![\"Bill](\"https:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/19\/2019\/11\/bill-davis.jpg\")
A substantial\ncontributor to this series is our resident expert, Bill Davis, who is the Director of Industrial Machinery and Heavy Equipment Solutions at Siemens\nDigital Industries Software<\/em>. Bill\u2019s expertise in this industry\nexpands over 30 years, with 20 years as an engineer.<\/p>\n\n\n\n Feel free to listen<\/a> to this podcast in the first blog of this series, or read the transcript excerpt, below:<\/p>\n\n\n\n Bill Butcher:<\/em><\/strong> Welcome to\nSiemens Digital Industry Software podcast series on Advanced Machine\nEngineering, brought to you by the Siemens Thought Leadership team! Bill, can\nyou give us some information on your background?<\/p>\n\n\n\n Bill Davis:<\/strong> Thanks for having me on,\nit’s a pleasure to be speaking with you. A little bit about my background \u2013 I\nam the Director of the Industrial Machinery and Heavy Equipment Solution area,\nwhich means I take care of the industrial machinery customers and heavy\nequipment customers in that space. Our software is uniquely positioned with\ncapabilities to take advantage of the problems and give our customers solutions\nthat they can’t otherwise achieve. We also help those customers by assisting\nthe product improvement process, so the next generation of software is even\nbetter than today’s version. This is what brought me to Siemens, with my\nexperience in the industrial machinery and heavy equipment area. Predominantly\nspeaking, my background is in automation, converting and packaging machinery. I\nworked at several different companies over the course of my 30 years in\nengineering and management positions, as well as both engineering and\noperations \u2013 I’ve seen both sides of the business, and I’ve also had the\npleasure to work with several very large mining machinery companies in my area,\nwhere they have unique challenges. However, today we’ll be talking primarily\nabout industrial machinery, and that experience has also helped shape how I\nhelp our customers and their go-to-market strategy. And realistically,\nthroughout all my experience, I’ve been the person who has been leading the\ncharge on bringing those companies forward on their digitalization journey,\nwhether it’s CAD, PLM, ERP integration, solution or simulation. It has been a\ngreat journey!<\/p>\n\n\n\n Bill\nButcher:<\/em><\/strong> Well, that’s excellent! I think our listeners are really going\nto enjoy the wealth of that experience that you just referenced. And before we\nlook ahead, I just want to revisit some of that experience. Let’s look back at\nthe last ten years. There have been so many changes in the machinery industry,\nbut what would you cite, from your perspective, would be one or two significant\ntechnology changes that have shaped the industry in the past decade?<\/p>\n\n\n\n Bill Davis:<\/em><\/strong>\nThat’s a good question! There certainly has been a lot of change. The tools\nthat we use for engineering are certainly different, they’ve become much more\ncapable than they were ten years ago. There’s certainly changes in the\nindustry, as well, so to divide this up into two different parts: on the CAD\/CAM\nand simulation capability, there’s substantial core technology around embedding\nsimulation into the design process \u2013 via a multi-discipline domain, finite\nelement analysis, computational fluid dynamics, vibration and harshness. Also, it\u2019s\na more collaborative multi-discipline type of design, like the so-called, \u201cGenerative\nDesign Movement” where instead of designing first and then simulating to\nsee where you had problems with the design, you’re using the loads and the\nconstraints that are in the design to help shape the net material that you\nactually need in that part, which helps drive what your design happens to be,\neven if you’re not using some of our technologies around additive\nmanufacturing. Realistically, there is so much electrification in the product that\nit’s difficult and challenging to simulate everything in the machine to arrive\nat what that final product is, without having some way of validating the PLC\ncode and the automation code that’s in it. So, those are big changes from the market\nperspective as well as the solution products, if you will.<\/p>\n\n\n\n Bill\nButcher:<\/em><\/strong> Those are great examples of the evolution, and it seems like\nmost of that is focused around technology. Would you say technology has been\nthe biggest catalyst for change in the machinery industry? Or are there other\nfactors that are creating the need for advanced technology solutions as well?<\/p>\n\n\n\n Bill\nDavis:<\/em><\/strong> The new technologies that are out there in terms of the\ncapabilities for design engineers are certainly pronounced. We continue to push\nthe envelope on providing a more robust toolset for design engineers and\nautomation engineers. However, I think one of the things that’s important for\nour customers and listeners is to understand this whole idea of consumer-driven\ncustomization. We all want our own product – if you’ve gone shopping on Amazon,\nyou can get what you want when you want it – and so what we’re seeing is that\nin the derivative type of markets where if I build a machine that makes a\nproduct that’s used in other products, for example – cell phone manufacturing\nis a perfect example – the lifespans are getting shorter for those products.\nYou need to be able to ramp up very quickly with a machine that’s going to make\nthat next version of cell phone. And, there are more variants in terms of the\ncell phone capability. So, the machinery is really impacted by those things \u2013 by\nthe consumers and what they’re looking for in a new product and how short their\nattention span is, as far as needing something new on a repetitive basis, so\nit’s really changing how dynamic and how adaptive that machinery has to be, to\ntake advantage of that or to react to.<\/p>\n\n\n\n Also, when\nwe look at what’s going on in manufacturing, this whole movement toward machine\nlearning and artificial intelligence, and highly adaptive equipment \u2013 where\nit’s running itself and, as the OEM \u2013 we\u2019re able to get more information from\nan analytics capability of what’s happening on the shop floor in a richer\nfidelity. This allows the machine to make some smart decisions, while giving us\nthe broader capability around it. All of this is driving toward new business\nmodels, where the machine builder and OEM are finding that it’s more\nadvantageous for them to be a partner with their customer and provide\nproduction as a service, which of course increases sustainability of that\nmachine and keeps it in service longer to help drive costs down for the machine\nbuilder and for the machinery consumer.<\/p>\n\n\n\n Bill\nButcher:<\/em><\/strong> Then what you’re saying is technology continues to advance and\nincrease expectations on customization from consumers and continues to increase\ncomplexity and tests the limits of those advancements. On another topic, the\ndigital twin is one of the buzzwords that we hear very often these days. Can\nyou elaborate on the concept of digitalization, and more specifically, the\ndigital twin in the context of industrial machinery?<\/p>\n\n\n\n Bill\nDavis:<\/em><\/strong> I don’t think a day goes by in my own inbox where I don’t see an\nemail or somebody putting out a piece of material on the digital twin, so I\ncompletely agree with you, it’s thrown about quite often, so it’s good to have\nthis kind of definition. What we found is that when we look at some of our\ncompetitors, their definition of the digital twin matches what their capability\nis, so you get this limited definition. For us, it really is a holistic\nrepresentation of the physical machine, its performance and even the recipe for\nhow it’s manufactured. So, it corresponds to everything mechanical, electrical,\nhydraulic, fluids, pneumatics, design domains, performance, simulation and the\nautomation code; and then extending it into manufacturing and service life. So,\nit takes the machine from the point of origination all the way through to it\ngetting recycled.<\/p>\n\n\n\n The trends\nare showing that machines are getting more complex and you really need to have traceability\nof the serial number of the machine from the point that you release it from\nengineering through manufacturing and into the service life. So, being able to\nunderstand all those different variants in the machine is really an important\npoint as to why you need to have a digital twin of each machine that you\nmanufacture. There’s a blurring of lines between mechanical, electrical and\nsoftware, so you can’t just have a digital twin of the mechanical, without\nrepresenting all the other domains as well. Finally, you need to have a\ncomprehensive digital twin to drive value because so much of the machinery is\nbecoming driven by software and electrical. Fortunately, in our space, we can\nrepresent the software that helps our customers manage and maintain the most\ncomprehensive digital twin.<\/p>\n\n\n\n Bill\nButcher:<\/em><\/strong> We now have the technology and tools in place to really drive\nchange and exponentially increase efficiency to help create true competitive\nadvantages for machine builders and suppliers by delivering machines into the\nmarket faster. You have termed the approach, “Advanced Machine\nEngineering”. Can you help the listeners understand what exactly is\nAdvanced Machine Engineering, and what makes it unique from any other\napproaches machine builders and their suppliers are using today?<\/p>\n\n\n\n Bill\nDavis:<\/em><\/strong> Advanced Machine Engineering is a term that we coined several\nyears ago, and it\u2019s high-level. It marries the development of the digital twin\nand the collaboration of those domains for developing the machine into a\ncomplete solution suite. We’re going to be discussing multidisciplinary design\n– the mechanical, electrical and fluidics – and why that’s important to have a\nsingle source of truth in the design to be able to address the back and forth\nbetween the silos that often exist. Secondly, because of all the software and\nthe automation code that’s being developed, you really need to have a way of performing\nvirtual machine simulation and testing out that PLC code in the virtual world,\nas opposed to building it out and then testing it. So, you’ve got to be able to\nprove out that the machine can do what it’s designed to do before we start it\nup on the floor and possibly break things.<\/p>\n\n\n\n Lastly, if you roll it all together in the context of the configuration of these different machines and the fact that whether you subscribe to a platform engineering model, or you’re building a one-off every time, you have various bills of material for diverse needs such as mechanical, electrical and fluids for different domains – and you need to express that in a bill of material form so you can actually produce it. With all of the different configurations of variants that you could possibly build for a customer, you have to have some way of managing it all, and that chaos is one of the biggest sources, from an engineering management perspective, that’s one of the biggest sources of waste – is looking for the right products, looking for the right equipment and having the right bill of material. It’s far more expensive to do the design when you don’t know the design from the various domains, so you need to consider when it comes to product improvement. This is all part of what we consider Advanced Machine Engineering as part of the solution.<\/p>\n\n\n\n Listen\nto podcast01<\/a>, podcast02<\/a>,\npodcast03<\/a> and podcast04<\/a> from this series via our Thought Leadership blogs.<\/p>\n\n\n\n Also, you can access\nthe entire podcast series via Apple<\/a>, Stitcher<\/a>, Spotify<\/a>, Castbox<\/a>, TuneIn<\/a> or Google<\/a>.<\/p>\n\n\n\n To improve the speed and efficiency of your machine design process, watch our Advanced Machine Engineering \u2013 Start your digital transformation journey today<\/em><\/a> webinar.<\/p>\n\n\n\n About our expert:<\/strong> This blog is an excerpt from the transcript, showing the first in a series of four podcasts on advanced machine engineering<\/em>, a part of the Xcelerator suite of products with Siemens Digital Industries Software \u2013 where today meets tomorrow.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":" The scenery of industrial machinery in manufacturing is seeing a pioneering renovation of technological progressions. 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\nBill Davis<\/strong><\/em> is the\nacting Industrial Machinery and Heavy Equipment Industry leader for Siemens\nDigital Industries Software. His experience and insights have been acquired\nfrom a career spanning 30 years in engineering and operations management with\nmachinery and heavy equipment companies. Bill holds a master\u2019s degree in\nBusiness Administration from Marquette University, with a concentration in\nOperations Management and Strategic Marketing<\/a>, as well as a\nBachelor of Science degree in Mechanical Engineering from Milwaukee School<\/a> of\nEngineering.<\/em><\/p>\n\n\n\n