Submissions deadline March 8th
Being predictable isn’t always a bad thing
They also offer a way to add additional functionalities – like resistance to heat or increased aerodynamics and much more – to the materials they cover. So, we really do rely on paints and coatings. To ensure all our coatings are up to the long-term challenges they face and provide our customers with the best results that live up to their needs and expectations, we need effective ways of predicting the real-world performance of our coatings. This will help us speed up the process of bringing new products to market.
The limits of traditional methods of testing
We have more than 200 years of experience behind us. Over that history, we’ve developed many ways – often based on empirical methods – to understand how our current products will behave over time, how long it takes for colors to fade and when surfaces will need a recoat.
During development, we often rely on accelerated testing of our products under laboratory conditions, but we also test them under extreme external conditions by leaving coated surfaces out in the elements to see how they survive over time. These are tried and true methods, appreciated and often specified by our customers. However, we’re always looking to do it better and faster, allowing us to accelerate the development and introduction of warranted products.
Better ways to measure and predict
To improve the acceleration of our innovations, we’re looking for your unconventional solutions for predicting performance. We know incredible advances in digital technology have the potential to dramatically change and improve the ways we measure and predict how paints perform in the real world.
Incorporating new, faster or more accurate ways of collecting and augmenting data from both new and existing sources into our products and processes will help us bring better solutions to our customers, faster.
Outside the can at AkzoNobel
Curious what we’ve come up with already? Check out our Intertrac Vision tool. We augment marine ship positioning data with hull performance data and globally collected environmental data to generate predictive models for the performance of marine anti-fouling coating. This helps predict future performance bespoke to each ship, allowing for a superior customer value proposition directly related to ship fuel savings. Read more here.
What we’re looking for
- Your solution is not just in your head. The concept has been fully developed and is ready to apply
- Scalable, cost effective and easy to implement around the world
Should include one of the following elements:
- New ways of creating and/or collecting real world data
- Extracting new insights from (existing) data sources
- Improved or accelerated testing
- Predictive analysis (specifically applied to paints and coatings)
Have you got the solution?
We are closed for submissions, we will announce the finalists on April 11!