"The ROI of PackML for IIoT" | Innovation Stage at Pack Expo East 2020

TAKE OUR CRASH COURSE ON PACKML FOR IIOT In under 10 minutes our very own Spencer Cramer will explain how PackML shortens engineering and commissioning times, improves quality and helps you create reusable code. Learn how PackML enables monitoring of KPIs and efficiency at — the plant and enterprise level. PackML's standardized machine data and benefits for packaging line is a winner, ROI for OEM's and manufacturers. But did you know that it can go into many other industries – machining, plastics and injection molding machines and others? Video Transcript: I always like to start a presentation like this one with some big statement coming from an authority in this case I'm using Bain Capital Bain did a management report a little bit more than a year ago which was nicely written up by a well-known tech blogger named Louis Columbus Louis was picked up by Forbes magazine and this report was published and what Louis says is that the report indicates that the industrial Internet of Things will be a two hundred billion dollar market by 2021 in 2021 that's like next year so it's not a two hundred billion dollar market today that means is we're going through a big digital transformation now and things are changing so when we think about our customers we need to look at it through the lens of time this is tenure spread from the same article which is showing us here in 2020 there's about the light gray or people who are just talking about IOT right thinking about it yeah I saw it in the show somewhere the medium gray are people who are planning implementation or doing pilots so there is now you can see this being 20/20 you can see that there is already now a majority of companies are either planning or implementing IOT solutions and the dark at the bottom is extensive implementation those are the companies that have the company-wide IOT program it's already in the works it's being done and people are gaining benefits from it. so you can see here in 2020 we're like at 15% of the market are doing extensive implementation but by 2022 that number is going to be over 20% if we like more like 22% and by 2027 looking further down the road more than half the companies will be there so I I bring this out for you as a challenge to think that this is something that's very real this is not if we're not talking about a future vision we're talking about things that people are doing today and that are they're gaining real benefits from so what does pack ml have to do with this well there was an article that came out by McKinsey Global Institute a couple of years ago and I'd love to quote it because they they see the economic benefit which is bigger than the market size the economic benefit of the industrial internet of things in the manufacturing world will be in in more than a trillion dollars per year by 2027 more than a trillion dollars but in that same article where they talk about a trillion dollars of economic benefit they say that to realize that benefit interoperability is key they say that from their studies interoperability will be required to unleash the full value and if it's not there we could be looking at a discount of as much as 40% so the stakes are high defined interoperability that can be used to describe the the the states of these machines online through the through the industrial Internet of Things so what would be a great way to describe the states of machines PackML this standard is the ideal type of data operable interoperability standard that we need in order to realize the value of this industrial Internet of Things and increase ROI. pack ml has this notion of a packet tag way of describing the mode or the operation of the machine in a way that one machine can say it and the other machine can understand it so they can have a conversation where they're speaking the same language and that becomes really important when you organize machines together into a line so let's look a little bit deeper into that you see here pack ml is a way of providing key performance indicators. KPIs enable proactive service analysis and response, showcasing how PackML can increase ROI.  the way it works is that the Machine PLC if it's programmed along the lines of using PACKml if you have PAC tags they can be brought out to a secure network where that secure network uses Ethernet and OPC UA and the PAC tags to collect the data locally on the shop floor and then if there's an internet connection available to securely transmit data up into the cloud once that data gets into the cloud it can be analyzed and those pack tags which talk about things like machine executes suspend held those pack tags become the basis of computing the OEE of the machine so the remote monitoring cloud which gathers all of that pack tag information performs the analytics and then disseminates that information through webpages dashboards and reports let's look at an example so if that machine owner has a fleet of machines in this case three identical machines all from the same OEM that owner might want to know which one runs best and which one doesn't so by having these pack tags come up into the cloud we can then highlight for the machine owner which machines need more careful attention and come up with reports that would indicate that so that they can make decisions but if your machine builder puts every machine that they've ever made onto a secure internet system where your data is anonymized so we don't know who it's coming from and we don't know what you're doing but we know how well you're running if you create a big system of all those machines the machine builder gets put into a position where they can provide incredible value to their customers and that's happening today this is this is what companies are doing to take insights and convert those insights to action companies are taking for example fleets of machines where they have a standardized machine and for every machine that they ship they know the OEE of the machine they know by country by customer by factory what those are and they can go to those come the steamers and say hey we couldn't help but notice that your three machines from us are in the bottom quartile we can help you make them better let us engage with you and get you the parts and the training and the support that you need so that you're operating in the top quartile those become business models that are very consultative and bring a lot of value from the OEM to the to the to the to their customer base another return on investment is just having that productivity information can can enable organizations to follow best practices the pareto is a very good tool for figuring out in the in that confused you know world of manufacturing what should I be spending my precious time and money on to make my operation better having the PAC tags be the route of the machine monitoring that you can then generate those Pareto's you can actually help your customers see what they should be doing or give the machine operators an iPhone app that shows the productivity of their machine so on their shift is over and they're driving home they can see how they did. that simple thing has proven to us over and over again that you will get a 5% improvement of machine productivity without any additional capital equipment put onto the machine let's put it another way ROI wise if you have a shop floor of 20 machines and you improve all machines by 5% that's like getting one free machine so there's a real ROI to that quick summary PackML in the walls okay it is a standalone it's a winner it has its own ROI you simplify the Machine operations you can train operators quicker and easier you can do faster start ups your software code becomes more robust and more transportable from one machine to the next and that makes the machines easier to troubleshoot you get consistent operation and you can do performance measurement in the walls those are all winners that alone is an ROI for POC ml on a machine but then if you look at it from the cloud point of view we have standardized data now we can do big data we can get a global install base with that global install base of big data coming in we can do deep analytics we can do modeling we can do digital twinning we can then benchmark machines to standards we can identify who's not conforming to those standards we can alert the customers we can do predictive services around those and we can help our customers optimize their machines so in summary pack ml whether it's the walls are in the cloud pack ml enables potential savings. the machine builders know that if they put pack ml on the machine it will work in a line more easily and a manufacturing company who's buying that machine is going to appreciate the OEM delivering a machine with PackML, with opportunities for increased ROI. and in fact some very large CPG companies actually spec that the machine must have pack ml so it's becoming a more and more important standard for the machine builder okay thank you