How to Optimize Automation to its Fullest in A&D – Transcript
In the latest episode of Talking Aerospace Today, Todd Tuthill and Suresh Rama conclude exploring what aerospace and defense can learn from automotive to automate its manufacturing processes, focusing on how to optimize automation for a company’s needs.
Patty Russo: Greetings, and welcome to Talking Aerospace Today from Siemens Digital Industries Software. I’m Patty Russo and I’m responsible for global marketing for aerospace and defense here at Siemens. Today we wrap up our very informative discussion that we’ve had over the course of the past two episodes on the things that the A&D industry can learn from automotive as aerospace and defense implements smart manufacturing, adaptive production, and automation technologies to boost its manufacturing processes. Joining us again are Todd Tuthill, Vice President, Aerospace, Defense, and Marine, and Suresh Rama, digital manufacturing evangelist here at Siemens. So let’s get right back into it and start with a question for Suresh.
Patty Russo: Yeah, to oversimplify the idea, Suresh, that you had mentioned you had said design for automation. To oversimplify, I’m going to say it’s almost like we need to begin with the end in mind. Cliché, but applicable and look at things from a holistic point of view, not just the design of the product, but as we’re talking about design for automation in the factory. It begs the question, and again, I’m kind of thinking about the breadth of the listener, whether they’re from a larger organization or on the supplier side, how much automation is enough? And let’s talk specifically about the A&D industry. How much is enough to see some benefit or return on investment, or looking at it a different way, how much is too much? You know, we don’t want to set ourselves up to fail. So how do companies decide what’s appropriate for their unique situation?
Suresh Rama: Let me slice that question into maybe three different dimensions. One being the economic viability, right? This encompasses the cost benefit analysis, and this is always a big thing. And it’s all about the initial investment cost and the projected ROI and the payback period. And it varies from one industry to the other. So some of that lessons cannot be directly learned from automotive because some of the payback period in the automotive world, which is a high level of maturation in the automated assembly systems may be much, much shorter because of the way that it has progressed. So companies need to carefully evaluate whether the automation investment will lead to significant cost savings, whether it be productivity increases through consistent and faster execution of those tasks in a safe way, quality improvements, because again the consistency of approach or conducting the task is going to be more high fidelity with automated system than manual. And this can also reduce the amount of human oversight for compliance requirements in order to achieve the regulatory requirements.
Suresh Rama: So this can all justify the expenditure. So it has many dimensions even within the economic viability aspect of how much automation that you need. And these are the things that is going to propel the adoption of automation. The next one is the production characteristics, and this production characteristics considers production volume, product complexity and variation, and the level of flexibility that is required. And that is not only in the product, but also in the processes or tasks that are going to be accomplished in not only manufacturing, but assembling the final product together. Higher the production volume always is easier to justify automation investments and more complex the product is that requires precision and need for intricate precision, locations and placement and alignments, automation can help. But there is a tradeoff between where perfection can be your biggest enemy.
Suresh Rama: So achieving a level of perfection through automation may result in a high investment cost and may not be required for low volumes of what you’re dealing with. So that has to be matched with the volume and product complexity and the requirement of precision, and this is where the manufacturing flexibility to handle these types of variations can really help someone looking into how much do I want automated. To say whether I want to go fully automated, partially automated, or stick with still manual. Last but not the least, is strategic alignment. And this brings the companies long term business strategy. Do I want to be a digital enterprise? Do I want to adopt this digital transformation?
Suresh Rama: Do I want to be in a competitive position that I’m sought after as the most flexible manufacturer for all of these types of product variants? And that kind of strategy alignment can also lead to the investments in automation because we’re looking at the future of where we want to look at, grow, and really pivot as the market demand shifts. And this also helps in availability of labor. More and more skilled labor for manual operations are becoming less and less, and more automation is sought after to replace the lack of skilled labor or the retirement of skilled labor, and the lack of ability to backfill them with skilled labor.
Suresh Rama: And more and more technological readiness of the workforce is also in question. So workforce upskilling to introduce them to the world of automation maintenance of the automated systems, and going towards that is necessary for the adoption of automation. That also brings another cost factor that needs to be considered before we enter into guessing or estimating how much is the right amount of automation. And it’s not just cost.
Patty Russo: Suresh, you were just talking in terms of the economic viability, the investment looking for consistency, and one of the things that that you talked about to you was perfect being the enemy of good and getting things aligned. Is there a tradeoff between quality and productivity when it comes to automation? Looking kind of just for a high level view of that before we get into the next topic that we want to cover.
Todd Tuthill: I don’t know if I’d call it a tradeoff. I think there are, there are ways to design your automation and you want to design your automation to improve both and I’d say that’s the goal. And there’s probably times where you can say, “Okay, this particular step in the automation, I’m doing it because it’s going to, it’s going to make quality better.” And maybe it’s not quite as productive and maybe the savings is in the long term life cycle of your product that the quality is better. And maybe there’s other aspects you can say, well, we certainly never want to hurt quality. We’re not going to drive quality down, but maybe it’s quality neutral and we’re doing this because it’s really much faster and much more efficient, but I think in in many cases well designed automation does both. It improves quality and it improves it improves productivity.
Patty Russo: So another thought that comes to mind as you were just talking. This question is for Suresh. I’m thinking about the differences between whether I’m planning for a greenfield factory versus a brownfield factory. How does this approach, how does digital transformation and automation in a brownfield factory different than a greenfield factory?
Suresh Rama: At a high level, greenfield offers more freedom in designing a smart automated factory, but it does come at higher initial costs. Comparatively, brownfield allows for gradual transformation to adopt automation, but it comes with more constraints. In the greenfield scenario, we can start with a clean slate, optimizing the layout for automated manufacturing for maximum productivity and efficiency with fully integrated end-to-end automation right from the start. Now looking back at automotive industry, this is how most body and wide welding or joining manufacturing processes started. Today, one cannot even imagine putting up a factory that builds the body structure of the car without 100 percent automation, without a robotic assembly system.
Suresh Rama: That’s where they start, because that is how the process engineers today are even trained to think. And hence, it has become very, very ingrained in the way they do it. So greenfield also provides the opportunity to implement innovative automation systems right away and adopt the automation technology and systems from other industries readily and, because there’s no legacy systems to integrate or replace. So we don’t have to think about the sunk costs and investments in machines that are already there. Therefore the costs are pretty high because you are building the infrastructure that is needed for a greenfield plant, but you have the flexibility to design that for a ground up automated manufacturing factory.
Suresh Rama: In the brownfield scenario, although existing assets and infrastructure can be reused with minimal or no additional investment, it does offer constraints of space, resulting in suboptimal layouts for good automation or getting the most efficiency out of the automation that you’re going to deploy. Also, there is a need to reuse or integrate existing machines, systems, which may, or even IT infrastructure or OT infrastructure that is already in there, which may require custom solutions for retrofitting and resulting only in a gradual transmission, transition to fully automated systems. Moreover, the transition management becomes a huge factor because usually in a brownfield you are producing something, so you don’t have like an empty factory that you’re going to fill up with automated systems, then it becomes a greenfield.
Suresh Rama: So a brownfield is actually producing something. So the transition management of how to keep the existing production going while bringing in new automated systems becomes a big factor in project management and what to shut down, what to bring online, how soon to bring online so that I can shift from what was previously done in a manual or semimanual to a fully automated or semiautomated system.
Patty Russo: Thank you for that, Suresh. Good insights. And as we look to, we’ve got just a couple more questions before we wrap, as we look at concluding this session, I’m putting on my hat as if I’m a listener, and I understand what’s ahead and some of the things that we need to do. So I’m, let’s assume that I’m ready to take this journey and I’ve listened and I’m going to go back to my organization and talk to our team and say this is what we need to do. What’s the first step, Todd? Where should an organization start?
Todd Tuthill: OK. I’ll start with the negative and I’ll tell you what not to do. Don’t start by going out and buying a bunch of hardware. That’s not where you we don’t start in the physical. You want to start in the digital, and I’d say our goal, and I listened to a lot of what Suresh said and the thing that kept coming back to me is I want to be Goldilocks. I want it just right and I think that’s what that’s what we all want. It’s, but how do you figure that out? Right? Goldilocks had to taste the porridge before she knew if it was too hot or too cold. We don’t want to taste the porridge first, tasting the porridge in manufacturing is way too expensive. What we want to do is use something we call a production digital twin. To figure that out, to tell us how hot and cold the porridge is.
Patty Russo: So I’m going to, I’m going to interrupt you there.
Todd Tuthill: Okay.
Patty Russo: Because the digital twin of production is a key topic that we’re going to pick up in our next episode, which makes this the perfect point to break in this discussion. But we will definitely be picking it up. So with that, I’d like to thank both Todd and Suresh for building on such an important topic in our industry. So many great insights, and thank you to our listeners who have been with us through this series. We will be back to continue this conversation on digital transformation and automation in the aerospace manufacturing industry. I’m Patty Russo and we’ll see you next time on Talking Aerospace Today.
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