IoT & Maintenance Stream
SVP European Asset Maintenance and Technology
Head of Maintenance Modernisation
Head of Fleet Management
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IOT & Maintenance, Wednesday 18 April 2018
- · Step 1: Companies are reinventing themselves by reinventing their products, how should freightposition itself?
- Step 2: Connectivity, digitalisation en automatisation within an Industry 4.0. level open up never seen opportunities for the future of Rail Freight
- Step 3 : Make it credible: Understanding the first projects in Lineas’ roadmap to the future
Developing real time data flows to optimise maintenance
- Collating on-board real-time data effectively you will be able to schedule pro-active maintenance at the best time
- Ensuring your investments ultimately improving the reliability of your fleet and benefiting from new insights into your rolling stock
- Understanding the opportunities in saving time and budget with the impact of a real-time data approach
Exploring the opportunities for rail that digitisation provides
- Using digitisation to provide additional services to our customers: developing in a customer centric way
- Digitization and Automation of Assets and Infrastructure
- Our vision for the future: Better utilization and increasing availability of assets and production resources as well as increasing energy efficiency, quality and customer satisfaction
Using Big Data to gain insights in the maintenance of our rolling stock
- Hear how TFL are taking advantage of increasing number of sensors and sources of data on our rolling stock
- Understanding how big data can be optimised and developing new algorithms to gain new insights into our assets
- Key case studies: simply changes to lower the risk of disruption and the cost of maintenance
Remote and Real-Time Diagnostics of Rolling Stock Assets Condition: Business Cases and Main Results
- How can technical and financial risks be minimised with the implementation of highly precise asset management?
- What best practices should be used for this purpose to optimise the impact on rail networks?
- Sharing insight on the qualitative and quantitative benefits of applying big data techniques to rolling stock assets to improve performance
The challenge of train condition-based logistics
- Sharing the status of NS’ big data environment: what are we doing with our sensor data?
- Developing technologies and applications to optimise the logistics of railway operations
- Transitioning to full dependency: overcoming the political and regulatory challenges
Panel debate: How can rail capitalise on the potential opportunities arising from condition based maintenance?
- Discussing the main challenges that rail operators and network managers face when first implementing CBM
- Ensuring you are gathering and optimising data: what are the key lessons that can be shared?
- Developing and building on key insights to optimise data and CBM
last published: 19/Jan/18 13:55
IOT & Maintenance, Thursday 19 April 2018
How SBB Cargo are leveraging IoT and Automation to prepare for the cargo industry of the future
- SBB Cargo’s intelligent approach to digitalisation. How we planned for the future.
- Using IoT technology to deliver an improved service through precision train tracking and enhanced passenger information
- Future insight: How to continue transforming freight
How is Danobat’s advanced technology leveraging highly accurate wheel measurements and wheel reprofiling systems for maximum operating efficiency
- How non-stop data is helping operators to make smart maintenance a reality
- Technological innovation to simplify data maintenance
- How to reduce inspections and maximise interventions
Developing a big data platform to optimise operations on the Indian Railways Network
- Understand how Indian Railways is working to develop a big data for asset management
- Exploring the deep learning paradigm the rail industry
- Developing an outlook of applications and innovations for a big data platform
last published: 19/Jan/18 13:55