The STARS Hack & Match on Advanced Technologies for Resilience of Railway Supply Chains catalyzes SME initiatives. It seeks to drive economic growth and provide innovation in the railway sector.

Are you part of an SME interested in submitting a potential solution for the proposed challenges? Pick one of the twelve presented challenges and offer your solution!

All discussions and collaborations will be possible in online Teams groups, segmented according to where the idea/solutions aim to impact. The Teams groups will comprise a minimum of 3 and a maximum of 8 people.

The Challenges

Challenge #1 - AGUI

AGUI is a family company located in the north of Spain dedicated to industrial subcontracting, being experts in welding (EN 15085) and complex assemblies. The manufacturing products are traction converters and different parts for train interiors. They offer their customers design collaboration providing process engineering and prototyping, complete supply chain management, local manufacturing, and a high service rate.

For this Hack&Match, AGUI proposes to work on this theme "We want to speed up our manufacturing cost studies to provide faster quotations to our customers. What innovative tools/AI/methods can help us with this purpose?"

Challenge #2 - PANTOhealth GmbH 

PANTOhealth GmbH is an innovative deep-tech startup based in Berlin, Germany, with a bold vision to revolutionize the rail industry. Specializing in real-time monitoring and predictive maintenance of trains, PANTOhealth leverages advanced technologies to enhance rail transportation's efficiency, reliability, and sustainability.

For this Hack&Match, PANTOhealth GmbH proposes to work on this thematic " Real-Time Monitoring of Lifts and Escalators in Rail Stations."

In modern rail stations, lifts and escalators ensure smooth passenger movement and accessibility for all travelers. However, malfunctions or breakdowns in these systems can lead to inconvenience, delays, and safety risks. The challenge is developing a real-time condition and functionality monitoring system for lifts and escalators to proactively detect issues before passengers encounter them, ensuring seamless operations and enhancing passenger safety.

The main goal of this challenge is to design an innovative and efficient system that can quickly identify any malfunctions in lifts and escalators, triggering an immediate alert to maintenance personnel or station operators. This proactive approach will help prevent potential accidents, reduce downtime, and improve the overall passenger experience in rail stations. "

Challenge #3 - Ghana's Ministry of Railway Development

Ghana Ministry of Railway Development develops policies to regulate the railway industry and improve its operations.

For this Hack&Match, the Ghana Ministry of Railway Development proposes to work on this theme "We are collecting a massive amount of data from our IoT sensors installed in our manufacturing factory / on passenger trains / on freight trains... but so far we aren't able to make the most of them. How could AI help us in this? "

Challenge #4 - NeudoTec e.U.

NeudoTec e.U., founded in 2022, is a technical consulting agency focusing on railway rolling stock.

As a representative for IZP Dresden mbH in Austria, NeudoTec e.U. also offers various support in the field of RAMS/LCC.

Consulting focus: Business Organization; Strategy & Innovation; Product Development; Engineering & Technology; RAMS/LCC.

For this Hack&Match, NeudoTec proposes to work on this theme "The review/assessment of extensive customer product/development specifications and complex customer contracts is time-consuming and effortful; in particular, the requirements are almost similar from case to case but verbalized differently. Could AI help to make the creation of Clause-by-Clauses easier and effective?"

Challenge #5 - Volf Equipment for Electric Vehicles (VeeV)

VeeV produces electric and mechanical devices and spare parts for electric vehicles (locos, EMU, DMU, trams...)

For this Hack&Match, VeeV proposes to work on this theme "We want to develop a simulation for testing braking resistors in various circumstances. This could be expanded to use the digital twin model, which could also be used for further improvements on the design."

Challenge #6 - Challenge #6 – Green Buffers AB

Green Buffers AB has created a unique crash system that changes how we can achieve increased crash safety - far beyond existing standards.

An award-winning system and a recognized innovation that received two significant awards, the Swedish SKAPA Prize 2021 and now the latest Steel Prize - 2023 from SSAB.

The new generation of buffers absorbs and dissipates the impact energy in collisions between trains at lightning speed for half a second. Which provides safer train journeys for the passengers and more cost-effective solutions for the train operators and reduces the carbon footprint at the same time.For this

Hack&Match, Green Buffers AB proposes to work on this thematic "We aim for ZERO uncontrolled derailments related to collisions. Passengers can just walk by themselves out of the train after a collision. No need to replace or recycle the trains. Meet citizen's expectations/demands by higher requirements in the specifications for improved safety and sustainability. Co-create and cooperate in a new partnership between end-user, train builders, and suppliers."

Challenge #7 - Talgo Inspire

Talgo Inspire is Talgo's Corporate Venturing unit. We aim to create and develop projects in collaboration with startups worldwide under the venture client model.  This way we work on building agreements with startups with which we share an innovative vision of a sustainable, responsible, and technologically advanced future in the mobility industry.

At Talgo Inspire, we offer you our expertise and assets to work together for the benefit of clean transport and the present and future of mobility.

We aim to be a booster of innovation in the railway sector. Therefore, we seek to find and work with those startups that have designed disruptive technologies which could improve our products or processes since we want to become the bridge that connects these pioneering ideas with the railway sector, providing opportunities for growth and global expansion.

For this Hack&Match, Talgo Inspire proposes to work on this thematic "Automated risk analysis of railway vehicles' OT systems (under EN-62443 and TS50701 standards)."

New generation train designs include a cybersecurity risk assessment based on methodologies and threat criteria according to current ISA-62443 and TS50701 standards. Once the train is delivered, it is necessary to perform a periodic update of its risk level using concepts such as the integrity or non-alteration of the onboard systems and configurations. 

The main goal of this challenge is to design an innovative system that allows showing a theoretical risk assessment overview before the train is delivered and then updating its status based on real-time or periodic monitoring of the key system, network integrity, or status indicators. This approach will help increase the efficiency of cybersecurity compliance review and provide a train's health status."  

Challenge #8 - Lucchini RS SpA

Lucchini RS Group specializes in producing railway wheels for all kinds of applications; the headquarters and leading production site are based in Italy, and other manufacturing companies are based in Europe, Asia, and Africa, covering the local market, including maintenance services.

For this Hack&Match, Lucchini proposes to work on this theme "We want to lower the power demand of our distributed sensors/devices on board trains..., without reducing bandwidth capabilities; or increase the energy harvesting from small solar panels or other kind of power generators. How could we do it? "


Challenge #9 - Lucchini RS SpA

Lucchini RS Group specializes in producing railway wheels for all kinds of applications; the headquarters and leading production site are based in Italy, and other manufacturing companies are based in Europe, Asia, Africa, covering the local market, including maintenance services.

For this Hack&Match, Lucchini proposes to work on this theme "We are collecting a vast amount of data from our IoT sensors installed on wheelsets of passenger trains or freight trains... but apart from providing the basic information they were designed for, the data collected from different type of sensors and correlated with another type of data could be used to find more sophisticated information not only related to the wheels but for instance of the infrastructure. How could AI help us in this? "

Challenge #10 - Photon Laser Manufacturing GmbH

Tier 1 supplier for the railcar industry. 200 employees in Berlin.

Laser beam welding of sidewalls, roofs, and other complex lightweight metal assemblies for passenger cars.

For this Hack&Match, Photon Laser proposes to work on this thematic "Digital twin for railcar body-in-white-production. We want a solution for collecting and combining production data (material certificates, machine production data, ERP data, personal confirmations, digital quality measurement data) and fail-safe, resilient, and certified data storage of serialized marked and delivered products for internal and external web-based database access over approx. 30 years warranty time. "

Challenge #11 - S.I.C.E.

S.I.C.E. designs and implements electrical, electromechanical, electronic, and information technology services and installations for the Italian State Railways.

For this Hack&Match, S.I.C.E. proposes to work on this thematic "S.I.C.E. designs and implements electrical, electromechanical, electronic and information technology services and installations for the Italian State Railways. Recently, we also delivered Railway line monitoring and diagnostics activities by processing and analyzing data collected from heliborne aerial surveys. This activity, which was initially highly innovative and appreciated, is now quite widespread; moreover, this activity is directly passed to the National Electric Company, which is autonomous for this type of investigation. At the time, the robust innovation was to geo-reference the acquisitions.

To conserve and give value to such competencies and experience, we now would like to understand how to possibly use and evolve them for possible applications on emissions/thermal losses of civil buildings (railway stations as well as offices and houses) both in terms of innovative tools and AI-supported software analysis."

Challenge #12 - McLedger

MCLedger is a boutique consulting firm combining technical expertise and business know-how to create high-performing digital service platforms for the transportation and logistics market with expertise in multimodal and commodal transport.

For this Hack&Match, McLedger proposes to work on this theme "Given certain KPIs chosen by a client: shortest distance, cheapest route, most eco-friendly route, quickest route, ... provide an AI solution to suggest one or more routes using multimodal (for freight) or commadal (for parcel freight) solution - (road, rail minimum but open to other forms of transport in the future)."