Watch IONA in action

Introducing IONA

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“Our vision is that robots need to gain an awareness of the environment that they’re operating in. And this can allow them to self adapt and self correct for the natural process variation that exists, but also allow them to better match the digital simulation or the programmed intent for that process. We believe that by combining sensing systems with industrial robots, we can generate the data that’s going to be needed to provide this context to automation that doesn’t currently exist.”

Ben Adeline, CEO Insphere

My name is Ben Adeline, I’m the CEO at Insphere.

Manufacturing’s on the brink of change. We’re seeing ever increasing demand for more output but this is coupled with ever increasing resource scarcity, both in the forms of energy that it takes to produce our products, but also the raw materials that goes into them. The current process of manufacturing can be incredibly wasteful. It risks over supplying the market]due to the rigidity of manufacturing, and it doesn’t have the flexibility to increase and decrease output as demand dictates. The way that automation is currently used has remained much the same for the past 40 years or so. It’s based very much on repeatable processes. So automating a single task, or automating the production of a single product, that doesn’t change over many years. This is no longer conducive with ever shortening new product introduction cycles, or even the level of customization that consumers are now demanding from their products.

Our vision is that robots need to gain an awareness of the environment that they’re operating in. And this can allow them to self adapt and self correct for the natural process variation that exists, but also allow them to better match the digital simulation or the programmed intent for that process. We believe that by combining sensing systems with industrial robots, we can generate the data that’s going to be needed to provide this context to automation that doesn’t currently exist.

Our mission is to generate the data that can be used to drive industrial automation and manufacturing itself, enabling automation to become more accurate, more flexible, and more autonomous, in its operation.

So we’ve created IONA as a sensing system that can generate the data that can then be combined with artificial intelligence and machine learning to feed back into this automation infrastructure, to create this step change in manufacturing that the future is going to demand.

With IONA you can also increase the accuracy of a process. This means that many more processes can be automated or existing automated processes can be improved in terms of their quality.

By combining sensors with industrial robots, we’re able to create a much more productive manufacturing system. This will reduce the amount of materials that it takes to produce our products, as well as reducing the energy inputs required. This will help manufacturers meet the needs of output required by society, as well as being better for the planet in the long term.

At Insphere we’re excited about IONA being at the heart of this digital transformation.

 

IONA - An Explainer Video

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IONA is a network of sensors designed to monitor and control industrial robots. The system can monitor the movement of the robot but also the relationship between the robot and the fixture or work object that it’s performing a task on.

IONA is a key enabler to support the digitization of automated manufacturing.

IONA is a network of sensors designed to monitor and control industrial robots. The system can monitor the movement of the robot but also the relationship between the robot and the fixture or work object that it’s performing a task on. The system consists of a series of nodes. These are simply mounted on automation cell guarding around the periphery of a robot cell. And they’re able to capture data from lots of different line of sight meaning that you can continually monitor a process as that process is running. The nodes themselves don’t need stable mounting. They can resect their own position in space so they can be mounted simply on the cell guarding itself. To connect the series of nodes. It’s a simple Power over Ethernet cable. So one cable that provides the data interface but also the powering to the node. This makes installation and setup of the system very simple and can be done in a short space of time. The sensors themselves measure small retro reflective spherical targets. These are passive targets and don’t need any cabling to connect them. These targets can be placed at strategic points on the robots or on the fixture that the robot is working on, or even to represent the cell datum structure. From the targets we’re able to construct 3D coordinate frames. Within our software then we can track how these frames move and also the relationship between the various frames that we’re monitoring.

The data from IONA can be used at three key stages of manufacturing.
>It can be used at the commissioning stage to correct for the differences that occur between the simulation or the offline programme and the physical setup of the cell. This data can also be used to feed back into the digital environment to update the digital twin, meaning that there is an exact replica in the digital world as operating in the physical world.
>The second stage that we can use this data at is as a process enabler to increase the accuracy of an automated process.
We can do this in a number of ways. We can achieve a better alignment between the work object and the robot itself but we can also use our data to perform a calibration in situ on the robot. This calibration can be run as a one off when a cell is first set up, or it can be run each time a process operates.
We can also use our data as part of a live feedback loop. So the process is continuously correcting and iterating based on the alignment or repositioning of elements within the cell.This can improve the dynamic accuracy of any given process.
>The third stage, when we can use our data is as part of a process control approach. By continually monitoring a process over time we can start to spot the trends in the data and understand whether our process is about to drift out of control. Corrective actions can then before it produces a bad or incorrect part.

The IONA system consists of both hardware and software. The hardware is the series of nodes, the controller, the targeting everything that’s required to capture the data.
The IONA system also consists of our software, our ORA platform. ORA is used to collect the data and also perform analysis before feeding that data back into the system. Within ORA we can perform a number of tasks.We can create a realignment between the work object and the robot.

We can use the data that we capture to update the programme to correct for any inaccuracies. And we can capture data over time to monitor the performance or trend of an automated process.

The IONA system is robot agnostic.We can work with any robot, be that a KUKA, or ABB, a FANUC. The things that change may be how we interactand pass data to the robot controller.

With IONA we can reduce the commissioning time involved in first setting up a cell. We can provide a more consistent product quality and ultimately we can ensure that the process consistently matches the designed intent.

Interview with Andy Silcox, Research Director AMRC Cymru

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“IONA is a great example of some really exciting new technology that is coming to market that will help revolutionise the UK Manufacturing for the future” 

Andy Silcox – Research Director at AMRC Wales

So IONA is a great example of some real exciting new technology that’s coming to market, that will help revolutionise UK manufacturing for the future. I’m Andy Silcox, I’m the Research Director here at the AMRC Cymru. 

The AMRC Cymru is here to de-risk new manufacturing technologies, for Welsh Manufacturers. So across all sectors from the aerospace, to the food and drink industry, to the medical device industry. We provide an agnostic test bed for businesses to come and try new technologies. We can show automation and use on representative examples, and just show you the art of the possible really. So the big trend has been across the manufacturing community for a number of years now, and that’s Industry 4.0. In essence, it’s around the use of data and digital manufacturing tools to make our production facilities more productive and more sustainable. 

The combination of industrial robots and sensors is a key trend moving forward, and will help make those robots more intelligent which will benefit the overall manufacturing system. Automation and simulation tools have been around for a number of years, but in the case of simulation in particular, it provides a snapshot of what’s happening on the shop floor. What we want is a real-time representation of what is happening on a day-by-day, hour-by-hour basis. And so what we’re looking to do, is to bring data directly from the shop floor into those simulation models. So we’ve got a living, breathing digital twin of the production facility.

 IONA gives us the ability to capture data on the shop floor and feed it back into those simulation models in real-time. So that gives us the power to be able to validate the production process as it’s happening and not waiting for the production process to be finished and conducting a non-value added, secondary inspection operation at the end of it. IONA is really interesting from the point of robot control. So robots are repeatable, but they’re inaccurate. So that requires a lot of setup time before starting the task. 

IONA will allow us to validate the robot position and its performance, and it gives us greater flexibility in its use. Industrial robots have been around in our factories for 40 years or more. But their natural home has been in car plants or factories like it, where there is high volume and a large amount of repeatability. There seems to be a demand for greater customization of product, and for greater variety in the product range. And therefore, the automation needs to be more flexible.

 IONA gives the ability to change the function of the robots, quickly and easily. And we believe that’s more conducive to the future of manufacturing in the UK. The majority of defects in products aren’t found until the end of the line. If we can find those defects at points of origin, then we can avoid a lot of wasted work and effort.

 What IONA allows us to do is monitor the process, as it’s happening and be able to then feed that back, either to A, stop the process and restart or feed back into the system, so that corrective action can be taken, as we go along. So IONA is a great example of some real exciting new technology that’s coming to market that will help revolutionise UK Manufacturing for the future. It gives us not only the ability to validate the production process as it’s happening, but it also allows us to combine it with robotic technology to make those robots more intelligent and get better data from the shop floor.

Additive Manufacturing Application at AMRC Cymru

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“We see IONA having an integral role in the future of advanced manufacturing.” James Allum, Senior Manufacturing Research Engineer AMRC Cymru


We see IONA having an integral role in the future of advanced manufacturing. My name is James Allum. I’m a Senior Manufacturing Research Engineer here at at AMRC Cymru.

My role is in additive manufacturing and design, with a particular focus on large format additive manufacturing with the AI build system and the IONA system. We’re developing a large format additive manufacturing capability, which is supported by the IONA system for verification and validation. We’re aiming to take this capability forward to be able to print large format additive manufacturing components,for both end-use tooling and similar capabilities in the future.

So, the advantage of robotics in additive manufacturing is that we’re able to develop complex structures and we have the flexibility to develop a range of different geometries, planar and non-planar. A particular challenge with large format additive manufacturing is the long build cycles. Obviously the larger the part, the longer the print time, which means we give rise to increased risk of losing those parts and losing and wasting time and material.

Of course, robots are typically used for repeatable processes, and may lack the accuracy for one-off manufacturing processes. Whereas, with IONA, we’re able to capture the data that makes the process accurate, and not just repeatable.

So with the IONA system, we’re able to monitor in real time, which means we’re able to collect data that we can compare back to our CAD data or our G-code data. This enables us to validate the process before committing to printing with filament. It also enables us to monitor the process as we print in real time, or monitor potential risks of failure during printing. My experience of the IONA system is that it’s been very simple to use. You require no prior metrology knowledge. It’s a plug and play system,
it can run for 24 hours a day, which means we can break between prints and monitor things and it’s running in the background. It’s ready for us when we need to make use of it.

And we’ve had fantastic support throughout from INSPHERE with both training and setup. Large format additive manufacturing has a very integral role moving forward into the future of advanced manufacturing. The IONA is an integral system that can support that going forwards. The advantages potentially are, of course, with validation, verification, and it gives potential great confidence to those processes
as we move towards looking at advanced manufacturing.

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