Following several successful data analytics projects focusing on asset and system performance, diagnostics and failure prediction, Fishbone has developed a standalone asset performance management tool. This cloud-based system utilises state-of-the-art Machine Learning (ML), edge and AI technologies to provide real-time performance insights and a set of targeted asset management tools.
The FISH is comprised of a cloud-based infrastructure which ingests and cleanses a variety of different data streams.
Once ingested and stored our ML and AI engines perform of series of analytics tasks. FISH contains a suite of off-the-shelf algorithms and toolsets and Fishbone’s data scientists can develop customer-bespoke analytics to suit specific asset data requirements.
Presentation and downstream use of the data and analytics outputs are again designed to be flexible. Fishbone have developed a set of tools to meet the initial use-cases for FISH and can develop customer specific GUIs and dashboards as required. The toolset options available to customers off the shelf include:
- Fleet Diagnostics tool. Analysis of data streams to identify real-time faults and run trending algorithms to locate and identify systems at risk of failing
- On-Condition Maintenance Scheduler. Scheduling of maintenance tasks based on actual condition of components and systems
- Train-to-Track Monitor. Gain insights into the train and track infrastructure as a complete system
- Battery Management. Analyse the wealth of data available from EV battery packs to identify faults and battery degradation to protect warranty and optimise battery and asset performance
Fishbone worked with the University of Leicester (UoL) to develop the initial system and continue to work together as the system enters production. UoL are experts in Big Data analytics and their knowledge and experience in this domain, coupled with Fishbone’s engineering domain expertise, has helped to accelerate the technology and the maturity of the FISH’s algorithms.
For enquiries, please use the Contact Us page on the Fishbone website.
