News

Isothermal Technology Ltd (Isotech) has been providing temperature calibration solutions since 1980, clients vary from National Metrology Institutes to calibration engineers working on-site.

ISOTECH – Solutions for all levels of temperature calibration

Many nations rely on Isotech for their Primary Standards.  For example metrology furnaces are used to melt and freeze pure metals providing a fixed temperature (ITS-90 Fixed Points) in order to calibrate standard thermometers. Accredited laboratories use Isotech Stirred Liquid Baths in which thermometers under test are compared to standard thermometers. In industry portable heat sources such as ‘Dry Block Calibrators’ can be used for calibration and Isotech produce Dry Blocks covering -100°C to 1,200°C.

Isotech see a demand from customers at all levels for greater accuracy and additional functionality. In recent years Isotech have launched innovative thermometry bridges and precision thermometers along with patented ISOTowers – which realise ITS-90 Fixed Points in a new way.

Isotech’s New Range of Portable Calibrators

Nine New Models – Each Available in ADVANCED, Site and Basic Models – New Styling – New Features – New Software – Enhanced Performance

Isotech has updated nine of its most popular calibrators to bring new styling and updated features. Each model is available in three different versions from a cost effective heat source to fully featured devices which include a three channel temperature indicator, temperature logging and Ethernet interface.

This new “4000 Range” spans -45 to 1,200°C with models that can be used as Dry Blocks or Stirred Liquid Baths with options for infrared thermometers, surface sensors and even to operate ITS-90 Fixed Point Cells.

“Our customers, who range from the worlds’ leading National Laboratories to site engineers have long valued the accuracy and quality of our equipment. This new range is a response from customers demanding modern styling and more features such as more input channels, advanced logging and an Ethernet interface. We are proud to meet this demand in a new lighter and stronger rugged case.”

The 4000 Models use the same proven, reliable isothermal volumes as the earlier Isotech calibrators whilst benefiting from new styling and advanced features. The ADVANCED versions have three input channels so that both the Standard and the Test Probes can be connected to the temperature read out.  Investment in custom tooling has benefited in making the models both lighter and stronger than before.

Automatic temperature cycling allows the block to step through calibration points whilst logging data. This can be combined with a “Setpoint Trim” feature to ensure the block temperature stabilises at the temperature as measured by the reference probe not the internal control sensor.

In addition to use as Dry Blocks accessories can be added to the lower temperature models that allow up to six different modes of operation

1. Dry Block
2. Liquid Bath
3. Ice Bath
4. Infrared Thermometer Calibration
5. Surface Sensor Calibration
6. ITS-90 Fixed Point Operation

The company has also updated its software with tools to review the logged data, manage setpoint programs and configure the unit.

A new carry case with wheels features a pull out handle that allows the unit to be easily transported.

Reference Chart

Isotech’s reference chart shows tolerances for Thermocouples and Resistance Thermometers along with colour codes and other useful information. If you are in the UK please email to request a free wall chart.

Innovation, Support and Temperature Training

Isotech has been pioneering the latest developments in temperature calibration from Primary to Industrial users for over 30 years.  Contact Isotech for further information, free advice or to arrange free on-site demonstrations. Isotech also run regular training courses, both on site and in Southport with hands on sessions in the laboratories.  For more information visit the website or call to speak to with the technical sales team.

Isotech

E: info@isotech.co.uk

T: 01704 543830

www.isotech.co.uk

For all our technological advances, nothing beats evolution when it comes to research and development. Take jumping spiders. These small arachnids have impressive depth perception despite their tiny brains, allowing them to accurately pounce on unsuspecting targets from several body lengths away.

Inspired by these spiders, researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a compact and efficient depth sensor that could be used on board microrobots, in small wearable devices, or in lightweight virtual and augmented reality headsets. The device combines a multifunctional, flat metalens with an ultra-efficient algorithm to measure depth in a single shot.

“Evolution has produced a wide variety of optical configurations and vision systems that are tailored to different purposes,” said Zhujun Shi, a Ph.D. candidate in the Department of Physics and co-first author of the paper. “Optical design and nanotechnology are finally allowing us to explore artificial depth sensors and other vision systems that are similarly diverse and effective.”

The research is published in Proceedings of the National Academy of Sciences (PNAS).

Many of today’s depth sensors, such as those in phones, cars and video game consoles, use integrated light sources and multiple cameras to measure distance. Face ID on a smartphone, for example, uses thousands of laser dots to map the contours of the face. This works for large devices with room for batteries and fast computers, but what about small devices with limited power and computation, like smart watches or microrobots?

Evolution, as it turns out, provides a lot of options.

Humans measure depth using stereo vision, meaning when we look at an object, each of our two eyes is collecting a slightly different image. Try this: hold a finger directly in front of your face and alternate opening and closing each of your eyes. See how your finger moves? Our brains take those two images, examine them pixel by pixel and, based on how the pixels shift, calculates the distance to the finger.

“That matching calculation, where you take two images and perform a search for the parts that correspond, is computationally burdensome,” said Todd Zickler, the William and Ami Kuan Danoff Professor of Electrical Engineering and Computer Science at SEAS and co-senior author of the study. “Humans have a nice, big brain for those computations but spiders don’t.”

Jumping spiders have evolved a more efficient system to measure depth. Each principal eye has a few semi-transparent retinae arranged in layers, and these retinae measure multiple images with different amounts of blur. For example, if a jumping spider looks at a fruit fly with one of its principal eyes, the fly will appear sharper in one retina’s image and blurrier in another. This change in blur encodes information about the distance to the fly.

In computer vision, this type of distance calculation is known as depth from defocus. But so far, replicating Nature has required large cameras with motorized internal components that can capture differently-focused images over time. This limits the speed and practical applications of the sensor.

That’s where the metalens comes in.

Federico Capasso, the Robert L. Wallace Professor of Applied Physics and Vinton Hayes Senior Research Fellow in Electrical Engineering at SEAS and co-senior author of the paper, and his lab have already demonstrated metalenses that can simultaneously produce several images containing different information. Building off that research, the team designed a metalens that can simultaneously produce two images with different blur.

“Instead of using layered retina to capture multiple simultaneous images, as jumping spiders do, the metalens splits the light and forms two differently-defocused images side-by-side on a photosensor,” said Shi, who is part of Capasso’s lab.

An ultra-efficient algorithm, developed by Zickler’s group, then interprets the two images and builds a depth map to represent object distance.

“Being able to design metasurfaces and computational algorithms together is very exciting,” said Qi Guo, a Ph.D. candidate in Zickler’s lab and co-first author of the paper. “This is new way of creating computational sensors, and it opens the door to many possibilities.”

“Metalenses are a game changing technology because of their ability to implement existing and new optical functions much more effciently, faster and with much less bulk and complexity than existing lenses,” said Capasso. “Fusing breakthroughs in optical design and computational imaging has led us to this new depth camera that will open up a broad range of opportunities in science and technology.”

To improve the safety of autonomous systems, MIT engineers have developed a system that can sense tiny changes in shadows on the ground to determine if there’s a moving object coming around the corner.

Autonomous cars could one day use the system to quickly avoid a potential collision with another car or pedestrian emerging from around a building’s corner or from in between parked cars. In the future, robots that may navigate hospital hallways to make medication or supply deliveries could use the system to avoid hitting people.

In a paper being presented at next week’s International Conference on Intelligent Robots and Systems (IROS), the researchers describe successful experiments with an autonomous car driving around a parking garage and an autonomous wheelchair navigating hallways. When sensing and stopping for an approaching vehicle, the car-based system beats traditional LiDAR — which can only detect visible objects — by more than half a second.

That may not seem like much, but fractions of a second matter when it comes to fast-moving autonomous vehicles, the researchers say.

“For applications where robots are moving around environments with other moving objects or people, our method can give the robot an early warning that somebody is coming around the corner, so the vehicle can slow down, adapt its path, and prepare in advance to avoid a collision,” adds co-author Daniela Rus, director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science. “The big dream is to provide ‘X-ray vision’ of sorts to vehicles moving fast on the streets.”

Currently, the system has only been tested in indoor settings. Robotic speeds are much lower indoors, and lighting conditions are more consistent, making it easier for the system to sense and analyze shadows.

Joining Rus on the paper are: first author Felix Naser SM ’19, a former CSAIL researcher; Alexander Amini, a CSAIL graduate student; Igor Gilitschenski, a CSAIL postdoc; recent graduate Christina Liao ’19; Guy Rosman of the Toyota Research Institute; and Sertac Karaman, an associate professor of aeronautics and astronautics at MIT.

Extending ShadowCam

For their work, the researchers built on their system, called “ShadowCam,” that uses computer-vision techniques to detect and classify changes to shadows on the ground. MIT professors William Freeman and Antonio Torralba, who are not co-authors on the IROS paper, collaborated on the earlier versions of the system, which were presented at conferences in 2017 and 2018.

For input, ShadowCam uses sequences of video frames from a camera targeting a specific area, such as the floor in front of a corner. It detects changes in light intensity over time, from image to image, that may indicate something moving away or coming closer. Some of those changes may be difficult to detect or invisible to the naked eye, and can be determined by various properties of the object and environment. ShadowCam computes that information and classifies each image as containing a stationary object or a dynamic, moving one. If it gets to a dynamic image, it reacts accordingly.

Adapting ShadowCam for autonomous vehicles required a few advances. The early version, for instance, relied on lining an area with augmented reality labels called “AprilTags,” which resemble simplified QR codes. Robots scan AprilTags to detect and compute their precise 3D position and orientation relative to the tag. ShadowCam used the tags as features of the environment to zero in on specific patches of pixels that may contain shadows. But modifying real-world environments with AprilTags is not practical.

The researchers developed a novel process that combines image registration and a new visual-odometry technique. Often used in computer vision, image registration essentially overlays multiple images to reveal variations in the images. Medical image registration, for instance, overlaps medical scans to compare and analyze anatomical differences.

Visual odometry, used for Mars Rovers, estimates the motion of a camera in real-time by analyzing pose and geometry in sequences of images. The researchers specifically employ “Direct Sparse Odometry” (DSO), which can compute feature points in environments similar to those captured by AprilTags. Essentially, DSO plots features of an environment on a 3D point cloud, and then a computer-vision pipeline selects only the features located in a region of interest, such as the floor near a corner. (Regions of interest were annotated manually beforehand.)

As ShadowCam takes input image sequences of a region of interest, it uses the DSO-image-registration method to overlay all the images from same viewpoint of the robot. Even as a robot is moving, it’s able to zero in on the exact same patch of pixels where a shadow is located to help it detect any subtle deviations between images.

Next is signal amplification, a technique introduced in the first paper. Pixels that may contain shadows get a boost in color that reduces the signal-to-noise ratio. This makes extremely weak signals from shadow changes far more detectable. If the boosted signal reaches a certain threshold — based partly on how much it deviates from other nearby shadows — ShadowCam classifies the image as “dynamic.” Depending on the strength of that signal, the system may tell the robot to slow down or stop.

“By detecting that signal, you can then be careful. It may be a shadow of some person running from behind the corner or a parked car, so the autonomous car can slow down or stop completely,” Naser says.

Tag-free testing

In one test, the researchers evaluated the system’s performance in classifying moving or stationary objects using AprilTags and the new DSO-based method. An autonomous wheelchair steered toward various hallway corners while humans turned the corner into the wheelchair’s path. Both methods achieved the same 70-percent classification accuracy, indicating AprilTags are no longer needed.

In a separate test, the researchers implemented ShadowCam in an autonomous car in a parking garage, where the headlights were turned off, mimicking nighttime driving conditions. They compared car-detection times versus LiDAR. In an example scenario, ShadowCam detected the car turning around pillars about 0.72 seconds faster than LiDAR. Moreover, because the researchers had tuned ShadowCam specifically to the garage’s lighting conditions, the system achieved a classification accuracy of around 86 percent.

Next, the researchers are developing the system further to work in different indoor and outdoor lighting conditions. In the future, there could also be ways to speed up the system’s shadow detection and automate the process of annotating targeted areas for shadow sensing.

University of East Anglia (UEA) students are now enjoying a newly refurbished state-of the art Electrical and Electronic Engineering laboratory featuring 36 fully equipped workstations thanks to Tektronix in conjunction with Rapid Electronics.

Located in 320 acres of rolling parkland near Norwich, UEA is a leading member of Norwich Research Park, one of Europe’s biggest concentrations of researchers, serving more than 15,000 students from over 100 countries. The new lab is part of UEA’s recently opened cross-disciplinary learning space – the New Science Building – to deliver high-quality research-led teaching and learning for over 3,000 students annually. The lab is central to the UEA’s engineering and computing sciences curriculum and is used by undergraduates in computer systems engineering, BEng/MEng students in electronic and mechanical engineering, and postgraduate students in both schools.

Under the partnership, Tektronix and Rapid Electronics have provided 36 seated workstations, across two laboratories, allowing first and second year students to perform an extensive range of practical electronics experiments. Each workstation includes the following instruments:

• Tektronix TBS2014, 100MHz oscilloscopes,
• Tektronix AFG1022, 25 MHz arbitrary function generators,
• Keithley 2231A, triple output power supplies,
• Keithley 2110, 5.5 digit digital multimeters (DMM)

“We are very excited at the opportunity to equip the main teaching laboratories in one of the UK’s top electronic engineering universities with Tektronix and Keithley equipment”, said Maria Heriz, Vice President, EMEA Commercial Operations at Tektronix. “Hands-on experience is a vital component in engineering education and by working with the very same tools they will be using after they graduate and move into industry, future engineers can be immediately productive.”

“We want our students at UEA to be well-equipped for the world of work and we’re incredibly grateful to Tektronix and Rapid Electronics for helping to provide our students with the cutting-edge equipment they need to succeed. Tektronix’s investment will allow us to continue to produce leading scientists and help us achieve our vision of transforming science at UEA”, said Professor Mark Searcey, Pro-Vice-Chancellor for Science.

Viktoras Cesnulevicius, a BEng Electronic & Electrical Engineering student, commented: “It’s great to have this new learning space and being able to work with industry standard equipment that will help me develop the skills I need in my future career. This lab is a great addition to the ever-growing science school and engineering faculty here at UEA.”

By providing a condition monitoring test rig for inspecting train wheelsets and gearboxes, Schaeffler is helping a rail operator in Asia to eliminate unplanned train downtimes and minimise maintenance costs.

Local public transport with regional rail vehicles is part of the customer’s core business. Low maintenance costs and high train availability are crucial factors for the railway operator. Any downtime or delays can mean considerable costs and financial penalties.

The Challenge

To ensure the best possible availability, the gearboxes and wheels of all the wheelsets of a train, including its axle and gearbox bearings, are regularly inspected, overhauled or replaced. The customer was therefore looking for a solution that would ensure the reliability and accuracy of checks, while also minimising the downtimes of the trains.

The Solution 

With its special condition monitoring test rig for railway gearboxes and axlebox bearings, Schaeffler implemented a cost effective solution optimised for the customer’s specific application. Schaeffler SmartCheck sensors are simply attached to the components to be monitored using magnets and undertake precise measurements of vibration and temperature without a requirement for further installation outlay. Components monitored include gears in gearboxes, gearbox bearings, wheel axles and axlebox bearings.

The sensors are directly connected via a Schaeffler SmartController to the input and output terminals such as an HMI touchscreen control panel, an external monitor, and alarm and data processing systems. The axles are driven by means of an integrated electric motor for the test runs. In addition, the system can reliably check whether the bearings were correctly mounted, for example, after bearing replacement. Parameters monitored include vibration, temperature, speed and bearing end position.

Customer Benefits

For the customer, the integrated solution for the inspection of gearboxes and wheelsets is an important tool in eliminating unplanned downtimes and malfunctions in rail applications. The investment in the test rig is also significantly lower compared to the cost of complex onboard monitoring systems, which are often used in long distance trains. The customer is also benefitting from the following:

• Reliable and very precise condition monitoring.
• Simple and full integration to the customer’s infrastructure.
• User-friendly and efficient operation.
• Inspection of gearboxes without dismantling and changing the oil.
• Inspection of bearings without dismounting and replacing the seals.
• Mounting check after maintenance or replacement of bearings.

Unplanned downtime of trains can always result in direct and indirect costs for rail operators. The reputation of the operator can also be damaged, particularly in public transport applications. In this particular case, there is an additional significant risk because any downtime or delays in rail traffic is penalised in the form of severe financial penalties stipulated by national regulations. Following the positive experience with Schaeffler’s test rig, the customer is now planning to use the system at other locations.

Renesas Electronics has joined the Autonomous Vehicle Computing Consortium (AVCC) as a core member. Renesas joins leaders from across the automotive ecosystem, including vehicle OEMs, Tier1 suppliers, and other semiconductor suppliers to help solve some of the most significant challenges of deploying self-driving vehicles at scale.

As the automotive industry pushes forward to meet the needs of an increasingly connected environment, vehicles are evolving to become more intelligent, more ecologically friendly, and more affordable. Looking ahead, future autonomous vehicles will be operated with even more complicated and large-scale software driven by artificial intelligence. Vehicle edge computing platforms will play a key role in achieving the required ultra-high-performance computing within the power, thermal, size, security, and safety constraints. A standardised technical framework is also critical in order to share, re-use and incrementally improve developments resulting from this widescale automotive ecosystem.

On 8 October 2019, a group of leading automotive and technology industry companies including Arm, Bosch, Continental, DENSO, General Motors, NVIDIA, NXP Semiconductors, and TOYOTA announced that they were joining forces to help accelerate the delivery of safer and affordable autonomous vehicles at scale. (Press release)

“To achieve the future of mobility, we must connect actual use cases with the requirements, technologies and ultimately– implementation required to realise autonomous vehicles,” said Masayasu Yoshida, Vice President of Renesas’ Automotive System Development Division. “The AVCC will play a pivotal role in achieving this mobility future, and we’re very excited to take part in building the framework for vehicle edge computing, combining our popular and proven R-Car SoCs with this new framework, and leading autonomous vehicle evolution together.”

“The AVCC is excited to welcome Renesas as a Core Member and anticipate their contribution of unique technology and expertise as automotive semiconductor suppliers,” said Massimo Osella (General Motors), Chairman of AVCC.

Over 550 schools are set to take part in this year’s Tomorrow’s Engineers EEP Robotics Challenge and have the chance to be crowned UK winners at the competition finals taking place at The Big Bang Fair in March 2020.

The students will build, program and control LEGO robots for a series of environmentally themed missions to discover what engineers can do to create a cleaner, more sustainable world.

As part of the Challenge, the student teams will build a LEGO MINDSTORMS Education EV3 robot and program it to complete a speed and control test and perform a set of environmentally themed tasks such as planting a tree. Students will also work as a team to present an idea of how engineers can help future-proof the world.

Dr Hilary Leevers, CEO of EngineeringUK, said: “We’ve seen young people around the world coming together to demand action over climate change. The next generation can be part of the solution by choosing engineering careers that will be central to generating affordable and sustainable energy, and to solving other global challenges that they care about, like access to clean water and sanitation. We need creative thinkers with a range of skills and perspectives working together to secure our future.

“The new environmental challenge was chosen for the Tomorrow’s Engineers EEP Robotics Challenge to address an issue that many of us are passionate about and inspire students as they discover exciting new skills and careers in engineering, technology, robotics and computing.”

Demand for engineering skills is high and will continue to rise in the future – EngineeringUK estimates that the UK needs tens of thousands more engineers annually.

Dr Leevers adds: “Communicating the breadth and variety of engineering careers to young people is vital for the future of the UK economy, if the engineering community is to keep inspiring the next generation of engineers.”

Now in its fifth year the Tomorrow’s Engineers EEP Robotics Challenge encourages young people to put coding and team work skills to work. The Challenge aims to help students discover exciting new careers allowing schools to achieve some of their Gatsby benchmarks. As well as students, teachers also benefit from taking part in the Challenge and are well-supported through professional development training days and online mentoring.

Marc Fleming, Headteacher of McLaren High School in Callander, Scotland and reoccurring UK finalists, said: “For those teachers who have attended Tomorrow’s Engineers EEP Robotics Challenge competitions, they have all stated that the process has improved wellbeing outcomes, through increased confidence, improved self-esteem and a greater enthusiasm for STEM subjects.

“If you are a school who is thinking of taking part for the first time, do not hesitate in taking up the challenge, your young people will love it.”

To find out more and apply to be a volunteer, visit: www.tomorrowsengineers.org.uk/robotics 

Glasgow-headquartered JWF Process Solutions, engineering specialists in measurement and instrumentation products and services, has gained a UK-wide operational footprint with the acquisition of Manchester-based flow measurement specialist Stream Measurement.

Founded in 1962, JWF has UK and international customers across the Oil and Gas, Food and Beverage, Chemical and Petrochemical sectors and counts Repsol, Chrysaor, Apache, Nestle, Diageo, Macallan, Ineos, PetroIneos and Babcock International among its client base.  Stream Measurement, established in 1999 following a management buy-out from Schlumberger, covers the Utilities, Energy, Automotive, Food and Beverage and Pharma sectors, with key customers including National Grid, Centrica, Phoenix Gas, Thames Water, Boots Manufacturing, Greencore, BMW and Astra Zeneca.

The combined group will have turnover in excess of £10 million, headcount of 37, UK-wide coverage, an extended partner network, strong synergies and enables JWF to further develop its service-related activities.  JWF, who moved to a new world-class facility in 2015 and also has operational bases in Aberdeen and Teesside, offers a full package of instrument and measurement solutions encompassing instrumentation, metering, flow surveys, commissioning, calibration and tank calibration.

Kenneth Fairbairn, Chief Executive of JWF Process Solutions, said: “JWF’s unique position in the market is underpinned by the partnerships we have in place with manufacturers across the globe, relationships that allow us to select the best solution to meet client expectations such as technical specifications, quality, materials, delivery timescales and cost – which are all crucial to our customer base.  The acquisition of Stream Measurement gives us added strength in existing and new industry sectors, a high-quality team of people who share our customer-first focus, UK-wide reach and the opportunity to build an even stronger services division at the combined group.”

Andy Maber, Commercial Director, Stream Measurement said: “This is a very exciting time for both Stream and our customers.  We are adding new products, services and increasing our geographic support, whilst the team at JWF complement our existing flowmeter expertise with their years of instrumentation and measurement experience.”

Robert Allan, Managing Director, JWF Process Solutions, said: “The markets we work in are going through a period of transformational change.  Oil and Gas in the UK is seeing a number of mergers and acquisitions and the Energy and Utility markets are continuing to expand due to their requirements for increased levels of specialist metering support.  The Stream acquisition further strengthens our ability to provide full turnkey measurement solutions across all markets.”

JWF is on track for revenue in excess of £8 million in the current year (year to 31st December 2019).

The Liverpool City Region Combined Authority will be asked to approve a grant for £15m next week, to enable research and technology organisation the Manufacturing Technology Centre (MTC) to expand its facilities and create more than 40 highly skilled jobs.

Having recently moved to the Liverpool Science Park, the MTC provides a competitive environment to bridge the gap between university-based research and the development of innovative manufacturing solutions, working with the automotive, aerospace, construction, defence, rail, informatics, fast-moving consumer goods and electronics sectors.

Steve Rotheram, Metro Mayor, said: “The Liverpool City Region is already a hotbed of advanced manufacturing activity and we are leading the way, nationally and internationally.

“The funding will have the twin benefits of delivering solutions for established industries whilst also providing a space in which innovative and responsive SMEs can develop.  Being able to support facilities like this, which will drive the city region’s economic fortunes, is one of the main reasons we are so keen to take more decisions locally.”

The proposed investment would enable the MTC to develop an open access Digital Manufacturing Accelerator that will comprise two assets- a “Rapidly Reconfigurable Factory Environment” – a digitally enabled Factory in a Box test bed at the MTC’s recently opened centre in the Knowledge Quarter and a “Digital Factory Environment” at STFC Daresbury in Halton. These facilities enable companies to test and develop their manufacturing processes and systems and use digital technology to enable them to become more productive and successful.

The MTC is part of the High Value Manufacturing Catapult, supported by Innovate UK, and was established to prove innovative manufacturing processes and technologies in an agile environment in partnership with industry, academia and other institutions. Housing some of the most advanced manufacturing equipment in the world, and with facilities in Coventry and the Liverpool City Region, the MTC provides a high quality environment for the development and demonstration of new technologies on an industrial scale, supporting skills, productivity and growth across the UK manufacturing industry.

Cllr Pat Hackett, Portfolio Holder for Inclusive Economy and Third Sector, said: “Enabling the MTC to expand its facilities will generate employment and training opportunities, attract and retain highly skilled professionals and support manufacturing growth and innovation in our city region.”

Neil Rawlinson, Strategic Development Director at the MTC, said: “At the MTC, we believe our purpose is to have a positive impact on society. We know we can do that by working in partnership with the Liverpool City Region innovation community. We are excited to be expanding our facilities and services in the Liverpool region, working with our partners and regional stakeholders to help manufacturers in the North West region stay competitive, improve product development and benefit from new manufacturing and digital technologies.”

Charlie Whitford, MTC Associate Director for Strategic Development, said: “This project is a unique opportunity to upskill and connect regional technology providers and supply chain, providing the ecosystem required to rapidly commercialise product research and development. We are also excited to be providing the region’s industrial base with a reduced risk, cost effective environment to test and incorporate manufacturing platforms of the future, opening new global market opportunities.”

Massive Analytic, a London based artificial intelligence pioneer, and the National Physical Laboratory (NPL), the UK’s National Measurement Institute, have now completed their joint InnovateUK Analysis for Innovators project, the “Metrological comparison between a generalised N-dimensional classical and quantum point cloud”. The results of this project have opened avenues for both further R&D into quantum as well as ways to enhance Massive Analytic’s AI platforms.

The project set out to break new ground in quantum by proving that point clouds, created by fusing multi-modal sensor data, could be represented and processed on quantum computers as quantum point clouds. As a result of the project, teams at NPL and Massive Analytic have been successful in simulating transposing point cloud sensor data from an autonomous car onto quantum computers.

Ivan Rungger, senior research scientist at NPL said, “Autonomous cars and other advancing technologies rely on the fast acquisition and analysis of sensor data, combining visual data with information such as temperature or humidity distributions. Using Massive Analytic’s data, we have produced a new method to represent these multi-modal inputs as general point cloud data on quantum computers. Our method simulates how the data can be ported to near term noisy intermediate-scale quantum (NISQ) computers – opening the doors for the commercialisation of these technologies in future.”

Thanks to the collaboration Massive Analytic has developed a classical-quantum computing hybrid approach, where outputs from classical sensor technologies are modified to enable early applications on current state-of-the-art quantum computers of the order of tens of qubits. Massive Analytic intends to augment its patented AI, Artificial Precognition, with outputs from a quantum processor to further improve prediction accuracy across all its product lines to deliver even more value to its customers. This breakthrough also creates a host of new possibilities for processing IoT data and applying AI and machine learning to it.

The company was supported to participate in the Analysis for Innovators (A4I) scheme by Innovate UK. Funding from the Department of Business, Energy and Industrial Strategy enabled Massive Analytic to access the cutting-edge R&D, expertise and facilities at the National Physical Laboratory, to help overcome the company’s unique measurement challenges.

Jonathan Mitchener, from Innovate UK said, “It’s great that our A4I programme can support key UK technology areas such as Quantum, and in conjunction with world class scientific partners, such as NPL, that A4I brings companies together with, support a growing and ambitious company to be more competitive in the new quantum computing space.”

Following the success of the A4I project, NPL and Massive Analytic are in discussion to establish a long term collaboration to develop quantum technologies for data science applications, ranging from sensing to cyber security to precision medicine.

George Frangou, CEO and Founder of Massive Analytic said, “Massive Analytic and the National Physical Laboratory in partnership are realising the benefits signposted by the Fourth Industrial revolution; linking Tech City to world class laboratories. With the Government now committed to being the leading European economy in Artificial Intelligence and Quantum Computing, we have the opportunity to create a partnership, which will be regarded as pre-eminent in our chosen domains.”