“At DSI, we look at digital twin, it’s not an end game, it’s really an evolution. You can think of it as the next generation of continuous quality improvement. It’s not something you can buy a piece of technology, your piece of software, install it, and boom you’ve got digital twin. Digital twin manufacturing is really the combination of people, process, and technology.”
Digital Twin IoT (Internet of Things)
What is Digital Twin? Digital twin is a process that involves digitizing your entire manufacturing facility. By creating a digital copy of all the processes, parameters and other factors of your facility, digital twin technology can then alter variables and see how hypothetical situations could turn out.
All of these variables are addressed in real-time to help engineers monitor the production line and facility operation. If there are any errors in the manufacturing process or inefficiencies in your equipment, the digital twin can identify them and immediately troubleshoot the problem. This allows you to see a potential solution to the issue, saving time on maintenance and emergency repair issues.
Digital twin is just one exciting development possible through the Internet of Things, or IoT. Industrial IoT and Industry 4.0 use digital twin as a synchronized system of digital improvements. The process of gaining meaningful data, interpreting it and delivering it to key personnel allows your facility to operate at peak efficiency.
Don’t let data sheets, charts and figures obscure the bottom line of all this monitoring.
Your current production facility is loaded with information that can help you improve its efficiency, but interpreting this data often proves too difficult and time-consuming. Digital twin offers visualization features that help this data come to life. See first-hand what it might look like to alter a single variable or make a major adjustment to your facility. These adjustments all happen digitally, so the risk is avoided if an adjustment proves to be inefficient.
Manufacturing Possibilities Using Digital Twin Technology
What do your customers think of your products? How are your products being used, interpreted and compared with your customers? These questions often go unanswered in the industrial manufacturing world. Through digital twin IOT, you can access an essential data stream of customer information and insight. This allows you to better adapt your products and services to meet your customers’ needs.
Digital twin can also put efficiency suggestions directly into the hands of your engineering team. Instead of operating your business as usual, your engineers can use the twin of your production facility to test out new options and identify inefficient points in your current setup. These can be maintenance issues, organizational issues or operational parameters.
Take much of the risk out of innovation. Instead of turning your facility into a laboratory where your engineers test out new solutions, use a digital model of your facility instead. Digital twin gives your team the resources necessary to experiment freely without worrying about actual hazards or productivity risks.
Digital twin combines seamlessly with other industry 4.0 technologies to keep your manufacturing facility at the cutting edge of productivity. Our team at Design Systems can assist you with implementing this and other innovative strategies to collect, interpret and act on data already in your facility. Visualization and prediction features allow this data to spring to life and assist you in managing your production line.
Create an Agile, State-of-the-Art Manufacturing Process With DSI
This is just the start of how the Industrial Internet of Things (IIoT) can accelerate your manufacturing process. At Design Systems, we offer the latest convergence of information and operational technologies. Contact us today to learn more about how we can update your facility and provide you with the full advantages of industry 4.0 and digital twin technology.
DSI at the Automation Alley Tech Takeover on 1/29/2020. DSI had a panel of experts discussing the steps to building a digital twin and as well as the ROI that can be expected.
Transcription of Video
…I want to talk a little bit about Design Systems so I was tooling around on their website yesterday and I happen upon the projects section and it was really taken with the way that they set up the projects in the use cases that they present. So the projects section has a bunch of stuff on a recent aerospace process valuations health care management distribution material handling impacts raise all kinds of information across a wide variety of industries.
And under each project, they start by outlining the challenge. And I thought that was such an important thing to do. It’s easy to get overlook that. My team is probably super sick of hearing me say okay so what’s the primary goal here this is what we’re doing what’s our primary goal what is success look like and so it was a nice easy way for people to access and say “Hey I got a problem similar to that”.
So they start with outlining the problems and then they give a quick snapshot of the solution. Some had numbers, some had a description of what a positive outcome looks like. It really helped set up “here’s my problem, here’s what the solution can look like”.
And then the third section there is what makes their particular solutions. Yeah, and it was full of numbers, right, because we all want to know what’s the implication on product, on our process, our sales, on our bottom line, what are the actual outcomes that I can anticipate seeing.
So, everybody tuning in via live stream I would welcome you afterwards, and anybody here as well to hop on their website and check out their projects section. It was a really nice easy implementable way of laying stuff out.
We work with a lot of companies that think digital transformation is a big mushy concept. It’s super scary, I don’t know where to turn, I know what’s coming, I just don’t know where to start. And that’s why companies like design systems can do such an important job of helping guide you through that process. Breaking down into bite size pieces, take out one problem at a time, one project at a time, and then you’re actually gonna be able to move forward.
Find a technology partner that can decide if there’s a technology out there that can solve it, whether it’s digital twin, or machine learning, whatever it is, even if [that technology] was only a part of it [the solution]. Figure out what a positive outcome looks like. Mitigate risk when possible, and then take a stop, try it what a shock.
So with that I’m gonna get off my soapbox end and introduce Amanda Moore. It’s my absolute pleasure to introduce her. She is with business development with the outside. And with that I will turn it over to me.
Amanda Moore: Thank you Kristin. When we were planning this presentation due to the nature of the tech takeover we were very conscious to keep a very technical and not sales. So thank you for that wonderful sales pitch for us.
So when we were putting this presentation together what we were trying to keep in mind is let’s address the questions that we are hearing out in the field. It’s very easy to plan a digital twin when you have a Greenfield area brand new factory, thats a piece of cake.
What do I do though with all my legacy facilities, and how do I protect this beast, and more importantly what do I get out of it, is there a return on investment for this, are what we’re going to the things we were planning on.
So, a brief introduction of Design Systems. Kristen did a wonderful job kind of going into the details, but a little bit about the statistics. The company is a privately held program management and manufacturing engineering firm which we started in 1983.
Today we have almost 300 engineers and technical support personnel. Because of the consultative nature of our business model we really spent a lot of time getting to know our customers and establishing long term relationships.
We understand where we can be of value to them and kind of where their challenges are. We have been an award winning firm over 37 years, and yet in operation we have been recognized by both OEMs, you know, for supplier awards and also by publications such as engineering news record. We are in the top 50 of our program management and also manufacturing design, and this year we were added on to the cranes tap 200 private firms.
We are headquartered in Farmington Hills, but due to the nature of the automotive and manufacturing industry we have developed a a global footprint. We do have an office in Canada and Mexico so we can be boots on the ground around North America, and we do provide solutions all over the world.
So the company is made up of 6 core engineering groups: our core capabilities, and then our program management team, so for each of our engagements we will look at what the specific problem is, or what the solution is.
The […] together gather the appropriate SMEs from each one of those groups. The program management then puts together this team specifically for that project. Being in Detroit we started out in the automotive industry. For over 37 years we have expanded into virtually every aspect of manufacturing and now we have a great deal of of conveyor expertise ,so we’ve now moved into baggage handling package and parcel handling, working with firms such as USPS and FedEx.
Because we work in so many different industries with so many different clients we have a wide variety of expertise. We work with virtually every type of design and engineering software out there…Now you’ll see, you know, if we range everything from OEMs to your small manufacturing companies with one or 2 plants it’s a wide variety that we work with.
So let’s look into this industry 4.0. Since this is an Automation Alley presentation I thought it would be appropriate to define our capabilities in the area by the outline of Automation Alley. […] Where we fit in, yes, in the modeling simulation, visualization, and immersion, this whole idea of doing the design and testing in the concept phase, in the virtual world before anything is done in the in the physical world.
Definition of Digital Twin
The digital twin, […] our definition of it is the virtual duplicate of the physical operations. And for some people that’s just looking at, you know, the statistics of what’s happening on the shop floor, what is each machine doing, what’s our throughput.
Just kind of that dashboard of what’s happening, we really expanded that version into a complete smart model. So it’s not just the operations of the individual machines, let’s look at the facility assets, all the data in there, what our vision is really to create […] of a single source of truth for the entire plant, digital twin of the entire facility.
And what this is going to do then, is to set up a set you up for future technologies such as machine learning, or artificial intelligence. So, in looking at art when talking about digital twin we recognize there’s actually 3. Digital twins are the first one, being the product the journal twin, and we have been utilizing PLM. Really proving out the concept of virtual design and design validation testing. We’ve been doing that for decades. Say with the PLM tools, and now with such things as generative design.
And now we have the tools such as the 3D laser scanning, 3D modeling, 3D simulation. Use that same concept or virtual design, testing and validation are done before anything is done on the shop floor. And then for their digital twin as part of project performance or the customer relationship…but we’re going to focus today on the manufacturing digital.
Challenges for Legacy Facilities
So, what are some of the challenges that legacy facilities have. Got a 30 year old plant. What are my problems? Well the first thing is rarely do you have accurately […] and before you can create this digital twin you need to have that actual data. Could be decades old, all of the changes that were made to the plant.
Maybe you have some new system support, and maybe an addition on the plant. Or you’ve gotten new drawings, or new installation documents, or whatever. But really is everything kept up to date?
One that is also drawing challenges for a long time is schools have not been doing teaching in 3D. It’s really becoming a challenge for people to understand […] what’s missing out there. I’ve actually seen a letter plan rooms that are even much worse than this one.
So you’ve got drawings all over the place, and you’ve got data, data silos, and on an asset data, and so forth, all over the place. It could be a different department, you could have maintenance has some records, you’ve got installation drawings here…just silos of data everywhere.
A lot of times you don’t know what is missing. Over the course of the plant or the operation of the plant. You’ve got change over in personnel, change over in equipment, lots of changes that have been happening on the shop floor.
Personnel and Institutional Knowledge
Another challenge that people are looking at now, you’ve got this layer of senior level personnel both in engineering and operations, in management. These guys that have been there 30 years they know everything about the plant. They know that you know this particular machine goes down by the way the floor it gets a little bit […] a northwest corner of the plant. All that institutional knowledge is going to walk out the door when they retire. So how do we start documenting all this stuff before that happens?
This kind of product, not having everything documented, and not having a single source of truth really puts us into a reactive as opposed to proactive mode. If a machine goes down what we do? somebody calls in sick, what do we do? our suppliers not delivering… everything is reactive.
Trial and Error on the Shop Floor
And then there’s also a lot of trial and error on the shop floor. There’s a new piece of machinery coming in. there’s a new product being developed, all that’s been done, you’re kind of in in trial and error mode.
So we actually had this this problem. It really exists for everybody from a small company that has one or 2 maybe shops, or we recently were contacted by it, yeah, and they said our leadership has said we need a plan for digital, a digital twin. Where do we start?
Really, it’s an issue that everybody is grappling with. So the first thing is to bring it up to the corporate. The corporate vision of what is digital twin for you. Are you going to look at these, you know, higher level technologies such as AI or machine learning? are you just simply trying to put everything in 3D. What is really your vision? and I would venture to say everybody would have a unique vision of what the idea is.
We look at digital twin, it’s not an end game, it’s really an evolution. You can think of it as the next generation of continuous quality improvement. And this affects… it’s not something you can buy a piece of technology, your piece of software, install it, and boom you’ve got digital twin. it’s really the combination of people, process, and technology.
With this new technology you need to change your processes from the 2D to 3D. Products are pretty workflows in order to get the value out of the new technology. It’s important to note that the odd to look at your personnel, what new training do you have to do, maybe you need to have some some new […]
Even some new designations such as somebody is in charge of data, somebody’s who’s in charge of your your […], identify use cases. We start incrementally. the biggest thing to do that, thank god, yes, we have to be able to implement this without interrupting existing operations. You can’t shut down a plant to implement this.
How do we do it along with our day to day operations, and your […] you can do that for use cases. Let’s figure out one small problem that we have. You’ve got one specific line that we just have horrible throughput on. How do we address that, how do we figure out their problems.
And as I say, really a very flexible approach with each one of these use cases. Let’s define what they are, what we’re going to get out of it, and how do we implement.
The Evolution of Digital Twin
So as you go along with the evolution of the digital twin you’re adding capabilities. And we look at it in kind of stages. The first step is to create your standards. You have the standards for, yeah, what constitutes the assets. […] for the data are what constitute the assets. And going forward, every project going forward, we utilize those standards. So once again we’re building that on, this oncoming digital twin…