Factory 2050
@imveurope
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Factory 2050 is the first building to be completed on the University of Sheffield’s advanced manufacturing campus
swallow the initial period of gathering data, in order to benefit further down the line. ‘Tere are a lot of different aspects in
aerospace that want to [use AI and] jump on this bus,’ Edge said. ‘But the first person who jumps on the bus has to buy the bus. Tat’s one of the barriers to entry.’
Connected factories ‘All this digital data is going to become more prevalent moving into the next generation of aircraſt,’ Edge said. Aerospace factories are investing in Industry 4.0 and connected manufacturing, just like many other industries. Tis applies even to older machinery. Te
AMRC has a demonstration lathe on which it has installed various sensors to measure carriage position, spindle vibration, motor current temperature, and other variables, all of which is collected on a Raspberry Pi. All of AMRC’s partners have lathes and machinery like this still in operation in their factories, and they don’t want to change that, Edge said. Te data can be used to tell the shop floor manager which machines are running, which are idle, along with uptime and cost efficiency. Te sensors also give an idea about how well the machine is running, allowing engineers to carry out maintenance before it breaks down. Te sensor system was put together for a few
hundred pounds worth of hardware, Edge explained, built in an open-source network GUI. Another smaller, three-month project,
We can say what the barrier to entry is. It’s then up to Rolls-Royce to decide if there’s a business case
currently underway for Rolls-Royce, is designed to show how machine vision can be used to distinguish between components. Te parts are very similar in appearance, apart from one or two features like the placement of a bracket or the number of holes, which makes them difficult to tell apart by a human operator. ‘We can say what the barrier to entry is,’ explained Edge. ‘It’s up to Rolls-Royce to decide if there’s a business case for the technology.’ In this case, AMRC is using a 30-megapixel camera supplied by Multipix Imaging, which is over- specified but useful for this proof-of-concept work. ‘Tis is an area where our relationship with Multipix has helped us out,’ Edge said. ‘It allowed us to do these types of operation pretty quickly.’ Another type of technology
that AMRC is working with extensively is virtual and augmented reality, showing how commercial headsets can be used for plant simulation, assembly, training instructions and other functions to save costs. In the construction industry, for example, AMRC has converted electrical wiring instructions into an AR overlay to highlight which terminals should
10 Imaging and Machine Vision Europe • Yearbook 2019/2020
be connected to each other. Te technology prevents mistakes, Edge said, and is far more cost effective than having to train an engineer to wire different types of cabinet – instead, upload the right cabinet make and the engineer follows the AR overlay instructions. ‘Overall, machine vision is of massive
interest in UK manufacturing,’ Edge said. He feels one big issue companies oſten have is that machine vision is fitted retrospectively and trying to work around other areas of manufacturing. ‘All these machine vision problems would be a much easier job if you had a dedicated space to do it in,’ he said. ‘We’re still growing,’ Edge concluded.
‘Inspection is so critical in aerospace; everything is inspected, a lot of which is still manual and can be improved on.’ O
PPMA show The AMRC presented a 3D imaging demonstrator at the PPMA Total Show in Birmingham at the beginning of October 2019. The equipment on display included stereo cameras, time-of-flight cameras and a 2D camera setup for 3D imaging. ‘There are a few different areas we’re looking at, and how the application transfers to industry, whether you can do fast metrology and fast 3D inspection using cheap 2D and 3D cameras,’ explained Kieran Edge, technical lead for machine vision, Integrated Manufacturing Group, at AMRC. This includes CAD-based matching and 3D deep learning.
University of Sheffield Advanced Manufacturing Research Centre
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