Faraday Predictive Ltd

The Company

Faraday Predictive LogoFaraday Predictive Ltd is a small technically based company, 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 also monitor energy consumption and the associated electricity costs, and crucially, link the level of developing defects in the machine to energy wastage, allowing customers to cost-justify precision maintenance work to reduce this waste, and reduce their carbon footprint.

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 been running summer placement schemes over the last six years and the work by those students has been a significant contributor to the capabilities of the entire range of Faraday Predictive products.

Some placement students from previous years ended up joining us, to continue their learning and development and simultaneously continuing to build our product development.  Their subsequent experiences have included working on a 3-year project jointly with Rolls Royce to develop our technology for application in the aerospace environment, getting trained to be helicoptered onto North Sea oil platforms, and creating complete 3-D printed products.  These placements from previous years made a major contribution to the new Faraday Predictive products which are now being deployed around the world.

We are a virtual tenant at SJIC, we also have staff based in IdeaSpace, an offshoot from the Institute for Manufacturing, located in Laundress Lane (between The Mill and The Anchor) or 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 if preferred.

The Opportunity

Project outline

Our existing product uses PC-based processing, which has a cost penalty for both the hardware and software we use. Effectively our product has to incorporate a complete Windows PC inside it.

This approach made sense in the early stages of our product because of the widespread availability in .net format (ie able to run on Windows) of software library functions to perform some rather complex mathematical processes that are essential to our algorithms.  However now we have established effective and robust algorithms, we are in a position to optimise them for efficiency and cost.

In order to expand our offering to a wider range of customers to be able to benefit from it, we are looking to convert our existing product into a form that will give us a lower cost base.  This will involve our existing software being converted and adapted from a .net on Windows basis to a Python on Linux basis.  The hardware will correspondingly reduce in cost from a complete Windows PC to an ARM chip-based system more like a Raspberry Pi. 

The resulting system will then need to be tested on a rotor rig (that we already have) to demonstrate it functions correctly.  

So this will be a design and build project, to take existing working technology from a conventional PC and convert it to run on a self-contained Raspberry Pi system together with a “Pi HAT” Analogue to Digital Converter.  This will involve writing / programming in Python, making use of existing Python library functions, and possibly setting up real signal capture systems to work with a small test rig motor / generator system, to simulate real world situations.

Likely range of tasks: 

  • Review and agree the definition of the project, to ensure clarity of the objectives and the nature of the outputs / “deliverables” that will be created by the end of the project (day 1);
  • Review and understand the structure and function of the existing .net based system that is to be converted / replicated / superseded by this project (days 2-3);
  • Review and understand the structure of an existing Python-based system that has already been created for a parallel product (days 4-5);
  • Create in Python, using Python library functions, a system to deliver the outputs agreed in step 1 (weeks 2-5);
  • Test the system by using it to take measurements on a small motor / rotor rig, simulating the development of faults on the rig (week 6);
  • Refine / tweak the system in the light of findings from tests (week 6-7).
  • Write up the experiences of the project, for feedback to Faraday Predictive, for St John’s, and for your personal portfolio.


Skills required

This project would be appropriate to someone with skills in, or interested in:

  • Engineering (combination of Electrical Engineering, Mechanical Engineering and Control Engineering) or Mathematics or Physics.  [Training / Education will be given to cover any areas not yet familiar to the intern]
  • Computer programming – likely to be working in Python
  • Enthusiasm / interest / initiative / creativity – to develop new approaches
  • Teamworking – to debate and build ideas with other members of the team
  • Independence – to be able to work on your own without minute by minute supervision.


Specifics to this project beyond the general ones above:

  • Engineering mind set – to feel comfortable with rotating machines driven by electric motors, and the concepts of AC voltage and current;  We will anyway provide education in the more in-depth aspects of 3-phase supplies and motor behaviour.
  • Degree of comfort in both electrical and mechanical engineering.
  • Familiarity / comfort coding in Python, and willingness to learn & extend this knowledge.
  • Some familiarity with computing in general – but not required in great depth.


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