There is Lean, and then there is Lean Industry 4.0

Welcome to the Industry 4.0 Club's fireside chat. The club's purpose is to engage the power of diverse worldwide talent to accelerate the global evolution to Industry 4.0. We accomplish this by hosting and supporting respectful, thoughtful, and interdisciplinary open conversations and creating quality content on wide-ranging Industry 4.0 topics to expand the reach of our community. My name is Mike Ungar, and I am the CEO of the Industry 4.0 Club. I have 40— over 40 years of experience, most of that in manufacturing at Michelin. Today, we're airing the 6th episode of our series of broadcasts entitled Lean Industry 4.0: Operational Excellence Meets Technology. Hosting this series today with me is Tim Stewart, Tim is the president of Visual Decisions. Tim, would you please introduce yourself?

Sure. So I've been in the industry since '92, and I have been working for most of that time with collecting information from the shop floor and using that to drive improvements in the process. I've had direct experience at Black& Decker as well as Cummins Engine. And then I spent some time in the software industry. I got better though and moved to a lean consulting company for a while. And I've then ever since then, I kind of broke off on my own and I've been working at that intersection. I've been working at that intersection between utilizing the data from the shop floor, from automated Industry 4.0 and precursor systems, and then utilizing that information within the lean tools to drive improvements to the process.

Thanks, Tim. So today, we're going to talk about, or the topic we're going to talk about is there's lean and then there's Lean Industry 4.0. And Tim and I thought it would be a good opportunity today to sort of just he and I talk for a while about this topic of lean and Lean Industry 4.0. Between us, we have decades of experience with Lean, and of course, most recently with Industry 4.0, and thought it'd be a great exchange if we could just share some thoughts and really engage specifically on the integration of Industry 4.0 into Lean practices. So, Tim, would you mind starting us off and sharing some background about our topic?

Sure, thanks, Mike. First off, I believe that there's a big better-together opportunity around lean Industry 4.0 or digital lean or whatever we want to call it. Whether a company's already been progressing on their lean journey for decades or if they've only recently dipped their toe in the water, my experience is that Industry 4.0 solutions can help drive significantly better results from those efforts. And I'm not alone in that belief either. There have been a number of studies by Bain and others that have shown that digital lean programs yield better results than lean initiatives alone. Most of the tools in the lean toolbox use data to some extent, and having higher quality data at a more granular level that's fully contextualized and highly available to everyone simply makes those tools much more effective. And likewise, I believe that some form of operational excellence or lean program has to be in place to really take full advantage of Industry 4.0 initiatives. For example, you can put an IoT system in place to collect data, contextualize that information, share it in pretty charts and graphs, use AI to analyze the information and make recommendations on actions to take. But if nobody takes those actions, or if nobody uses those charts and graphs to perform root cause analysis or something else, then nothing has really improved. So I strongly believe in the synergy between the culture and the tools that Lean provides, and the improved analysis and decision-making capabilities made possible through Industry 4.0.

That's a great way to get us started, Tim. Just before we get into the conversation in some more depth, I want to just mention to our friends that are listening on LinkedIn Live, if you have a question for Tim or I throughout the broadcast, please drop it into the comment section, and we'll do our best to get to it. So, Tim, one of the things that comes to mind when we think about this challenge, or this integration of Lean Industry 4.0, is a lot I hear from— I've heard from a lot of Lean practitioners who've worked really hard for now, maybe decades, to put in place Lean, that they're afraid of bringing something else in, and its impact it might have on their Lean culture. All right? Right. So, Perhaps we can start off and talk about what is a lean culture. Maybe you can get us started, and then we can exchange on that from there.

Sure. One of my favorite quotes from Taichi Ohno is that purpose of lean is to create many different ways. And so, you want differentiation from the systems that came before that. production system that came before that, in that it's really focused on empowering employees and utilizing their contributions, not just from a physical perspective, but from a mental perspective as well, and really having them, uh, be a part of that improvement process and so forth. You know, one of my favorite quotes from a customer plant manager is that process improvement is a participation sport.

Yes.

And really focusing in on how do you get the people involved and how do you get them participating in this and really taking ownership of that process improvement. Yeah, that's a key part of that lean culture. And I think the concern with some of these tools is that if you automate that data collection process, if you don't have the people, you know, doing the tick sheets and writing on the whiteboards and so forth, that they won't be as involved and won't feel that, you know, kind of minute-to-minute ownership of that information and that process.

You know, I think, I think, though, your point about employee engagement, it's funny because when you think about, just forget about, take off the word Lean from the word culture and say, what's a good manufacturing culture? Employee engagement's a great, regardless, should be a great part of your culture, right?

Yeah.

When I think, when I think about Lean culture, there are 5 points that come to my mind that I usually talk about with folks and look for, say, hey, you've got a great Lean culture, or culture, if you will, when you have these 5 points. And the first one that comes to my mind is value defined by the customer, by the client. The second one is what you just mentioned, employee engagement. Those things, it doesn't matter. You could take the word, like I said, take the word lean off and just talk about culture. Then there are 3 more elements that I like to always highlight. One is this passion for eliminating waste. A strong respect for standards. When I say respect for standards, I don't mean blind obedience to the standards. I mean knowing what the standards are, recognizing when you're having trouble meeting them or you're not meeting them, and then acting accordingly.

Yep.

Then thirdly, visual management, making these visible. When I think about Industry 4.0, they really don't bump against any of those, to be honest with you. When we think about employee engagement, I've often talked about or often think about rather than having the employee write down the data, have it automatically captured, and use the time they would use to write down the data to help them, to engage them in problem solving.

Right.

So, so we don't change the idea of employee engagement, we just change what we're doing to get it done.

And to me, that's so much more value add, that if your goal is to, you know, part of the goal is to create thinking employees, and part of the goal is to identify and eliminate waste and so forth. If you combine those things and automate the drudgery work of collecting the data, but then engage their higher faculties in how do you use that information to then make improvements to the process to identify and eliminate that waste, to me that is something that is significantly more valuable to the company than having them do the information on tick sheets and whiteboards and so forth.

Yeah, so I think comfortably, and I would have this discussion with anybody who's a Lean practitioner, I'll say a purist, if you will, for lack of a better word, but somebody who doesn't think about the integration of these tools, to say, I don't think there, you impact culture with Lean, with Industry 4.0 tools. I think if, worst case, you don't change it, the best case, you actually enhance it. If you do it the right way.

Yeah, and, um, you know, I think that, uh, some of the, you know, practices that I've seen put in place around these things, um, are fantastic from, you know, different customers that I've worked with. Uh, I think on some of the other conversations that we've had in this series, I've talked about the TPM Tuesday idea where, you know, one of the plant managers has worked with the lines to shut down once a week on Tuesdays, gather the operators, the supervisors, maintenance people, etc., look at the actual information coming from the system that's collected automatically, and then utilize that information, but having everybody involved in that process to then generate improvement ideas with that information and try to mitigate or eliminate one of those Top 3 reasons for downtime over the past week.

Yeah, that's a great example. So we've talked about culture now, and hopefully our listeners can embrace the fact that we can bring the Industry 4.0 tools to bear. And should keep in mind that our goal isn't to change any of those culture points, but to maintain our culture and in fact enhance it with what we do with Industry 4.0. Just that hopefully our listeners can follow that. So with culture being defined, maybe we can take a moment and step back and talk about lean tools for a moment.

Sure.

So let's kind of get into what are some of the foundational lean tools that you've used most often, and then maybe we can dig into those and then we'll, and then sort of pivot from that.

Sure, I mean, some of those, you know, foundational tools, you know, 5S, visual controls, Kaizen, value stream mapping, SMED. There's a lot of lean tools, and probably 5S not quite as much, but I think all the rest of those are very highly data-based. And There's a lot of room for interaction between these initiatives.

I think it's interesting when you talk about, you mentioned the VSM. Regardless of whatever tools I'm going to use, whether clean tools, Release 4.0 tools, or some blended, I'm always starting with the VSM. Because I can't, if I can make, and the beauty about the VSM again is it makes the process visual. And we know you can actually do a— in some ways you can now do that digitally, and it's in many ways it becomes a digital twin of the factory, right? And so it's much easier then to actually create a future state, understand the impact of that. But I'm always starting with the VSM.

Yep. Yeah, I'm still waiting for any of the vendors out there, if you're listening, to create a live value stream map based on the information coming from the shop floor, where you can see— you can use the VSM not only as a planning tool and as a project-based tool, but as a live daily management tool where I can see for a given work order, for a different product family and so forth, what is the expected time between, you know, at a task and between tasks and so forth, and then what is the actual time. And see, is it, you know, within some standard deviation of the expectation? Is it varying from the path that it's supposed to take? How can I identify exceptions that are happening out on the shop floor utilizing that and so forth? And I— again, if there are any vendors out there, if you have such a tool, let me know and I will work with you.

Yeah, that's good. Actually, I've met, I think a year ago, I met somebody who had developed a tool and I didn't get a chance to get my hands into it. But I think there are some folks that are becoming much closer to, at least you have it digitally. Maybe it doesn't create live feedback. So you can't, you know, on the spot, but at least you've got a digital tool that you can easily change and develop a future state.

Yeah.

And the beauty about that, of course, is that it's easier than redrawing it every time you make a, you know, you do a new one. So it does save some time. And it's also then much more portable, right, for others. You can— so I think it's a— but I would start with the VSM regardless when I'm looking at making improvements. I think that's a great visual tool. And whether you— and making that using digital support for that, to me, makes a lot of sense. You mentioned also SMED and Kaizen. The idea of having those using the data collection, having that be more automated and more quick. I mean, we used to teach a version of Lean Six Sigma.

Okay.

We get a kick out of the Six Sigma guys integrating Lean into their tools. But DMAIC, if you follow that define and measure, there's always going to be measure in that approach, whether it's Lean or Lean Six Sigma. You're exactly right. Having automated data collection, having the data available, one gives you a jump on moving through to creating the alternatives and looking at options for improvement. Instead of having to go out and by hand collect all that data, When you're doing an event itself.

Yep. And some of the AI-based video tools and so forth that are coming out these days, yeah, from a SMED process, give you tremendous capability of automating spaghetti mapping and all kinds of different portions of that SMED process.

So let's jump in for a second then. So We talked about some of the lean tools, even 5S. I think you— we start thinking through, um, how we can integrate some Industry 4.0 tools into that process as well. But 5S and Kaizen and VSM and SMED, let's talk through where does Industry 4.0 come into those, and then maybe, you know, how does additional other— What Industry 4.0 tools fit into a continuous improvement or lean approach?

Sure. So if you— I'll start with an easy one with visual controls.

Yes.

You know, if you think about the visual controls that you put in place from a lean perspective these days, whether it's, you know, daily production charts or, you know, so many different aspects of giving feedback to the operator and encouraging the behaviors that you're trying to drive and so forth. Having those be digitally based and the data is collected automatically and updated live for the people, and then now you can focus instead of having them— instead of trying to focus on the behavior of updating the visual control itself, you can focus on what is the behavior that you want that visual control to drive on the shop floor and now look to drive that behavior with that. And so if you're intentional about those things, you can do so much more with those, uh, because you can contextualize the information much more too and have more detail available.

Um, well, if I could just add to what you're saying, The other challenge we used to get into, you mentioned that we used to create hour-by-hour charts for the production post, right?

Yeah.

The challenge was that no hour in many of the work posts that we were involved in, no hour was identical to the next. What do I mean by that? The amount of production or the standard, the target standard in 1 hour, if you had nothing going on with 1 number, But if I had the shift break in that hour, then it would be another number. If I did a changeover in that hour, it'd be another number. If I was starting at the beginning of the shift and had 5 minutes of startup duties involved, that was another time. And so we would always have these crazy— how do we create an hour-by-hour chart? Well, especially when changeovers didn't occur at the same time every day.

Right.

That was dynamic. And so with a digital hour-by-hour chart, you have the ability now much more easily to do that, have it be there in front of the individual and be something that is much more easily dynamically dealt with than before in the old paper or whiteboard approach. And it sounds like it's a simple thing, but at least in our world, false reds and false greens, you know, you can't really say, well, what are you gonna do about that? You don't— you're not dealing with really the root cause. It's just a numbers issue. It's not a real production problem. So, so this using Industry 4.0 and bringing this data in digitally, managing it is a lot more effective.

Yeah, I'm— one of the complaints that I've heard about the digital displays is that you can read a whiteboard from, you know, 20, 30 feet away, and you may not be able to read a you know, production board on a TV screen from that far away. But with the whiteboard, it's in exactly one place on the shop floor, and you can only see it from within, you know, the 20 feet in front of it. But you can replicate that computer screen on as many different screens as you want. And so you can have that displayed at every single station if you want to and have that be visible to everyone.

Well, Plus, you know, one of the issues we run into, we ran into also is numbers versus, versus shapes and colors. I know colors is an issue for people that are colorblind, but let's take shapes. You can use when you have a certain target, and did you hit the target or not, you can display a shape to tell you whether you're successful or not. And it's a lot easier to see a shape from a distance than it is to see a number. And so using, again, good visual controls in an electronic format can be also just as effective or more effective because you're not trying to read numbers. You're able to quickly see a shape or a color and then determine where you are and what the challenges are.

Right. A check mark versus an X or something.

Exactly. So I think the digital approach there to our bar charts makes a lot of sense. Other things that you've been involved with there, or integrations of digital tools into lean tools?

One that I want to spend a little time on is standard work. When you, you know, look at standard work and you look at the Industry 4.0 solutions, I think that there's a tremendous opportunity to Tie those together. From, you know, the point of view of implementing standard work and getting that standardized out on the shop floor, there's, you know, the opportunity to display those standard work instructions and so forth on, you know, the screens right at the computer or right at the workstation. There's augmented reality capabilities. There's pick-to-light. There's all kinds of different ways that you can start to help enforce or encourage and poke at that standard work, you know, at the workstations and so forth. And likewise, there's video analytics that you can— for manual processes that you can start to look at, you know, how people are actually moving and grabbing parts and so forth and whether they're adhering to the standard process. process, even for the manual work. For, you know, machines, you can make sure that, you know, each shift, each operator that's running that process has the machine dialed in the exact same way that they're supposed to according to the standards and so forth.

Yeah.

There's a tremendous ability to tie in You know, what you're trying to do from a standard work perspective into the lean tools or into the Industry 4.0 tools, but then also when you think about how you're trying to utilize and drive value from those Industry 4.0 tools, you're trying to, you know, get people to utilize that information and so forth. And so when you think about standard work, not just for the operators but for your leadership and so forth. Having that defined so that, you know, utilizing the information coming from those systems is part of the daily practices for supervisors and engineers and so forth also makes a huge difference. And so I think that there's a lot of synergy between standard work and these tools.

Yeah, that's a, that's a great comment. You know, I think you, you think about the ability to put sensors out there to know that the machine is set up correctly. And that the operators, you could even say, put in place timers, if you will, to know how long the operator sequence should take. Are they hitting it or not hitting it? And really to provide feedback, active feedback, because most folks, if they have the feedback, then they'll do something about it, right? Especially if it's accurate and legitimate feedback. So, hey, we have a question from someone who's listening in, and I wanted just to put up on the screen, maybe. You have some experience here. So Matt asked the question, are there some off-the-shelf digital lean systems solutions that exist on the market? Most of these I've seen in the past were homegrown. Anything come to mind from your experience?

There are a couple that I've come across, actually one that I just started talking to this Week, coincidentally. That's based out of Sweden, but it is— their solution is a digital lean platform, and you can customize it and tailor it to your own practices and so forth. But I haven't really had a chance to dig into it too deeply yet. Some of the other solutions that I've seen are not as fully, uh, let's say integrated with the data collection side, but they have good, uh, forms and so forth that, you know, are Excel-based and so forth that help you, um, you know, format some of these things, but they're not tied to the live data collection.

You know, and to add to what you're saying, moreover, today I see systems that deal with a very small part of the overall process and I was able to get with one element of enhancing a lean tool, but they don't— they're not comprehensive yet. And I'm not sure that, you know, it kind of depends on what's most burdensome for you in your environment. Sometimes picking that one little sliver can make a big difference. You know, the one I'm thinking about off the top, for example, would be something like Connected Worker where If you've got the ability to put work instructions and just general information available quickly to the operator on the floor, you know, that's— it sounds really simple, but it provides communication in a way that enhances what's going on immediately. And so you're not surprised by stuff.

Yeah.

So, I mean, those are— but these are these very slight, you know, they deal with a problem in any situation. They're not very— I think if I'm saying that question— as comprehensive as an entire platform, right?

Yeah, I mean, I'd love to see something that kind of automated the process of putting a TPM tower in place and just being able to see, you know, all of that information that's in a typical tower. And I just haven't seen it out there yet. I've hoped that people would take a platform like Tulip or something like that and as a third party, you know, build that on top of the Tulip platform and then be able to sell that as a value-add solution on top of there, but I haven't seen it today.

Yeah, well, thanks, Matt, for the question. And, you know, we'll perhaps even offline, we can, we can provide you some more feedback on that. So I guess we're talking about where we can integrate Industry 4.0 into our lean environment. The other thing we really haven't touched on, and I— we spent a lot of time talking about data, but when you start thinking a little bit more broadly about things like cobots, using technology to improve ergonomics on the shop floor, To me, that's a wonderful opportunity. And that technology was much more expensive years ago and not nearly as, if you will, friendly with people.

Right.

So, you know, I know at least in my work history, ergonomics was always a challenge. We're always trying to make incremental progress in that. And these cobots that are available now are a huge step forward to take some of the work off individuals, but also be able to have individuals work around these, these, this automation in a way that's safe.

Yeah, and I know that a lot of the lean practitioners that I worked with, you know, over the past 20 years and so forth have pushed back on a lot of the robotics and automation because it disrupts flow. Because it can't be within the process because you have to have those safety fences and so forth around the robots. It's hard to, you know, implement that within a single piece flow type of an environment.

Right.

But as you talk about, you know, with the cobots and so forth that can operate safely within, you know, an environment with operators and so forth, now you have the ability to put some of those things in place that address those ergonomics issues, but still operate safely within that single-piece flow or, you know, a better flow environment than traditional manufacturing would look at.

Yeah, we have another question from— and I apologize, I think it's Noman. He says, Tim, much of the conversation I'm having with machine learning, AI, and manufacturing be it healthcare, discrete, etc., what would you recommend to the people who held the purse to approach it? I think if I understand that question, it's really— I'm going to assume what he's asking is how do we encourage folks that are willing to make the investments that they should invest in MلاI?

I definitely think that there's intersections with machine learning and artificial intelligence in this space as well. If we look at being able to do root cause analysis and so forth, then there's a lot of applications there. There's a lot of applications around product quality. That you can look at in terms of AI and ML. If you look at predictive maintenance and, you know, other applications such as that, really what you're trying to do when you reduce downtime is you're trying to, you know, keep that flow within the shop floor so that you can get the throughput and so forth, and you're trying to reduce the variation within the process. And so There are a ton of applications for AI and ML, and for an individual customer, where the biggest opportunity would lie would really depend on, you know, what their process is, where they have the inefficiencies in that process. Those are the things that would determine the biggest payback. So, you know, my recommendation is always to kind of begin with the end in mind. Take the time upfront to identify really where are those biggest opportunities and what, you know, what are the biggest levers that you can pull within the process to drive that payback and then start from there.

I would add too, you know, there's been enough work done, quite a bit of work done with these systems so that there are plenty of case studies out there where whether you think your biggest bang for the buck is quality or production or reliability or energy, or, you know, you choose it. There are plenty of case studies out there, and I think taking advantage of those case studies to help understand what, what could be for you is really, really important. Certainly, just to add it, you know, the adage— used to see those weight loss commercials, right, where it says, you know, Your results may vary, right, based upon your application and your history. It's the same thing here, but I think you can look for the potential. And there are companies, you know, I think the other warning is, if you will, or caution is, find, if you do get into this, find a company with experience because there are a lot of folks who've tried things and have learned from their failures, if you will. And so they know now the best way to go in terms of making sure that they deliver the results that you're— and they're going to do that analysis with you up front to predict what those results might be as well.

Yeah.

So that's a good— thank you, Norman, for the question. That's really great. So really, you're bringing up another point. Machine learning and AI is certainly now an Industry 4.0 tool that should be integrated into our continuous improvement, our operational excellence approach, along with Lean. I mean, it's focused on waste elimination. You know, I mentioned energy. You can reduce your energy costs. You can improve quality, which will reduce the cost of non-quality, which again is a waste to get rid of. So there's a lot of opportunity here using that tool as an example to actually eliminate waste. And improve your overall performance of your process. Any other tools you can think of or that we should talk about when we talk about adding Industry 4.0 tools to our overall continuous improvement toolbox?

I'll throw another aspirational one out there. A lot of companies have utilized FMEA or Failure Mode and Effect Analysis. to look at individual parts of the process or, you know, the product failures and so forth. And usually that's a very intense manual project where you lock people in a conference room for a week and have them brainstorm through what are all the different potential failure modes and what are the effects of those and going through your RPN analysis and so forth. And then you'll have them implement a data collection system on the shop floor, machine monitoring. And when they go to create what are the tags that they want to put in place for the different failures, different stoppages that they see, even if they've done an FMEA on that line, they won't use the failure modes from the FMEA to say these are the different failures that we're seeing.

Mm-hmm.

they'll just create, you know, a separate set of them, and then you can't tie those together. But if you actually integrate the FMEA with that downtime collection from the process itself, you can actually automate the process of keeping that FMEA up to date and so forth. And then you can use the FMEA as kind of a live tool to manage that process and so forth as well. And so again, There's a lot of potential for integration here that's just not being taken advantage of, and I don't know of any solutions out there in the marketplace that do that automatically.

I appreciate the thought process there, but I mean, I really, I guess at the end of the day, you know, with technology, as long as you stay, I guess, grounded in the culture, the principles of Lean, And are wise enough to not lose them and be aware of them as you bring in more. For me, it's just enlarging the toolbox, right? That's, that's really the opportunity here to make more faster progress at the end of the day and improve your business results.

Yeah. And I mean, that, like I said, is more of an aspirational goal. It's not something that I would recommend trying to Start day one. Um, but I think that, you know, as with everything else, if you start by focusing on the basics and, uh, really get those to be exceptional, uh, you're gonna make so much improvement in the process just from doing the basics extremely well that you can work on those other things downstream.

Yeah, that's a good, that's a really good point. So I, we've been talking for, oh, 35 minutes or so about Lean Industry 4.0, and I think we're probably reaching the end of our time together. Do you have any final thoughts, Tim, to share with the audience before we wrap up?

I think we've touched on a lot of it. It's, you know, again, I think that, you know, this is, you know, better together. situation where you can certainly have success with lean without doing Industry 4.0, and companies have been having that success for decades now. You can have success with Industry 4.0 without having that operational excellence program or lean in place, but it's a lot harder to actually generate those improvements. But when you put them together, I think that, you know, 1+ 1 really does equal 3 here.

Yeah, that's a really good point. I wanted to share something that we were talking about offline that I think might be interesting to think about for those listening. You know, I think about Lean having been, well, Toyota was doing some of the tools long before it was formalized, but I guess the book Lean Thinking was probably a stake in the ground with introducing it to the masses, if you will, in the early '80s. Okay, so, and for a lot of companies, they didn't really— and then you went to the '80s and people were talking about it, just like we're talking about Industry 4.0 now, and even into the '90s, and even past that. Today still, there are companies that haven't embraced some of those lean tools, right? So, so I'm thinking about one company that It wasn't until the late '90s that they started considering lean, and then really, you know, 25 years later in the mid-2000s is when that got formalized as part of the company's continuous improvement culture. So 25 years, okay? And when I think about Industry 4.0, it was only formally defined maybe 10 years ago, and a lot of technology and the cost of things have come down and The technology is rapidly advancing. I mean, we just, you know, we haven't talked at all about generative AI and its potential, but the point being is that, do you want to be that company that took 25 years to formalize its lean practices when it knew when they were public 25 years earlier and how much effort they lost in terms of being able to leverage that for progress? My challenge as we're talking this today is, don't wait 25 years to start integrating Industry 4.0 into your lean culture, into your operational excellence culture altogether. Now is the time. You don't learn by not doing, you've got to get out there and go after it. That's my 2 cents, don't wait too long.

Excellent.

Yeah, thanks for the time. So, so we've, we've been talking about Lean, and then now that there's Lean Industry 4.0, really talking about the importance of integrating Industry 4.0 into your Lean practices and your Lean culture. I want to thank Tim for taking his time out of his schedule today to be part of this Industry 4.0 Club fireside chat. The Industry 4.0 Club hosts conversations on Tuesdays and Wednesdays, alternating topics around women in manufacturing, the future of manufacturing, fireside chats like this one, and people, process, and culture. If you like these, please join us, or please find us on LinkedIn at our LinkedIn page and also at our website at www.industry40club.com. And we hope to see you again at a future broadcast. Anyway, Tim, thanks a lot for joining us, and I wish everybody a good rest of the day.

Thank you.