The products of modern engineering enterprises are characterized by high complexity and precision. Furthermore, to produce competitive products, it is required to provide a short time for the design and introduction of new products as well as the modifications of products already produced. Such a problem cannot be solved without the use of modern software both for design and technological preparation of production and for engineering analysis.
On this episode of the Next Generation Design Podcast, our host Jennifer Piper is joined by Dr. Sam Anand, a professor and industry expert with 35 years of experience in advanced and digital manufacturing. Sam is also the director of the Siemens Simulation Center and co-director of the Industry 4.0 Institute at the University of Cincinnati.
In this episode, he will help us understand the impact of the Siemens Simulation Technology Center on engineering education and research at the University. You will get to learn about Sam’s expertise and experiences in teaching digital manufacturing and design to students at the university level. And you will also hear more about using Siemens software and tools in the curriculum and the focus on solving real industrial problems through simulation.
What You’ll Learn in this Episode:
- How Dr. Sam Anand started his career in engineering
- The impact of the Siemens Simulation Technology Center on engineering education and research at the University of Cincinnati
- How the Siemens Simulation Technology Center is being utilized in teaching and research at the University of Cincinnati
- The key concepts emphasized in the courses that use Siemens’ NX software, and how they are taught to the students
- Other government and industrial projects that utilize Siemens’ NX software to develop digital manufacturing and design
You need to engage the class, you need to make it relevant to what they’re learning so they understand the purpose of what they’re learning and what its application is. So the Siemens software and the tools exactly fits in that mode.Dr. Sam Anand, Siemens Digital Industries Software
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Sam Anand: The days of a professor writing on a whiteboard equations and regurgitating is gone. You need to engage the class. You need to make it relevant to what they’re learning, so they understand the purpose of what they’re learning and what its application is. We not only teach the basics, but we give them real-life parts or examples in real life and ask them to analyze them using Siemens software.
Jennifer Piper: Welcome to the Next Generation Design podcast. I’m your host, Jennifer Piper. Today, I’m talking to Sam Anand, professor of mechanical engineering at the University of Cincinnati, about his role as director of the Siemens Simulation Center, how his department is able to utilize NX in their curriculum, and the rapidly-evolving world of computer-aided design. Before we begin, let’s meet today’s guest. Sam, can you tell our listeners a bit about your role at the University of Cincinnati?
Sam Anand: I’m a professor of Mechanical Engineering. I’ve been here for 32 years. I work in the area of advanced manufacturing, digital manufacturing, intelligent design, and all aspects of IoT, AR, VR, and MR. I am the director of the Siemens Simulation Center at the University of Cincinnati. I’m also the co-director of the Industry 4.0/5.0 Institute at the University of Cincinnati which is campus-wide. I’ve had a breadth of experience with multiple industries. When I say “industries,” I am talking about research contracts with the university, with Raytheon, Honeywell, P&G, GE, Ford Motor, a whole range of those industries, Faurecia, and so on. And we have used several pieces of Siemens tools in these contracts and brought them back to the classroom for student experience. So, that’s a quick overview. So, about 35 years of experience in advanced manufacturing and digital manufacturing.
Jennifer Piper: Welcome to the show and thank you for joining us today. I’m curious, how did you start your career in engineering? What first attracted you to the field?
Sam Anand: I came to this country in 1984 after I got my master’s in Mechanical Engineering from India, and I came to Penn State, that is where I stayed for about six years and I got my master’s and a doctorate in industrial and manufacturing engineering. And then I moved over to the University of Cincinnati in 1990, and that’s where I’ve been since I started. Engineering has always been a passion because it allows us to be creative in solving problems, particularly the gaps in the industry, and coming up with new, organic kind of knowledge to solve those problems, either in design or in manufacturing. My passion was manufacturing because I see products and goods made, and we know that is a driver of most economies eventually. So, that is where I wanted to put my entire interest and stress here. So, in a nutshell, the creativity and problem-solving capabilities of engineering are what attracted me. And of course, I haven’t left this field, so that definitely emphasizes my interest in that area.
Jennifer Piper: Was teaching always your end goal?
Sam Anand: No, not at all. I was interested in engineering. So, when I went to Penn State, obviously, I was interested in getting a master’s and a doctorate. But I initially wanted to work in the industry, but the kind of training and research that I did at Penn State and the basic exposure to different professors from different universities, who I met at conferences and other kinds of scenarios, gave me the impetus to actually become a professor because mingling, teaching with research, and problem-solving puts you on a sweet spot where you can teach people, you can also do research, and also interact with industry and bring that back to the classroom. That was what I liked, and that’s what made me become a professor.
Jennifer Piper: And what kind of courses do you teach? What are you teaching this current semester?
Sam Anand: I teach manufacturing. So, this semester, I’m teaching a manufacturing process course. This is an undergraduate course, where we cover the gamut of all the manufacturing processes. Of course, we introduced Siemens software in every part of the curriculum of that course as we have done throughout the curriculum in mechanical engineering. Right now about 1400 students are exposed to Siemens software in various courses. I teach that course in the fall. And typically in spring, I teach a graduate course, which is Computational Methods in Additive Manufacturing, where we use some Siemens tools and our own apps that we created through Siemens tools as part of the classroom experience. In all these courses, the mainstay is to bring real-life industrial problems with simulation to train the students for the next generation of engineers in this digital world and make sure they hit the ground running. Also, understand that solving real problems with some industry interaction brings you closer to what you would be doing later on in life and that provides an extra layer of training, and that is what we strive toward doing.
Jennifer Piper: Which of those courses is your favorite to teach?
Sam Anand: Two things. One is predictive modeling — so, how to model the process and predict how the distortions and the final part quality is going to come out using digital simulation is a big deal. It is a very complex process, particularly when you have heat input. Also, looking at intelligent design: How do you design a part in such a way from the get-go at the design stage, you sort of foresee what problems are going to occur downstream, and then fix them at the design stage, saving a lot of costs and effort here. So, we teach a lot of analysis of the part on a layer-by-layer method using complex computational geometry and math tools for them to analyze and predict what problems are going to occur downstream and then use that information. We also teach some examples of using IIoT (Industrial Internet of Things) to gather machine information and bring it to the cloud using MindSphere, and then basically use that information to correct the process parameters in real-time, on the fly, so as to bring about a correct defect-free part. It’s a multi-pronged approach, where we fix the design, we also look at modifying process parameters on the fly based on sensor input, and how students can learn, how those sensor inputs play a part in changing the process parameters and selecting the optimal ones.
Jennifer Piper: When you’re doing the additive manufacturing portion of the curriculum, are you guys also having the students do the actual 3D printing and doing the final product? What does the end result look like?
Sam Anand: Yes, some of it, we do; some of it, it’s more computational. So, the good news is, nowadays, almost everything can be simulated with a digital twin model that we help the students create. So, the idea is, instead of wasting time with multiple iterations of design, you simulate, and then verify and reiterate and simulate again to get to the final product. So, that is faster, time-saving, and gives you a lot more options, that’s what we train at. Yes, we do some printing, but the idea is not to train students in the art of printing, but on the math and physics behind the entire process so they understand the fundamentals, and also connect them with simulation and predictive modeling software with all the new tools and AI and machine learning so they can bring that to bear on making a good product here, what we call as the first part right with no defects, so that we save costs, save energy, save material, and makes everybody happy.
Jennifer Piper: Well, it sounds like you’re all having a lot of fun with that. What types of products are they designing?
Sam Anand: So, it’s basically a range of products, it could be for aircraft parts, it could be for medical devices. And depending on the type of parts, the material is different, the design is different, the nuances of the process parameters are different, and how to make those things. So, a lot of concentration on metal parts, which is a lot more complicated, particularly metal powder additive manufacturing, which is what GE, Raytheon, Boeing, and all those folks do for lightweighting parts. So, we focus on lightweighting complex designs that can be tailored and made for those kinds of situations. So, it’s a range of industries, from aircraft to auto to medical, we focus on those industries on the cutting edge areas here. But the principles are the same, whether you take the path to GE or to medical application, we teach the fundamentals. And from there on, you can branch out and pretty much make any of these parts here. So, it’s an evolving field, additive manufacturing, it is changing by the day here — new things are coming out, so we try to keep up as much as possible.
Jennifer Piper: This industry does change incredibly quickly, so it’s great that you already have your students thinking on their feet! So Sam, obviously much of your coursework involves computer-aided design. I’m wondering when you were first introduced to that system.
Sam Anand: Oh, that was a while ago. For my work at Penn State, I was using I-DEAS, which is a precursor to NX, and all the other software, I-DEAS, was made by, of course, SDRC at that time, which eventually morphed into Siemens. So, that was my PhD thesis — part of it used I-DEAS. Since then, I’ve taught courses on CAD or CAD and manufacturing for 30 years and we are evolved to different pieces of software. And of course, we added NX. I think NX is a pinnacle of a top-notch software that can bring it all together be it design, manufacturing, and analysis. So, it helps us train the students in cutting-edge software used by Fortune 100 industries, GE, Boeing, all the big companies here, so there’ll be trained students in that software here. NX is top-notch software, so that’s why we picked it.
Jennifer Piper: Well we absolutely love to hear that. Is there anything in particular that you like about using NX?
Sam Anand: I think it is the range of applications that you can choose from. And the interface is so friendly and smooth, once you know how to operate it, it naturally leads you from one step to another, making it logical to work on it. That’s the best part of the software here. And each version of the software brings new tools and new methods, which is great. It’s like buying iPhone 14, it looks the same but it’s got some new features. That’s exactly what NX does when it moves up every edition.
Jennifer Piper: Have you found it challenging to keep up the pace with the updated functionality? Or do you feel like you’re able to incorporate that new feature, solution, or add-on module as part of the curriculum?
Sam Anand: The interface sometimes is different. But if you have used the previous versions, it doesn’t take a long time to learn. The same analogy as the Apple iPhone, there are new features that pop up, but if you are a user of Apple iOS, it shouldn’t take you more than a few minutes to figure things out there and so on. So, it is logically a sequence, the ramp-up is not dramatic. It is not to the point where somebody says, “Whoa! I don’t even know what the heck it is.” It’s logical. So, I don’t think it’s really a concern. It’s more of a step up that people understand when you step up things change a little bit.
Jennifer Piper: As you said in your introduction, you’re director of the Siemens Simulation Technology Center at the University of Cincinnati. Can you tell our listeners a bit more about that?
Sam Anand: Yeah, the Siemens Simulation Technology Center was formed in 2016 with help from Siemens, a generous gift from Siemens. It had multiple goals, definitely to train students in Siemens software, the suite of Siemens software, in all areas of simulation and predictive modeling, infuse that information into classrooms so that students are seamlessly working on these kinds of software while they learn the fundamentals, and also include information about using the software in industry products and contracts, and bring that information back to the classroom for real-life student learning. And that is the purpose of the Siemens Center, and also creating packets of learning using Siemens software that we can post on the Siemens Center website that can be replicable, not only by professors at the University of Cincinnati, but by other universities around the world. So, we serve as a repository of all those apps and small packets or modules that anybody can use in their courses to make it successful. They’re all Siemens-centric packets of software there. So, it’s been around for about six years. Right now it is evolving and morphing, where we are integrating Siemens Center activities into the Industry 4.0/5.0 Institute that was newly formed, I’m the co-director. And the Digital Futures, that’s a building at the University of Cincinnati, it’s an 180,000-square-foot building for interdisciplinary research. We are infusing Siemens, Siemens activities, and Siemens software into those activities as well, and spreading the knowledge and the information beyond the classroom.
Jennifer Piper: And how has the Siemens partnership impacted engineering in general at the University of Cincinnati?
Sam Anand: Oh, tremendously. I think the students are learning a whole suite of software not only NX. We teach some parts of Simcenter 3D, STAR-CCM+, in heat transfer courses. We teach MindSphere and Mendix in our IoT, AR, VR courses. And then all elements of Simcenter 3D that we are talking about, and the Xcelerator package, that is the new push right now, we’re teaching all elements. So, we have integrated Siemens software into more than 20-25 courses, and about 1400 to 1500 students are impacted, where they see the software used in their homeworks, projects, demos, and so on and so forth. The students come out with a knowledge of the software and how to use it. And clearly, knowing that fundamentals along with the knowledge of using the software, which is what they’re going to see in the industry, helps them seamlessly transition to the industry. And then the use of Siemens software in industries, contracts, and research that brings a different level here of students’ experience. It’s been highly impactful and we are grateful to Siemens.
Jennifer Piper: That’s an incredible number of students to be able to receive that sort of education before even joining the workforce. What do you think has been the greatest benefit of this partnership for the students?
Sam Anand: We bring in Siemens experts now and then to actually interact in the classroom in the form of lectures and presentations. So, that’s an added element to this, they see that. Wherever Siemens software is used when we do research contracts, we bring that back to the classroom, show them the cutting edge of what happens beyond textbooks, and then bring in industry folks from those industries to actually interact and show them the value of using Siemens software. So, it’s a multi-pronged approach here and students definitely benefit from it. And they go to the industry and I hear—and this a feedback we get both in their Co-Op as well as their actual jobs—that the transition and the work experience is seamless. And definitely, that makes a big difference here; instead of spending months on training and getting them up to speed, now they can hit the ground running.
Jennifer Piper: That must be a tremendous benefit for them once they do enter the job market. As you know, Siemens does offer an NX student edition with a curriculum element. Can you tell us how you’ve been able to utilize that in the classroom?
Sam Anand: NX is taught first time in the sophomore year as a full class. So, the students get access to the free software that they can use on their laptop. Along with that, we have developed ourselves training packets in NX that somebody outside the classroom without going to the classroom can use and come up to speed with training. It’s like a crash course in NX, we can use that. On top of that, we talk about training and certificates and so on. Some students pick it up, and that’s why they move to the next level in training. And the best part is they use NX throughout their curriculum in all their five years. The idea is what we call a degree-wide solution. So, we let them use a software in every course and then build on it with other pieces of software so that they don’t forget it. So, there is some element of it used in every course as you move up from freshman to sophomore to junior to pre-junior to senior. So, that is the best part of it — it’s not learned in one course and forgotten.
Jennifer Piper: How do you go about teaching NX? What are the steps involved with getting students educated in that field?
Sam Anand: NX is a complex software. So, it’s not something that you pick up on the fly and you can learn it in one afternoon. Obviously, it’s complex for a reason; it can do a lot. So, we teach that in stages. We don’t want to go to tier five right away, we started tier one, teach the basics so they can do some simple modeling based on it, and then we ramp it up stage by stage to the complex parts and all the features of NX. So, it’s going to take some time for students to get up to all levels. But just knowing some basic modeling and using some of the features of NX will get you up and running for most of your jobs. We also teach some aspects of generative design, which is the new push right now. So, making them understand optimal designs is a big part of it. We do a lot of work with companies. Right now, we have a contract starting with Eaton on using topology-optimized designs for heat exchangers using machine learning. So, one of the things is there is no one optimal design, there are sub-optimal designs, and there’s a suite of other designs that are close to optimal that one may want to pick. And that generative design gives you not one option, but many options that one can choose from. And that is one thing that we want to emphasize. In life, there is no one solution, there is a suite of solutions, and each is applicable in different situations and you should know how to generate those solutions and go from there. And that is true for most life decisions, too.
Jennifer Piper: That’s definitely a very important lesson to hone in on. What about when teaching the digital twin? How does CAD synchronous technology and the digital twin affect mechanical engineering and product design?
Sam Anand: The digital twin predictive modeling, physics-based modeling, we emphasize those in courses. Students need to learn the fundamentals, but also need to use software to build predictive models using software so that they can use that framework of a digital twin of the process or the product to look at what-if scenarios: “What if I did this? What if I change this? What happens here?” So, that helps them hone those skills. And of course, there’s validation. Building a digital twin has to replicate the real-life model. And once it’s validated, then you can use it to plan and also design parts that are optimal and also design the process so that you can make it efficient, sustainable, and also cost-effective and make error-free parts. So, that is what digital twin does. And Siemens, with this emphasis on digitalization, digital transformation, and the digital thread of their data flowing from the design, process, all the way across the manufacturing chain. And the suite of software brings us to the point where we can teach the students the whole swath of those tools to understand the digital twin and digital strategy. And that is wrapped up in multiple courses. Of course, you cannot teach it in one course, it is spread across multiple courses. And we make it a point to build on it so that when students come out of the curriculum, they know how this works and the digitalization of the process and the product works here. It’s a slow process, but we build it up.
Jennifer Piper: What specific courses involve using NX for design? Can you expand on that a bit?
Sam Anand: We start with the basic graphics course at the sophomore level and then move up the chain. We use it in the mechanical design courses, we use it in the Strength of Materials course for designing parts and doing, basically, Simcenter 3D analysis using NX Nastran. And then we move up and build, once again, NX models for our heat transfer, fluids courses where we may use Star-CCM+ for analysis. We use NX models in our manufacturing process course for building parts and analyzing those parts for machining or additive manufacturing. So, NX is used in every course where you need a product for analysis. We use it over and over again here and build on it. And of course, NX is used later on in senior design when students work on an actual industry design problem, all of them use NX for modeling the product and doing all the analysis using the Siemens suite of software.
Jennifer Piper: And what types of projects are the students working on in these courses?
Sam Anand: Typically, what they’ll do is there’s a combination of things here. For example, you take manufacturing process, we teach them NX CAM, NX computer aided manufacturing for simulating machine tool paths. So, we give them parts and ask them to do the process plan for making the part using machining. And then they come back into NX CAM and plan the tool paths and visualize the tool paths using NX CAM to make sure that the process plan and the tool paths they have designed work correctly. And then the output of that is the NC code — we can take it and feed it to a virtual machine and see actually how it works here. So, that’s an example of using NX into NX CAM for the students to actually go through the process of getting into the interface of NX CAM, designing the tool paths, designing the process, visualizing using a tool part simulation software that’s inbuilt into NX and doing it. The same thing for NX Additive Manufacturing — you could build a part and then look at the support structures you need for the part, look at slicing, the time it takes, and all those problems. And then we have our own apps that we have constructed within NX Additive Manufacturing and we use a lot of those apps. So, it’s a combination of using Siemens native tools but also tools that we have built using Siemens NX APIs (Application Programming Interface) that we built here.
Jennifer Piper: What kind of feedback are you getting on these courses? Are they generally well-received by students?
Sam Anand: The students like the fact that they are learning a digital tool. The days of a professor writing on a whiteboard equations and regurgitating them are gone. You need to engage the class, you need to make it relevant to what they’re learning, so they understand the purpose of what they’re learning and what its application is. So, the Siemens software and the tools exactly fit in that mode. So, we not only teach the basics, but we give them real-life parts or examples in real life and ask them to analyze them using Siemens software. Now, they don’t have to write the equations because they know the software and the tools within Siemens already has the equations built in. After they work with pencil and paper, we bring it to the next step here so that in real life, when you go to an industry, you don’t grab your pencil, calculator, and paper and slog it out; you use the software to do exactly what it does. And that is the enlightenment that they get and say, “Wow! So now I can do what I was doing which took me two hours to do, I could do it in 10 minutes. And I can run 50 examples in one hour which I will never be able to do with pencil and paper.”
Jennifer Piper: It sounds like you’re really bringing things into the 21st century! Can you tell me a little bit more about what sort of research projects you’re focusing on? What do you have underway?
Sam Anand: We do a range of projects, and in all of them, we use a lot of the Siemens software, we make it upon to use commercial software so that we keep it all aboveboard. We do projects on additive manufacturing design, we do NX-based designs for clients, analyze designs, and write our own graphic user interface within NX, we apply our algorithms and computational geometry methods for analyzing a part design and then segregating it and doing analysis to find out the process parameters in additive manufacturing or problem areas — when you make a part, and then highlight it so the designers can make changes to the part or change the process parameters. That’s one area. We also look at layer-by-layer analysis of the part using first principles physics and then look at distortion prediction for metal additive manufacturing and compensation within NX at this point. We do a lot of work on IIoT on gathering machine data automatically and pulling it into the cloud, and then doing first principles based analysis and trend analysis and correlating the process parameters to make an optimal part while changing the process parameters on the fly. We also bring in AR and VR right now so you can get that data onto your iPad as you look at the machine, and superimpose machine data on your iPad so that you can see what’s going on in the machine when you walk up to the machine close by. You’ll see a picture of the machine, but you also see the parameters of the machine data and what’s going on right on the iPad. So, that’s your mixed reality interface here. We’re doing projects with the medical school using additive manufacturing for cranial flap repair for neurosurgery, where we collect CT scan data and actually analyze it for making a 3D printed part. So, a lot of range of applications from aerospace to automotive.
Jennifer Piper: Can you talk a bit about your experience with the Digital Manufacturing Design Innovation Institute?
Sam Anand: It was a federal initiative by the Obama government. It is based in Chicago, Illinois, UI Labs, University of Illinois Labs at Chicago. So, in a nutshell, it is government funding to enhance the manufacturing competitiveness of this country. So, it started off in 2016 or so. One of the first projects we did there was on virtual modeling and prediction of metal powder additive manufacturing. We partnered with GE Global Research and the University of Illinois Urbana-Champaign along with TechSolve, where we were using NX APIs that we talked about for analyzing part designs, looking at problem areas of the part what we call is DfAM (Designed for Additive Manufacturing) features, just to highlight those features so that we can fix those parts here in the early design stage by performing some analysis. We wrote a paper based on that and it was awarded the Best Paper at the North American Manufacturing Research Conference.
Jennifer Piper: Wow, that’s tremendous. And what other DMDII projects have you been a part of?
Sam Anand: The next DMDII project was led by the University of Cincinnati, I was the principal investigator. We worked with Faurecia and Raytheon for an IIoT device for collecting machine data using inexpensive Logitech cameras that you can place in front of an older machine that does not have sensors, and then recording the parameters of the machine that you see there and then analyzing it on the fly so that you can display it on your computer really far away. So, the idea was to combine the data from dumb machines with smart machines so that you see it as one big dashboard interface that you can use here. And we pushed that data onto the cloud and we pulled it back into an AR device and so on. And a brand new project that we finished on MXD was with Boeing and Siemens Corporate that involves digital twin, using machine learning, and then optimizing process parameters for a particular Boeing process. And of course, it’s proprietary, so I can’t get into the actual Boeing process here. But what we used is computer vision, image processing, machine learning, and digital twin to actually affect process changes on the fly so as to make a part, correct all the time, and fix it as it goes out of whack before the next part comes up at that point. So, it’s a good experience of using those projects and working with industries. So, those were the three projects. The University of Cincinnati is a Tier-1 MXD member. And, of course, we work closely with Siemens in some of those projects here.
Jennifer Piper: That must be very exciting that the University of Cincinnati is able to be involved with those projects as well. Sam, before we finish, I’d love to know, what is your biggest tip for a young engineer just starting out learning NX?
Sam Anand: Be patient. There is a learning curve. Once you get past a certain point, it will get much smoother and you will start enjoying it — the reason is now you’ll start exploring the features of NX, which are tremendous features. It spreads itself in different areas: You can do electrical design, you can do mechanical design, you can do aircraft part design, you can do additive manufacturing parts. So, there is no end to it, it goes into all the areas that you can think of. But once you master those things, you will start to enjoy it because now you can see the power of NX and the associated software to do so much analysis that 20 years ago people could not even imagine. That is a part that we try to emphasize; the digital tools and computing power has increased so tremendously that this is a new age right now that you can do all kinds of analysis and come up with great part designs, novel product designs, and novel ideas that you couldn’t have done 20 years ago.
Jennifer Piper: I’d like to look forward a bit. With technology evolving at such a rapid pace, how do you see the curriculum changing when teaching NX and other Siemens software?
Sam Anand: I think the idea is to integrate NX early in the curriculum and make it a mainstay of using NX and other courses for part design and analysis. And then using those part designs, seamlessly integrate with other applications like Simcenter 3D and Star-CCM+ in each of those courses, so the base NX always comes back in courses. One of the things we are contemplating is using one product as a basis of a project in each course. And it’s akin to making a product in a factory and different departments coming and actually providing input and modifying the design. So, we want to make that same scenario as students move to different courses and take the same product and do thermal analysis, mechanical design analysis, and stress analysis, but it’s the same part. So they know the effects of these kinds of analyses on the same part and how it evolves and changes, and why the different features of design come to bear so that it satisfies a particular constraint. Once again, NX is the backbone that we want to use for all these courses here.
Jennifer Piper: Well that’s wonderful to hear. And where do you see the future of design headed in general
Sam Anand: I’m one of those folks who does a lot of research contracts and then try to bring it to the classroom. There is a lot of effort right now in designing multifunctional multiple-material parts. So, how do we combine multiple materials to make them low-weight, and at the same time, it satisfies some heat transfer constraints? Maybe on one side, it is insulated, and one side is conducting as an aircraft application. Or it could be something that has some vibration properties that are specific to that application. So, how do you do multifunctional applications on the same part by combining materials using topology optimized design, which is a lightweight organic design? So, that is a new frontier. And doing intelligent designs to predict manufacturing problems beforehand so that you make design modifications ahead of time on these multifunctional multi-material designs that you come up with. So, that is the big deal. And also applications in medical, aerospace, auto, all these things are ripe open right now for new kinds of materials and new kinds of combining different materials to your best effect, making a lightweight part, at the same time, bringing in the functionality of the heat, the vibration, the thermal loading — all into one part here to make it optimal for you. That’s a new front right now.
Jennifer Piper: Are there any final thoughts you’d like to add about your program at the University of Cincinnati?
Sam Anand: I do want to say something, I’m actually sitting in this brand new Digital Futures building, which is a brand new entity. And it is basically an interdisciplinary research facility, which has 17 labs. And across the curriculum, from folks in business or art or design are all sitting here, and the common theme is digital, as they work on it. Obviously, we have some space here that we’ve been given. We have been identified as a good example of using digital tools in our research and curriculum, and that’s really why we’ve been called here. So, just wanted to plug in that particular element here. Other than that, we are excited to partner with Siemens. It’s been an excellent journey, and it is getting even better in terms of the tools we’re using and the collaboration we are seeing. We are working right now with folks at Siemens Milford on new areas that we want to penetrate using Siemens software and bring it back into the classroom. It always comes back to that so that the students benefit on a well-rounded education, and if they are graduate students, they benefit from a good research portfolio that they can use when they graduate and find good employment.
Jennifer Piper: Thank you so much, Sam, for being with us today. Hopefully, we’ll get to talk to you again soon.
Sam Anand: Jennifer, thank you and I really appreciate the opportunity given by Siemens and thank you for the excellent questions. Much appreciated.
Jennifer Piper: Thank you to our listeners for tuning in to today’s episode. Join us next time for more discussions about the latest in design innovation and software applications. I’m your host, Jennifer Piper, and this has been Next Generation Design.
Next Generation Design Podcast
As product engineering tools continue to morph and expand at speeds human expertise may not be able to endure, Revolutionary design technologies that span beyond industry borders, will prove their necessity for companies looking to take over their markets in the future. What will the future of design technologies and machinery look like? What will your digitalization story be? Where engineering meets tomorrow.