Find the Power of Your Data: Harnessing Innovation for Autonomous Smart Manufacturing

Transcript

Stan Miller: Hello everyone and welcome to ROK Studios. I’m Stan Miller, I’m the PR & Analyst Relations Manager for Rockwell Automation in the EMEA Region, and I’m here with Ashkan Ashouria, he’s our Product Manager for Digital Solutions including IOT in the EMEA Region. Ashkan, welcome to the studio.

Ashkan Ashouriha: Thanks for having me. Thank you.

Stan Miller: It’s so good to have you here again. We’re here to talk about finding your data’s power and harnessing innovation for autonomous smart manufacturing. This is a huge topic, so I’m looking forward to this discussion. So, let’s get into it. To start, how has the evolving landscape of smart manufacturing affected the way companies approach the role of data in their operations?

Ashkan Ashouriha: I guess this the core question, right. So, think about when the industry starts to think about a smarter way of doing manufacturing, cost manufacturing. There was a lot of ideas, but once you have an idea, you’re trying something and you have a lot of lessons learned and you’re trying to repeat. So beyond now, at the end of the day, at the end of one of the first cycles, there’s a lot of lessons learned, dos and don’ts. 

Nearly a decade ago, people thought to say hey, data is in the oil to data mining, but nobody said what to do with that, right. So, it means a lot of people, OEMs, end users, created a lot of data, and that’s it, right, because they want to be on time but nobody really told them, hey, maybe you should first think why you need the data, right. So, it means – and the myth of one of the biggest lessons learned of the last ten years is you should have a data strategy, right. 

The strategy means really which type of information you need from a sensor. Do you really need a sensor or do you need a different sensor, those kinds of things, for your ultimate goal. So, this brings me to my favorite topic, you have to do reverse brain storming, means you have to say okay, this is my ultimate goal, this is my goal, but digital transformation is not your goal, it’s your toolset, right, you’re using it to reach a goal. 

For example, you’re looking after higher true put, OEE, increasing OEE, okay, that’s a goal. It’s not digital transformation, that’s a goal. Digital transformation is how can you get there, and then you have to understand where you are, then you have three bullets at the end of the day, and then you have to start to connect them. So, okay, I’m here, that’s my goal, those are the toolsets, let’s go.

And then you need a data strategy because otherwise you’re investing a lot of money and time and resources, and in the end, you learn oh, okay, that wasn’t what I was looking for, right. So – and you know, nowadays once you’re doing that, you’re investing, you have to go to your board and say hey, this is what we missed, and we don’t have the data started, this is hard to achieve, let me say it like that.

Stan Miller: Yeah, so pursing – not pursing digital transformation for digital transformation sake, but focusing on the outcome, if I’m hearing you correct, makes sense. So, let’s talk about in the context of smart manufacturing, what are some of the key challenges that manufacturers face in transforming that raw data that you were talking about, right, into actionable insights and how they can effectively address those obstacles?

Ashkan Ashouriha: So, the first challenge is don’t try to do everything at the same time, because you’re losing control, you’re losing to trust in the company and you’re losing trust to your own strategy because when you try to do everything at the same time, you can imagine that can’t be successful, right. You have a lot of cases, okay, no, this won’t fly maybe in the next five years, we can’t do that. So, this is your first thing. Second one is really tell your people, tell your employees why you’re doing this, so we have all this discussion. 

Again, a lot of lesson learned, around talking to CIOs, CEOs, those type of roles, okay. We started to do that because there was pressure, we have to do something. But they didn’t say okay, we should maybe talk more to the people, tell them hey, we’re doing this not to replace you with your job, we’re doing this to secure your job, right. 

Because otherwise, maybe our competition, that means companies of the customer, will do maybe a better job, hire a better integration. So, we are running in a competitive situation globally and you have to have a healthy view, let me call it like that, on what you’re doing. So, talk to your people, say hey, now we are bringing that specific solutions into the cloud because we believe this is helping you with your daily job. 

And if you look into the messaging during the pandemic, it changed from digital transformation, digital transformation to more hey, digital worker, right. How can we help the workforce really onsite, in front of the machine, the operator, the maintenance people. So, that’s one of the lessons learned in behind. And the last one is really, again, you need a data strategy, that’s the huge point because again, from sensor up to the cloud and the outcome, how does it fit together.

Stan Miller: Yeah. Makes sense. Ashkan, you spend a lot of time talking with customers, understanding their challenges, their opportunities, and also their successes, right. So, at a high level, we don’t necessarily need to name drop anyone specifically, unless you want to, but can you share a real world example of how the integration of IOT, digital twin AI or other emerging technologies have driven significant improvements in efficiency, business outcomes or business outcomes for manufacturers.

Ashkan Ashouriha: So, the biggest successes are really those where the customer had a specific problem, issue, challenge, call it whatever you want, and really strived to specifically focus on that, not more. So, there is one that was on the early days when we started with our journey of the Connect Enterprise. So, I supported that for my side and it’s still one of the most impressive one. 

So, there was a company working on paint shops, right, and I said hey, we have a lot of robots, we’re doing this and they have to have a better flexibility number and higher quality. Said hey, for that, we did a lot of investments in robots, right, all the paint shops are robots and high speed cameras. You see, the thing is, they wanted to use the high speed cameras to make a lot of ultra speed photos about the nozzle of the robots, where they’re really pushing the paint “fork” into how is it patterned, how does it work? 

We got terabytes of data from one robot, not all of them, because too much data. Again, no data strategy back in the days, right. So, I said okay, here it is, right, this application, here is terabytes of data. So, we worked internally with our server system department, said hey, how can help the customer. I mean, we desperately need some data science people look into it and we find a lot of patterns, right, the way the movement, the pressure, the paint itself, do we have to change something. 

So, this was mind-blowing, right, we helped the customer really with that, and they’re still using those outcomes to modifying, optimizing the brown field and looking more into the green field applications. Okay, this is what we will give to our OEMs, guys, look, this is our standard, you want to have this to optimize because think about it, higher quality means you don’t have to rework, right, so it means a lot of energy savings.

And if your paint shop or paint job is better quality, it is sustainable as well because – right. So, you see, there is a lot of dependencies where back in the days we didn’t solve it and today say, a lot of dependencies. So, we already solved the problem but now, we think oh, okay, there was – so, there was really two different topics, key drivers for the customer, now we are connecting together.

Stan Miller: That’s a great example. All right. So, earlier in our discussion, you mentioned work force, I’d love to circle back on that a little bit. How can manufacturers ensure that their work force is adequately prepared for the transition to data driven autonomous smart manufacturing in an environment, and what role does upskilling play in that process?

Ashkan Ashouriha: There are different challenges since you have a wide range of – let me say generations in the people. So you have the younger people, they are the bones, the baby boomers or whatever, right, different – you have to find a common sense how you are bringing those values, because from the customer standpoint, those are values, they’re investing into it, right, we’re bringing that to the customer. And so, this is this. 

So, we always saying to the customer, again, be transparent, right. So, bring them in and say hey guys, look, this is, for example, this is your smartphone, your tablet, helping you to get information, not but because we want to track you, but that’s helping you, right. 

You’re replacing paper, replacing maybe different versions from one would document, if you talk to the quality people, you’re learning a lot, and this is one common sense, what is a quality target, for example, for product XYZ. So, that’s what we really try to talk to the customer, say hey, okay, you have specific roles, specific focus again, like a matrix, and how we can really help the customer. And this is bringing me to our own heritage, right, scalability is our DNA, right, and this is helping us a lot. 

Because we have to say, okay, this is the small version – or if you want – maybe this is easier. If you want to have t-shirt sizes, right, so you have the XS up to 5XL, but it depends on what your role is and which kind of support – let me call it digital support you need for your daily job.

Stan Miller: Got you. Tailored approach, that’s clear. All right. Last question for me and that’s about – you know, let’s talk a little bit about – you know, as industries continue to embrace smart manufacturing, what do you envision as the next frontier in leveraging data and technology to further optimize production processes and accelerate transformation in industry?

Ashkan Ashouriha: You already see the smile on my face because if you look into the news, everybody’s talking about ChatGPT, right, AI, and OpenAI, those kinds of things. Is this new? No. And again, we use that for the customer with the paint shop. Understanding what it is, where it can help me and losing those 90% of fear, so we had a lot of discussions with customers during the last fears and they asked, hey, where do you see that? 

So, thinking about how we can leverage those capabilities from a modern AI and let me collect that, in the manufacturing area. Because the scary part is, that example with ChatGPT is connected to the internet. Every piece of information that is publicly available is connected to it. Do you want that for production? I guess no. But the toolset itself, that technology, those capabilities, could be used in an isolated environment to help you say hey, okay, this is my production, tell me, can I reach my goal; if not, what should I do. 

Just as an assistant, it’s like you’re asking your Alexa, whatever, Siri, whatever system you’re using, hey, what is the next sushi restaurant, I love sushi, give me some suggestions. This is the same thing, right. So, it is just helping you, it’s not doing your job, it’s helping you, right. And from my personal view, I did some tests with this, okay. Hey, when I want to talk to sales or talk to a customer, what is the easiest way to talk about the specific technology? 

As a techy, it’s sometimes hard to do. And those answers were good. So, it helped me to rethink my approach. I said okay, maybe this is because the system gave me very easy understandable language, so okay, you can use those bullets, okay, I will take that one, that is good, right. Just as an assistant, take it, right, and lose the fear of it. So, you know, we’re talking about AI since – I don’t know, 50 years, but now the people start to see okay, okay, okay, it is the point of no return, right. So, if we use that, that would influence our future in smart manufacturing.

Stan Miller: Ashkan, it’s always a pleasure to have you in the studio. Thank you so much for joining us today.

Ashkan Ashouriha: Thank you very much for being here.

Stan Miller: And thank you for watching. If you’d like to learn more about Rockwell Automation’s software solutions and IOT solutions, visit www.rockwellautomation.com.