Taxal – Model-Based Propositions – Part 1
[00:00:13] Hello, my name is Alan Berentson Texel, I’m here with Paul Brown from Seamans, senior director of marketing at Siemens. Digital Industries are called IoT. We’re discussing model based propositions and today we’re talking about the requirements through the process, aren’t we, Paul? Absolutely. We talked about some of the problems. Let’s talk about, you know, so what do we need to do about this? How how can we make our lives easier? So how does how does what does one have to think about to actually make a difference?
[00:00:46] I think there’s a couple of elements to this as the the cultural element, which is that making sure that the people understand the need to communicate. And then there’s the technology element of what technology can bring to bear. I think importantly, one thing is that. Companies already have ways of doing this because the whole idea of managing requirements for a product, in many cases, companies already do that using things like spreadsheets. So they actually have some record. The challenge then is how do you make that? What do you do about traceability? What do you do about change? So I think that there’s both technology and also a level of human process that that companies need to think about as they go through this journey.
[00:01:33] Right. We talked about companies are really doing this, but these are isolated tasks on these are often isolated tasks which require a lot of human interaction to keep working and coordinated. And isn’t that one of the problems? I mean, one of the problems is we use all these different things all over the place and use humans potentially to interrelate them, which is a problem as humans make mistakes. You know, let’s be honest. So wouldn’t it be a good idea to use perhaps technologies or more formal methods of getting this all working together?
[00:02:07] Yeah, I mean, that’s part of the problem. As I say, some people use spreadsheets to manage things like their requirements, feed that through. But then the connexions between the different parts of the chains tend to, as you say, rely on human where I mean, at the end of the day, there’s less people in interpreting what’s there and feeding that through, which is, you know. Initially is a fine proposition, but straight away, the minute a change comes through. Just being able to trace where I change a requirement and all those things, so and that’s what technology can do for you. Technology can do that, gluing and connecting the dots and doing all the traceability. For example, if you look at if you think back, we are now at the zero six emissions regulations at the moment. This is for cars, for automotives, and in the euro, in the euro, six euro caps, six emission regulations. There’s a limit to how much the output of these vehicles, which is half of what it was in the euro, five well, and Eurocup seven will come out when that comes out. New new requirements, how to DDoS a company. Traceroute through is okay. Well, what does that impact, what sort of things are going to need to look at? Is it. And at moment they’re relying on manual methods. So having a systematic way, bringing technology in to help. And it is a help. I mean, you can’t do this just by throwing technology at it. Know, is is where we’re looking at is how can we connect the dots? How can we connect the dots from requirements through into parameters, into the design system, into simulation. When you look at using cia. type techniques, simulation to to be able to analyse and verify against those requirements and keep that loop all altogether constant, constantly feeding through.
[00:04:14] And one of the other benefits is, I mean, you talked about simulations and things like that is you go through a complex product lifecycle. You’re talking about complex, very complex products. They’ve got huge amounts of options and variance, and they all create their own challenges. Again, increasing the sort of complexity that we can we can have different levels of fidelity through this lifecycle, can’t we? And that’s part of the benefit of this methodology, is being able to manage and allow us to to to gain insights from these different levels of fidelity.
[00:04:51] Oh, absolutely. If you start right at the top level requirements into a basic system kind of architecture diagram, what do we want all of these different subsystems to do? How do they behave and how do they play together? Because and as you mentioned, options, variance. You can get situations where, you know, I have a product when I add something to that product, what’s the impact on all the other parts that are affected? Maybe it’s heat transfer. Maybe know, maybe you add something in which generates a heat source. Does it affect everything else? And how are you going to manage all of that without having some help from from the technology? And I think that goes back to my point, that the world is becoming more and more complex. The more consumer choice we offer, the more options more people can actually configure to what they want, the more personalisation that we have in products, which is everyone is talking about how products are becoming more personalised, adds to the complexity that you have companies have to live in and tracking requirements all the way through design validation and then closing that loop off. We are increasingly seeing customers using technologies like the Internet of Things to actually feed back to the start of the process, to give information to to close that loop of closed loop. And we call it the digital twin. But the whole idea of having a product definition inside of a card system, a computer generated definition which is controlled and verified by and managed and updated as we go through so much.
[00:06:34] And the other thing is, as a bi not even a by product, but as one of the significant benefits is when you do it right and you apply technology correctly, you immediately benefit from instant traceability, improved quality, you know, and to help things like compliance. I mean, medical device companies are big into into this type of methodology because it just helps them ensure it doesn’t it isn’t a replacement. It just makes sure it’s correct.
[00:07:05] Yes, absolutely. I mean, you get more and more regulation and regulatory control. You have to prove that you’ve done the work that you’ve done and that you understand the require the legislative requirements and how they ripple through and prove that you meet those standards. And that’s that’s where we’re talking about.
[00:07:27] So so how do we get going? I mean, how does a company, you know, starts I mean, what should they think of?
[00:07:35] Well, I think one of the things important things is they look at the processes you use now. And as I say, everyone is doing a level of IoT requirements. If you’re doing custom products, if you’re doing configure to order, if you’re doing, be able to order any of those or come in with customer requirements. How do you manage that process through and how do you track it? Try and get an understanding of how you’re doing it now. Now you’re passing those requirements on. Technology, yeah, as I said, technology will will help, but it’s not the it’s not the magic answer. There’s the idea of people, people like ourselves. We have people that can help our people come talk to us about the way about their processes and how we can help. And, you know, don’t it’s not a case of just, oh, let’s throw some technology at it. We are also seeing a lot more people coming out of new graduates coming out in the academic curriculums are changing and you’re seeing more and more graduates coming out which understand this kind of course, the main idea in the old days when you say, OK, I did a degree in mechanical engineering or electrical engineering, it’s it’s more I see more and more people coming out with a systems type background to understand those crossovers. And and so academia is another area where people can go look and say. And then there are obviously there are regular kind of seminars around this area, around systems engineering. But one of the key messages I think is don’t get don’t get put off by all the terminology. It’s actually and it’s actually what most companies are doing already without all the terminology.
[00:09:15] Great. Thank you, Paul. So, you know, taking it from Paul, who has been involved in this domain for a long time with some amazing customers, because I’ve met some of them. It is a complex paradigm to get your head around. I think it’s made worse sometimes by the terminology. So keep it simple. Rely on people who understand the problems. Go to academia. Thank you, Paul. Very interesting. I appreciate that. Thank you, Alan.