At Fishbone Solutions we have innovation embedded in our culture. Our customers benefit from this approach through our incessant drive to improve our methods, skills and technology. Whether it’s to a long term strategic goal or a performance improvement of an individual, process or product, delivering creative and new solutions is at the heart of our business offer.
We do this by providing the environment, the experience and concepts from multiple sectors to safeguard new ideas or take products to market. Our innovation process is simple but allows our teams to identify potential opportunities at any point in the lifecycle of a project.
Engineering- data analysis and prognostics
Statistical analysis and solution development to solve engineering performance, warranty and maintenance problems.
Our approach is to work with customers to identify creative solutions to help solve their engineering performance and warranty issues.
Whether the asset is a car, train, aircraft or machine our algorithms can be applied to anything with a "black box" or telematics unit.
Case Study - Train OTMR Data
Modern railway vehicles carry an OTMR (On Train Monitoring Recorder) device, similar to the "black box" of aeroplanes, and this records many channels of data about the current state of the vehicle, such as its speed, acceleration, throttle (gear) position, brake setting, brake cylinder pressure and so on.
We have developed algorithms to parse, filter, analyse and generate KPIs and component failure data from the information gained from the OTMR. The algorithms have been used by Train Operating Companies (TOCs) to identify system and component failure trends including wheelslip, compressor/traction performance, and door operation. Trend analysis can be undertaken on any data channel provided.
Our solution creates a commercially attractive approach by re-utilising existing train-borne data to improve performance on trains, with or without a dedicated telematics platform.
Angel, LED Lighting SA
Understanding train performance using data analysis
More and more railways are looking to introduce predictive maintenance regimes for their rolling stock, based on the continuous monitoring of asset condition to identify potential component and system failures.
It is relatively straightforward to incorporate such concepts in new trains which are being built with communication platforms, but not so easy to apply them retrospectively to legacy rolling stock built before the widespread use of sensors and integrated train management systems.
Reproduced from the November 2017 issue of Railway Gazette International by permission of the Editor. © Copyright DVV Media UK Ltd - www.railwaygazette.com