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Artesis LLP

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Artesis LLP is a small technically based company, poised for significant growth based on the development of unique methods for remotely monitoring industrial equipment.  We bring big benefits to companies by helping them avoid unexpected breakdowns, avoiding un-necessary maintenance work, improving reliability and reducing costs and disruption to operations.

We have customers around the globe, in industries including Oil and Gas, Power Generation, Pharmaceuticals, Food and Drink, General Manufacturing, Shipping, and Facilities Management.  We monitor their equipment remotely and provide regular advice to them, all from the UK.

We have recently been running summer placement schemes, and last year’s placement student now has a full time job with us working on a 3 year project jointly with Rolls Royce to develop our technology for application in the aerospace environment.  We’d like to think that a summer intern this year could follow a similar pattern.

We are a virtual tenant at SJIC, we also have staff based in IdeaSpace in the Hauser Forum building at the West Cambridge site.  We are assuming the project will be based in Cambridge, but we are flexible on location, and could consider a “virtual location”, of the student working remotely some of the time if the student particularly wanted.

 Opportunity:  Learn about the world of automated equipment fault diagnosis and health monitoring of rotating equipment

Project outline

Develop ways to improve the accuracy of diagnosis of faults identified by Artesis equipment health monitoring system, to be incorporated into next generation of products.  The core of this will be to more closely match the diagnoses to the specific nature of the equipment.  This will be developed by categorising existing historic data into appropriate classes of equipment and operating conditions, and then developing and testing revised methods against these individual classes.  This will be a real contribution to Artesis LLP capability and future products, which will give the intern exposure to the world of industrial equipment, to operations and maintenance, to maintenance strategy optimisation, to signal processing and coding.  It may also involve some exposure to the world of Machine Learning and the Industrial Internet of Things.

Likely range of tasks: 

  • Learn about how the Automated health monitoring and fault diagnostic system works at present
  • Use existing system to diagnose real faults in real equipment – sufficient to fully understand the current capabilities and limitations
  • Review, analyse and categorise existing and historic data into classes appropriate to different equipment types
  • Devise ways of creating appropriate thresholds and trigger points for use with each class identified
  • If time is available, and skills are appropriate, devise and write some computer code to apply these diagnostic methods to the data, testing against historic data and then using for real on new live data

 Skills required / this project would be appropriate to someone interested in:

  • Engineering (combination of Electrical Engineering, Mechanical Engineering and Control Engineering).  [Training / Education will be given to cover any areas not yet familiar to the intern]
  • Computer programming – possibly Matlab, or C++ or possibly others [Training / Education will be given to cover any areas not yet familiar to the intern – the important thing is an interest and willingness to learn]
  • Enthusiasm / interest / initiative / creativity – to develop new approaches
  • Teamworking – to debate ideas with other members of the team
  • Independence – to be able to work on your own without minute by minute supervision.