Sellafield Ltd Supply Chain Forum Special for International Women's Day

Our criticality safety assessors Katrina and Haleema represented Cerberus at the Sellafield Supply Chain Event in March. The event was a women’s special, falling just after international women's day, and was only attended by women in the supply chain and at Sellafield Ltd.

It was so great to hear from different SMEs and all the great projects currently going on. It was especially great hearing from the next generation coming up through the Sellafield apprentice schemes. We wish them all the success in their next chapters! Another fantastic presentation was from the Jacobs women’s network, and we look forward to hearing and collaborating more in the future.

- Haleema H, Criticality Safety Consultant

At the forum, companies are given the opportunity to give a 60 s pitch. Katrina Christaki took the challenge and pitched Cerberus Nuclear to the other attendees at the forum!

Cerberus looks forward to continuing collaboration with Sellafield and to attending the next supply chain forum. 

ANDI: Sellafield Success Story

Cerberus Nuclear's ANDI (Automated Nuclear Damage Inspection) has been featured as a Sellafield Ltd success story.

As part of the latest update to the Sellafield opportunities guidance, Cerberus Nuclear has been featured within its SME action plan. The SME action plan reaffirms Sellafield's commitment to increase opportunities for SMEs within the supply chain recognising the adaptability, innovation and value that SMEs bring to help Sellafield deliver its mission.

As a public contracting authority Sellafield Ltd are committed to delivering activities which increase the opportunities for SMEs (small to medium enterprises) to do business with the supply chain. Sellafield have a target to spend 32 - 33% of supply chain spend with SMEs in 2021/22.

To find out more about how to do business with Sellafield go to

To learn more about ANDI and our latest developments combining computer vision with 360 video go to ANDI360.


ANDI: 360 Tracking

This is our latest post regarding our software ANDI (Automated Nuclear Damage Inspection) and incorporating identification capability with 360 video data.

The 360 camera sector has advanced significantly over the past few years, camera resolution and image quality has improved greatly as well as advancements in software processing to provide multiple different ways of viewing the captured images and video. Cerberus Nuclear has been keeping up to date with latest developments with an aim of using this technology in the nuclear sector.

Cerberus recently developed ANDI (Automated Nuclear Damage Inspection) for Sellafield Ltd. The software automatically identifies key areas of damage from inspection videos and is currently being used by Sellafield to accelerate damage inspection tasks. The software is built into a user-friendly interface and supports the creation of reports and logging of key identified features.

Building upon our knowledge we are currently testing the use of 360 camera and video data with our custom computer vision algorithms, including ANDI. Some key advantages of using 360 data for automated damage inspection is that the orientation of the inspection camera is no longer a factor as images capture the full 360 degrees.

Similar technology is currently being used in autonomous vehicles for object identification and distance determination.

Footage obtained from a Cerberus Nuclear test car.

Our preliminary testing has proved to be very successful and we have overcome some of the challenges inherent in working directly with 360 data sets. The prototype software we have created demonstrates the capability of combining both 360 image technology with our bespoke computer vision algorithms.

Our goal is to continue the development of ANDI so this highly useful and innovative technology can be put to good use solving a wide range of challenges in the nuclear sector and beyond.

Look out for future updates, if you would like to learn more don't hesitate to get in touch at

Sellafield LINC: Image Processing for Assessing Package Integrity

The Challenge

LINC with Sellafield Ltd is a scheme that encourages SMEs at local and national level to collaborate and deliver innovative solutions to support the mission at Sellafield. LINC challenge 42 was titled ‘Image Processing for Assessing Package Integrity using Machine Learning’ and set the challenge as follows:

“The long-term storage of nuclear waste is at the heart of the nuclear industry in the UK. As a requirement this material must be examined on a regular basis, which generates a vast amount of data to be reviewed. Presently this is done manually and takes a lot of time and is vulnerable to human error."

Cerberus Nuclear’s Data Science team proposed the development of software containing a trained machine learning computer vision model that would be capable of automatically recognising issues that could affect integrity of the package. Our team use the ‘Agile’ design methodology, which incorporates software testing in short, focused development cycles; ideal for the project.

We were delighted when Sellafield Ltd chose our solution ahead of some tough competition.

ANDI: Automated Nuclear Damage Inspection

ANDI is a high-quality user-friendly software program that utilises computer vision machine learning for automated identification of damage from externally supplied video.

The software allows detailed examination of product can inspection videos, automatically identifying damage such as scratches, dents and corrosion. The neural network within ANDI uses a cutting-edge R-CNN approach for image analysis and was trained using previous examples of damage.

Damage identified is highlighted within an embedded video player, which allows users to quickly skip to areas of interest and examine results frame by frame to inspect the exact moment(s) that damage has been detected. The confidence level of identified damage can be customised by the user with damage highlights switched on or off to assist with detailed inspection.

An integrated inspection report system was incorporated into the software to allow users to make notes and log frames for easy follow up review. The software also allows the processing of multiple batches of inspection videos with minimal user interaction. This allows the review of multiple processed results within a single session.

The algorithm for the Sellafield challenge uses an extension of the R-CNN called the Mask R-CNN. The R-CNN algorithm (Region based Convolutional Neural Network) can detect and classify objects within images, it focuses on variations of colour, texture and scale within an image to form a region.

“I really like the look and feel of the software and I’m impressed how well the neural network is identifying the key elements of damage, it’s very good!”

Gareth Myers, Technical Researcher, Project Lead, Sellafield Ltd

“We are delighted that Cerberus Nuclear helped make a difference at Sellafield Ltd. The Data Science team have delivered a great solution, bringing modern techniques to the nuclear industry.”

Daniel Cork, Director, Cerberus Nuclear

Sellafield Ltd are currently using ANDI to enhance their damage inspection workflow which, prior to using the software, had taken many man-hours to identify, categorise and log.

Cerberus Nuclear are proud to announce ANDI has recently been a key feature for inTechBrew. inTechBrew promotes the latest high Technology Readiness Level (TRL) nuclear industry innovations across UK and Europe.

Machine Learning
Computer Vision

Previously, the team developed a custom computer vision object identification algorithm to identify cars and lorries on a motorway using R-CNN object detection method.

The algorithm identified the number of objects, object type (car, lorry, etc.), object colour, object speed and confidence in match. In addition, a report was generated that summarised the information gathered over time. The development was to demonstrate validity of use for stopped car identification as well as traffic monitoring purposes.

The Sellafield Ltd LINC challenge aligned well with the previous development work already performed and paved the way for the creation of ANDI. Additional technical challenges such as variable lighting, frame blur and reflections had to be overcome as well as creating a custom user-friendly interface that met with Sellafield Ltd requirements. The processing time for the computer vision algorithm was also enhanced.

Object Recognition - Computer Vision

We have developed a custom computer vision object identification algorithm. As a demonstration, we trained a neural network to identify cars and lorries on a motorway using R-CNN object detection.

The algorithm identifies a number of objects, object type (car/lorry etc.), object colour, object speed and confidence in match. In addition, a report is generated that summarises the information gathered over time.

Cerberus Nuclear has access to the necessary computing power for near real-time, high-accuracy identification. The example was produced to demonstrate validity for stopped car identification as well as traffic monitoring.

In addition to this example, computer vision has a number of nuclear applications that we will be looking to build upon in the coming weeks.

If you would like to know more or if you have a specific challenge, which you think computer vision may solve, don't hesitate to get in touch.

The Generator - Point Cloud

For many years companies and networking groups have used this facility for seminars and lectures to facilitate networking, knowledge sharing and collaboration opportunities.

Cerberus Nuclear were delighted to offer our services to Birchwood Park, which then allows them to showcase this valued facility in a unique manner.

The original point cloud consisted of over 100 million points of data created from multiple 3D scans. Our scans produced a high-density point cloud with accuracy of 1mm.

The interactive model shown above has been downscaled to ~2 million points to cater for optimised dynamic viewing.

A big thank you goes to Birchwood Park for allowing us to access The Generator, for more information check out:

24th MCNEG Meeting (MCNEG 2020)

Cerberus Nuclear's Geoff Hall recently presented at the 24th MCNEG meeting held at the Culham Conference Centre, Oxfordshire.

MCNEG provides a forum for new and experienced users of Monte Carlo software for radiation transport.

Geoff's presentation was based on the assessment of transient dose rates from transport packages and gamma monitor normalisation. The talk was received really well with some very good follow-up questions.

It was a well attended event and there were some really good talks, the tour of the JET reactor on day 2 was excellent!

Geoff Hall

Cerberus Nuclear would like to thank AWE and UKAEA for supporting the event.