SFM360, is a research driven collaborative platform designed to inform maintenance, operations and supply chain organisations on the real world experiences, financial implications and tangible benefits of investments in digitalization for fleet maintenance operations to create a digital supply chain, improve life cycle asset management, data management and decision making in maintenance and optimise reliability and availability of rolling stock fleets to reduce cost in fleet maintenance activities and meet asset management cost targets across multiple rolling stock asset including legacy and new fleets.
Highlighting real world experiences from UK, Europe & Asia Pacific on how rail operators are implementing and integrating Asset Management systems, Digital Twins, Additive Manufacturing, Sensors, and Device Management, IoT and cloud technologies, AI & Machine Learning to make their maintenance organization more efficient and data to bring down cost in a revised operating environment for the industry.
You will gain first-hand insights about the way forward, including practical examples on:
Manipulating data to understand
the asset life cycle, reducing maintenance interventions, increasing reliability and productivity in maintenance operations
Investing in methodology and continuous data management, building a roadmap for engineering to ensure you meet asset management cost
The application of artificial intelligence within the maintenance world, implementing machine learning tool sets to improve decision making in maintenance
Optimizing Asset Management Systems, modeling business and maintenance processes to improve forecasting & Maintenance planning
Enhancing maintenance processes in the workshop, investing in automation to meet demand and increase productivity in maintenance activities
Improving data management to optimise defect management in maintenance organisations, planning the correct intervention in real time
Adopting a circular business model, building digital twins to deliver a digital supply chain, improve resilience and sustainability and make maintenance more data driven
Developing the execution of data analysis in fleet operations, transferring and correlating data to find insights to build the business case for AI & Machine Learning
Financial implications and tangible benefits of implementing more sensor technology to collect real time data, reducing maintenance cost
Confirmed Speakers
