At one of Rolls-Royce’s manufacturing facilities, inspection is carried out to measure the moment weight of rotating components, to determine optimal alignment relative to the engine.
However, these measurements do not remain constant. With data mining and machine learning, surprising trends or relationships are constantly extracted.
Your challenge is to produce an algorithmic model that allows periodic adjustment throughout the manufacturing process, in tandem with identified trends and new data inputs.
Yes, you are called to create a super-human decision-making engine for aero-engine inspection, using data analytics and AI. How exciting is that?
How can Machine Learning and Artificial Intelligence improve the success of product compliance throughout the high-value components manufacturing process?
During the event, teams will be provided with relevant numerical datasets to train their models on.
We will be offering £10,000 of initial seed funding to the winners to help develop a proof of concept/prototype in partnership with Rolls-Royce Plc.
The prize package will also include mentorship and support from senior members of the Manufacturing Technology team and R2 Data Labs team to develop the MVP, as well as PR and profiling opportunities.
All participants will be given the opportunity to qualify for the R2 Data Labs ecosystem programme, and become part of our network of innovators addressing critical business challenges where value can be delivered from advanced data innovation.
Through this challenge, R² Data Labs at Rolls-Royce are looking to connect with external partners in the following areas:
Who can take part?
Has your startup already developed a successful machine learning model for automated recalibration and decision making?
Does your company have a pre-trained model that could be calibrated for this challenge?
Are you looking to add Rolls-Royce Plc to your portfolio?
If the answer to any of the above is YES, we would love for you to apply to this challenge.
You have your idea, now the next step is to ensure you have the right team on the day.
Each team should have 4-5 members at the event consisting of a mix of the profiles below:
You love building and testing algorithms, and are generally obsessed with reducing error rates and increasing algorithm reliability.
Your skills and strengths
are in data analysis, DevOps,
robotics and/or human-computer interaction.
You have the skills to ensure the end user takes to your solution like a duck to water - making everything look slick and polished.
You may be a PhD, self-taught deep learning maverick or someone who is extraordinarily talented at solving hard problems when given access to data.
Your abilities lie in showing the audience just how feasible your solution is, and you know how to show you are worth the investment.
Who should you bring along to the hackathon?
09.00 am Breakfast
10.00 am Hacking
11.00 am Final Check-in for Mentors
12.30 pm How to Make a Kick-Ass Demo
1.00 pm Project Deadline & Lunch
4.30 pm Coding Ends & Jury Briefing
5.00 pm Demos & Deliberations
7.00 pm Winners Announced
09.00 am Opening & Breakfast
10.00 am Introduction
10.30 am Data Workshop with Chris Athey
11.00 am Hacking Starts
12.00 pm "Moving Away from David vs Goliath to David x Goliath" with Caroline Gorski
1.00 pm Lunch
2.00 pm Mentoring Sessions
7.00 pm Dinner
If you have any questions about the event, please email email@example.com