimize the usage of some of those raw materials and the energy that's used in my manufacturing process and so when I talk about hey where are the areas that customers can innovate with AI That's a key starting area you know what is the process that uh you know how do you understand the process and how it's behaving today what are the variables within that how well are those being measured can we improve the way that they're being measured can we also improve the way way of how often we're created a model that identifies the most optimal State uh we run with a lot of customers who maybe they built a regression model that they've used now for years and it's been that state rather than being able to do something that's Dynamic that can change with the variables of those conditions that's really um you know one key area that we're seeing a lot of people innovate with AI um I think some of the other areas that you see is a lot around quality control um talking to operators hey where can I play AI you know I say hey where do you have a set of eyes within your process today whether that's you know 100% Quality Inspection or uh you know if it's samples every 15 minutes someone's going to check something hey you could put a vision system there that's now capturing 100% of those um so now you've got full quality full audit check capability um that it'ss on top of those and then the the final place that we're really seeing as people start to take advantage of these new Edge analytic systems uh as Google makes it easier to develop your models uh you know we're focused a lot on the productionize coming out of those um leveraging the cortex Frameworks bringing all that data together again back in a cloud environment um where we're now seeing models on top of models so AI is using now the outputs of these new state-of-the-art vision systems with some of the your other data that you have from ordering to now try to optimize based on how do you want to uh create create the best throughput so really exciting times of where you know I would say everywhere within your organization is probably uh has an opportunity to apply AI oh that's great and I think it's a perfect segue uh into our next theme which is security right uh and we'll talk about cyber certainly as the national Center for cyber security manufacturing mxd we we think about that a lot but maybe start with you Dario and and talk about you know what are some of the things that you've done to approach or help um approach this challenge of security maybe give us some some examples sure yes uh well Google is well known for having one of the best security practices in the industry right so we leverage our expertise in the cyber security space and ensure that all our offerings consider security as an integral integral part of of of them right it's not just a as an add-on or an afterthought so we are also um in Google distributed Cloud providing different features and operational models uh like boundary proxy and Bastion host something that is unique to our offering to give customers full control uh on their data so they uh can audit what data is being pushed to the cloud or or leaving their their premises and approve or remove previous approvals on specific data items or even have a break glass feature to stop any remote access to their on Prem infrastructure to keep a kind of peace of mind yeah um finally our product family can support different uh deployment models right from connected deployments to fully airgap Solutions where the entire infrastructure is disconnected from Google cloud or or or internet right if the customer prefers so for additional security uh we saw some sectors that need to ensure that no external actor could even get access to their data or infrastructure right and for them we are offering a gole distributed Cloud airgap solution which includes an operational center that is completely isolated from the cloud or from internet uh it's kind of a cloud in a box type of solution that could run completely isolated from the rest of the world if the customer decides or needs that that's great uh Fabian anything you want to add because I think that is an important part right that physical security right the OT side which we often manufacturers forget hey plc's they can get hacked right we demonstrate that on the floor so anything else you want to add to that in terms of security yeah that's why I mentioned the virtual uh PLC coming but like the what obviously what Dario says is very important it's all depend depends on the customer and the use case you know obviously there will be most of the case are going to be a hybrid environment and also the cyber security offering from that Dario mentioned is very unique in the industry where we're able to actually monitor your network traffic and protect your OT environment so we actually at mxd we just put together a live demo of our cyber security offering so allowing you to not only deploy things like Edge Computing fully a gap or not but then also monitor the traffic to protect your OT environment and and prevent from an ransomware attack from happening because we can detect it and and then shut down everything that needs to be done and remediate and Trace back to maybe the attacker so it's part of the antire offering so secret is definitely one of the key differentiator that we offer I'm glad you bought it up and uh I'll give it back to you know thank you great no that's perfect and I think uh this is exciting because we're getting to the last piece right when you're having fun at time flies we want to leave some time for questions so before I get to this last one just a reminder as Jacob mentioned please if you have any questions uh or comments that you want the panelist to talk about just type them in and and I'll get to them um but before that let's start with the future right our last theme um what are some of your priorities looking ahead through 2024 and Beyond in terms of of this capabilities of these things that we've talked about and maybe Derek I'll start with you uh just excited to hear what what your your priorities are and and what you're looking to for towards uh the end of this year and next year yeah you know it's uh it's an exciting time as we all know AI is the a great buzzword these days um and you know the one of the thing that has me excited a lot about was some of the I'll talk about just the generative AI capability and how that applies potentially even for things like this where we talk about Vision um you know one of the key key key problems that we see um as you're generating adoption for these systems is the ability to gen capture enough data to train a model uh to get to a performant level uh you know with some of the latest and greatest uh generative AI capabilities ability to generate images or what we may call synthetic data uh it's becoming more and more real I think that's really exciting to be able to demonstrate and create defects that maybe are rare examples but allow you to now create many variations of that uh that allow you to get to a higher performant model more quickly I think that's really exciting for you know the later half of 2024 and Beyond uh of what that's doing um you know I think more specifically what are we you know um as a partner focused on a lot of about um you know just being able to seamlessly create that interoperability between systems um leveraging uh again back to uh the cortex um you know what some people may have already heard is manufacturing data engine manufacturing connect all those really just focusing on how how seamlessly can we make it so that you're collecting uh and keeping that data in a good quality State uh I know it's the old adage but garbage in garbage out still applies uh so you know this technology that really really brings that all together helps you control that data uh can't be underestimated so those things are uh you know some of the things that got me excited what we're looking forward to in the later half of this year I mean Dario I don't know if you guys have some more more to add to that yeah yes Dario definitely um we uh will continue investing in in developing our platform our Google distri Cloud platform uh and also AI building blocks and and AI features right so we want to democratize the technology uh or the AI technology by reducing barriers of entry for our customers to simplify adoption of of new technology new use cases um we are also working on uh helping them to to deploy this uh these Solutions um provided by customers like clear object with an integrated marketplace where customers could shop for readymade Solutions and do a single click deployment on their infrastructure and then we are also integrating generative AI to uh how to manage how to operate our infrastructure so it's easier for customers to to to optimize their the their Solutions right on running on our plat great Fabian yeah I'll conclude by saying basically all we're doing is making that data accessible and useful so it's going back to what you said earlier at mxd you focus on making advanced technology um easy to adopt for this manufacturing company this is why we chose to be here empowering the empowering the workforce making sure that they can take an action because they Now understand what's happening so think about all these we talk about this all the time all of these workers that are retiring let's say if I'm retiring next week you might want to capture my knowledge in case you find it useful and now with the power of what we bring to the table you can record audio video unstructured data analyze it make it accessible for the next employee coming in and now it's all something that they can access but it's now useful because it's structuring the the data for you it's make it interactive so that you can ask a question and let's say I'm facing a piece of equipment like this and you know I can interrogate it be able to uh optimize the use of the equipment which means optimize the line and that that's always is the focus the focus is to really understand where this customer is starting from and how we can show him by you know bringing the customer to mxd we've had I think over 2,000 visitors in boost this year which is very exciting and then once they see it it's like it's a haha moment for them I mean we have existing customer that came who told us we didn't know we could do all of this with you and then we had customer who never interacted with Google Cloud who are now deploying our solution so extremely excited about the partnership thank you Federico and Jacob for having us and uh there's a few questions yeah in fact I think this is a perfect segue to to the question which I'm sure is on the mind of a lot of folks so you talk about old equipment see still being able to use Edge Computing what kind of investment is needed to get that started um I think you know that that's you know very valid right because costs are real and you know understanding there is investment and in in that what's the return and all that but maybe Derek or whomever wants to take that first I think it's understanding how much of an investment what kind of investment is needed to to get started yeah um I think the simplest way to answer that I always tell people it's a new car it's not a new house right so I think that tries to put it in a in a general ballpark of what you're talking about um you know the in in um in new car probably on the lower end of that um you know there ultimately there's the hardware that's needed um so the that uh can be from a minimal level to you know it just depends on the feasibility But ultimately i' say Hey you know you're talking you know you know 20 to 50,000 I'd say right is your TR General that that's hardware Services everything to really get started and start to demonstrate the feasibility you know typically we see the outputs of those is not only a demonstration of the feasibility but also a nice solution architecture with the you know what's the path forward what does this look like at full implementation understanding of your cost so that you can make informed decisions of how you roll this out across your organization yeah I think uh sorry just real quick Dario because I I I think that's important and I want to hear what you have to say I also want to add as we talk about this all the time this is a journey right there's not a destination right so whatever you invest now it will pay in the long run but you have to be committed and you have to make sure you have um the entire company uh under consideration right we did a study for the FDA on barriers to driving digital adoption we uh did it for 10 top pharmaceutical manufacturers and actually only two came out on top of really ahead in digital transformation and I'll spoil it here I was going to ask for who who thinks what what they did first uh it was actually change management they focused on change management first then did the technology and that takes investment as well and people often forget that so so I just want to bring that up Dario I'll turn over you and I know Fabian you you're passionate about that as well so I'd love to hear your thoughts but Dario please go ahead yeah but following with the car example that Derek or analogy that Derek mentioned we also have the option of lease the car or buy the car right so Google uh distributed Cloud could be leased on a monthly fee or purchased uh up from payment for the hardware and then paying for the service and then the service include our H system reliability Engineers that remotely monitor the hardware so you don't need to build a team that has to get some expertise for the platform you can lever as our s team that remotely manage the the hardware or the infrastructure including software patches system update Etc and our partner ecosystem that brings the expertise on managing their Solutions great Fabian I know you wanted to say something yeah oh yes but I agree completely with what you said and you brought up by the way on the change management and having support from executive usually that start with this because if not it's going to fail or it's it's going to be really slow at succeeding um but outside of this I like what Dario mentioned the flexibility so we're really an open platform you know we bring partner to the table will package whatever you need with the solution of the partner and you know you can think about even applying no code lood application at the edge which then suddenly the worker at the plant level can create their own application so they can get access to the data they need in the real time so there's a lot of things that comes with it this solution but then the the customer can also apply it to themsel to provide a service to their own customer so there's a lot of things that you can do with all this technology all it is is like bring bring us obviously the problem and to our partner and ourselves and sit down with us at mxd we'll kind of do a design thinking workshop and show you all the options that you have and it could be aligning with your digital strategy for the next three to five years like we do with most of our customer or figure out a very specific problem that you might have in the production process that needs to be solved because you're incurring 1550 million dollar of you know scrap a year so that's always a good one yeah yeah and and look U I really appreciate it I know we're we've got some more questions that we'll we'll hopefully get back to you if if you've posted one because we're running out of time here I just wanted to thank our panelists this has been a great discussion I know Fabian you've said it definitely for those that can come visit uh Chicago visit mxd visit uh the space here that Google has um it's really amazing once you get to see it as you said the light bulb goes off and that's what we're really here for is to to help you think about you know you're manufacturing what you do we're here to help you enable that so really uh appreciate the conversation today so thank you Derek thank you Dario thank you Fabian this has been a great conversation uh Jacob I'm gonna turn it back over to you uh to wrap us up yeah thank you much so much Federico thanks again for our panelists here as well and thank you to the audience for participating and sending in your questions and make for a much better conversation so appreciate your time and attention as well um with that said just wanted to mention a couple other upcoming programs we have so if you enjoyed this webinar we hope you join us at some of these as well so we have an upcoming technology Summit focused on Quantum for manufacturing and then a couple other events coming up here as well partnership with Dow and ey talking through sustainability in manufacturing and then finally our annual annual member Summit uh combined with a little special event this year for mxds 10e anniversary so we hope you'll join us for some of these events you can visit mxd usa.org events to to uh register for those and then finally just uh keep up with us on our social media platform so Twitter um Instagram and Facebook as well um will help you to uh to stay in touch on those as well but um that said just again wanted to thank you for joining the webinar and thanks again to our panelists and hope you enjoyed the rest of your day thank you thank you bye-bye

2024-10-07 06:14

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