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SUNY Farmingdale ​[Music] hi I'm columnist and I'm the industry solution director for manufacturing for Microsoft's cloud and enterprise team and I really want to talk to you today about how advanced analytics is at the core of the digital transformation that's happening in manufacturing if we really look at what is happening in manufacturing we're moving from kind of traditional push linear supply chains to really putting the customer and a whole new generation of smart products at the core of what is often been called the fourth industrial revolution in manufacturing and if I kind of met it out there's a lot of words on the slide here and we kind of built out the whole picture but it's really about moving from selling products to really selling products as a service and so almost every manufacturer that I'm talking to is in some shape or form try to work out how do they monetize service and they monetize the new insights that they're getting from deploying smart products usually powered by the Internet of Things or the industrial Internet of Things as it's often called and that leads us kind of into the role that advanced analytics has to play in this whole transformation that's going on so not only is product as a service at the core of this digital transformation and often people will talk about the servitors ation of manufacturing another term that you may hear if we look at this whole transformation it's driven by many of our needs to get these custom products and deliver a custom service increase our margins but the guys that really have to deliver on all of this are the core guys in manufacturing so now if you look at the roller advanced analytics is playing in this transformation and you probably see where I'm headed already we've kind of got all of this change that's being forced on manufacturing they're trying to get new customer insights from those smart products that they've got out there they're trying to ensure that their workforce and the ground in the digital factory are given as much insight as possible into what they need to make and how they need to make it and so they try to do all of this with what is still a growing skills gap in manufacturing and this is where advanced analytics and certainly our our approach microsoft specific approach to advanced advanced analytics can really help and we've kind of got two things that we're trying to do to make sure that the skills gap in manufacturing and the fact that data scientists are in huge demand that we can basically address this need to apply advanced analytics technology to address this digital transformation in manufacturing with a couple of different approaches on the left hand side of the slide here we're looking at the delivery of what we call a solution template so we have Cortana intelligence solution templates that give you a fast start you don't have to be a an expert in data science to leverage these but they get you up and running let you get a proof of concept going very quickly and one of those examples is kind of in quality assurance and i'll i'll demonstrate that to you shortly another key area is divided for crafting and upon forecasting is important because we kind of need to give manufacturing as much notice as possible of what they need to make and and when what I'll also talk about is some finish solutions that are partners are delivering we're pretty much that's delivered as a a nap and I'm going to highlight a couple of examples from wipro using advanced analytics for asset failure analysis and the hitachi who are doing something with IOT predictive analytics for connected field service scenarios so taking a quick look at the Quality Assurance solution template this kind of quick start for you two to go after Quality Assurance problems in manufacturing what we've done here is basically provide a solution that really lets you get a the root cause analysis of quality problems in a complex manufacturing process where you may have multiple steps in manufacturing the product may pass your traditional tests at each step and yet fail at the end or actually fail when it gets to the customer so actually getting to the root cause analysis of the problem and what is causing that problem each step of manufacturing whether that's machine tolerances whether it's the operating conditions of the machine and correlating that with quality data is a technique that we've used with cable and I'm going to demonstrate that solution to you in more depth okay let's take a quick look at the Quality Assurance solution template for many of factoring we just click on try it now you'll see a power bi dashboard here I'm just going to click down on the left hand side just to click into the introduction before I show you and this kind of tells you a little bit about the solution template itself it's really allowing us to take a deep dive into a multi-step manufacturing process and actually build a model from the quality results that's taken from each step as well as final testing and even failures and colleague results we may get after its left manufacturing so returns and actually put together a model that allows us to predict failures in a more amenable way and as I discussed earlier that means we can kind of predict a failure maybe it's step two in this five-step process that we're showing here this happens to be based on some work that we did with jae bok the third largest contract manufacturer in the world if you look at the actual solution template we are simulating five steps in a process similar to tables and at each one we've kind of put together all the pieces that you need to basically be able to do that kind of


correlation of the iot data that you are getting from the floor the quality desk test data that you're getting from the floor and combine that to build a model that actually predicts when a party is going to fail so then you can stop a part going from step 2 2 step 3 which may be a very important step in the case of table that is when they start to add the expensive components onto the board so that's something you can't reverse you can't rework so if you know that the board has already failed at step two you kind of want to be able to reject that and so we've put together a simulator here not a very good production in this particular case because if we really had this kind of failure rate all the way through we'd be getting something like three to five percent managing to get to step five but for the purposes of you to basically be able to simulate and then start to plug in your own IOT data and get a solution up and running very quickly to kind of do this quality assurance in manufacturing and avoid those kind of expensive scrap or rework situations this is a really good representative solution for manufacturing ok let's look at demand forecasting and the solution template here this particular case what we're doing is really taking a look at how we can actually make life easier for manufacturers again by doing a better job of forecasting so as I mentioned there's a lot of change that is being forced on manufacturing to switch between products because of the proliferation of products or skews that they're expected to make in kind of the new assemble to order configure-to-order or even engineer to order that customers are demanding so what we're doing here is really allowing you to look at the prices you should be charging for the products that you're making but also start to actually model how you could shape demand and so how could you actually smooth out the number of change overs potentially that you have to do back in manufacturing or maybe not getting the right answer for manufacturing but doing the right things of the business it might be how do i optimize the the product mix the right mix of products that's going to give me the maximum profit and so this is obviously a common problem doesn't just apply to manufacturing applies to consumer goods in other areas as well but it has particular relevance to manufacturing so I do want to highlight this one as well in terms of being able to smooth out some of that and demand volatility that is kind of forcing its way all the way back through the supply chain two core manufacturing now I want to highlight a couple of Finnish solutions from partners that are really helping us address both the examples i'm going to show in the next couple of slides are kind of in me the fax server ties a shin area where people are trying to drive improved field service of products that they've already sold in this case wipro with their asset failure analysis are really providing the complete tool set that you need to really get at the root cause analysis of failures and so they're using a combination of logistic regression and artificial neural networks to kind of get at the root cause of failures of complex assets and so they can get right down to you know what are the part failures that may be causing the problem and of course that that means they can either do a better job of getting those parts at the right location and the supply chain for where those failures are are going to occur or hopefully do something more proactive right in terms of either going out and proactively maintaining those products for your customers or pushing that back into the design process or changing a supplier if it's a particular suppliers problems so if this application really gives you that ability to to do all of that effort failure analysis and of course then you can feed that into business processes the next example I'm going to look at is with hitoshi so hitoshi are doing something similar albeit very focused on i-80 enabled products in the field and so with their finish solution what they're doing is providing everything you need to intelligently predict the failure before they occur so they are augmenting a lot of the things that we do with dynamics 365 connected field service but they're expanding on the ability to go beyond remote monitoring into theirs predictive maintenance and so they're actually doing also some former root cause analysis and a couple of others I don't have slides on but I kind of want to call out an interesting example would be work that's being done by blue granite on product mix optimization they've done a lot more work with chemical companies and kind of doing clustering of all the different products that can be made on their facilities and optimizing what that product mix should be either to help production or to actually increase profitability they're also doing some creative things around applying that to say what products could I make on similar facilities so I wanted to call out some work that blue granite is doing on solutions and then another one that's very public and you can go out and search on on bing or google for is really buy new signature and work they've done with her she's on their Twizzlers and that one gets back to that manufacturing core where by building a multivariate model on the tanks that hold all of that licorice that goes into Twizzlers they've been able to basically control or advise on the control of 22 different senses to make sure that they produce the right specification of that twizzler if you make it too fat as in those it's one percent heavier you're giving away a lot of money in terms of what your packaging so by actually getting tighter control over those 222 sensors they can reduce the amount of product giveaway and so that's a another example of really how advanced analytics is is being applied in new ways in manufacturing and then I want to take a few minutes to say you know what's different about Microsoft's approach what I think as you've heard we're kind of focused on industry solutions and either working with partners on finish solutions or providing the accelerators for common business scenarios that we're seeing and we're also trying to


deliver it in a fashion that means you don't have to be have a whole team of data scientists you could be a small business large business it doesn't really matter you can actually spin up these capabilities on Azure and actually get to value very quickly so fine Stanley certainly isn't you to manufacturing many of us have had experience in operations research and we done six sigma quality for years and we've done multivariate modeling for years and so many of us have libraries that we've built up particularly if we have complex assets then we may have built a libraries in our or Python or other languages and our intention is that you can still leverage that you can leverage that with these solutions and take that investment forward and expand and address the significant skills gap we have in manufacturing but also in recruiting data scientists and it's easy to get started right just go to the Cortana intelligence gallery to find out more about the manufacturing vertical solution templates i showed you quality assurance and demand forecasting and we keep adding to that library i also what points you at if you really want SAT solutions that focused industry solutions for manufacturing and our other verticals then i also want to point you at apps or stop microsoft com or you can just put in app source com and you'll kind of find those finished solutions they're quick and easy many of them with trials that you can spin up just as quickly as I showed you on the Quality Assurance solution template well I hope you're as passionate as I am about the opportunity to leverage advanced analytics empowering the digital transformation on manufacturing go try these solutions out today [Music] you [Music] New Rochelle campus.

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DALLAS CONSIDERING CITE AND RELEASE PILOT PROGRAM FOR MARIJUANA  
DALLAS CONSIDERING CITE AND RELEASE PILOT PROGRAM FOR MARIJUANA  
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