Vil du afgive tilbud på offentlige udbud? Se vores TaaS-service til forberedelse af udbud
Udbud

Automatisk køretøjsinspektionssystem

Åben
Frist
14 dage tilbage
28. august 2026
Kontrakt detaljer
Kategori
Andet
Reference
076454-2026
Værdi
Ikke oplyst
Lokation
London, Storbritannien
Udgivet
6. august 2026
Organisation
CPV-kode
Projekttidslinje

Udbud offentliggjort

11. august 2026

Frist for spørgsmål

21. august 2026

Frist for tilbud

28. august 2026

Kontraktens startdato

22. marts 2027

OrdregiverindsigtPRO
🔒
Lås op for ordregiverindsigt
Se forbrugsmønstre, foretrukne procedurer og mere.
Opgrader til Professionel →
Budget
Ikke oplyst
Varighed
13 måneder
Lokation
London
Type
Andet

Original udbudsbeskrivelse

Transport for London (TfL) is seeking to engage with the market to understand available solutions for an automated vehicle inspection system to undertake condition inspection of rolling stock as part of routine maintenance activities. TfL is seeking solutions capable of providing automated inspection of train bodyside, roof and underframe equipment as trains arrive at maintenance facilities. Solutions should be capable of identifying individual vehicles by painted number and capturing condition data of the vehicle during train movements. Solutions should be capable of detecting, classifying and reporting defects and asset condition issues, including, but not limited to, overheating components (such as brake resistors, bearings, traction equipment, HVAC equipment, brake blocks, wheelsets, traction motors and gearboxes), graffiti, broken windows, missing, damaged or misaligned components, damaged collector shoes, underframe damage, out-of-gauge equipment, wheel profile defects, wheel flats and brake wear using video & thermal imaging and acoustic monitoring technologies. The inspection capability should cover both sides of the vehicle, the roof and underframe, and be applicable to both multiple-unit and single-unit train formations. Solutions should provide secure capture, storage and management of inspection data, including images and sensor outputs, and utilise automated analytics, including Machine Learning (ML) and/or Artificial Intelligence (AI) where appropriate, to identify defects, trends and recurring issues and provide actionable information to maintenance personnel. TfL is particularly interested in understanding how proposed solutions can reduce manual inspection effort, improve maintenance efficiency, increase asset availability and support condition-based maintenance through frequent, automated fleet inspections. This planned procurement will be for a phased proof of concept and prototype trial and implementation at up to two London Underground Rolling Stock maintenance depots only. Depending on the outcome and demonstrated benefits, TfL may elect to procure further installations at other London Underground maintenance depots. The proposed procurement is envisaged to be delivered in three phases as defined below (subject to change): Phase 1: Concept design and development of the proposed solution. Phase 2: Subject to successful completion of Phase 1, development, installation and evaluation of a Proof of Concept at up to two London Underground Rolling Stock maintenance depots . Phase 3: Subject to business approval, potential fleet-wide rollout of the solution across the TfL's network. Phase 3 represents a potential future requirement only. Any future requirements under Phase 3 (in whole or in part) shall proceed at TfL's sole discretion and this EME or participation on in any future tender shall not constitute a commitment or guarantee of volume. As part of this EME, interested parties should note that TfL reserves the right, at its sole discretion, to develop any individual phase, any combination of phases, or none of the phases. Progression between phases is not guaranteed and remains subject to the TfL's continued business requirements, funding availability and internal approvals. The future procurement shall include defined break points at the end of each phase. TfL may, at its sole discretion, elect not to proceed to any subsequent phase without liability, other than for deliverables satisfactorily completed and accepted in accordance with the future Contract. No commitment is made to proceed beyond any phase, irrespective of the success of any preceding phase.

Risikoanalyse

Risikoanalyse er endnu ikke tilgængelig for dette lands udbud. I øjeblikket understøttet: Estland, Letland, Litauen, Polen, Frankrig, Storbritannien, Danmark, Holland, Norge og Finland.

Vinderstrategi

Få en AI-drevet vinderstrategi skræddersyet til dette udbud. Inkluderer sandsynlighedsscore for at vinde, vigtige muligheder og udfordringer, anbefalede fokusområder for tilbuddet, indsigt i konkurrencepositionering og handlingsrettede anbefalinger for at maksimere dine chancer.

Log ind

Konkurrenter

Opgrader for at se, hvilke virksomheder der sandsynligvis vil afgive tilbud på dette udbud, baseret på historiske indkøbsdata.

Log ind

Krav og kvalifikationer

AI udtrækker og organiserer alle krav fra udbudsdokumenter — obligatoriske kvalifikationer, tekniske specifikationer, finansielle betingelser og indsendelsesregler — tydeligt kategoriseret, så du ved præcis, hvad der kræves for at byde.

Log ind

Grundlæggende krav

  • Company registration in EU required
  • Proven track record in similar projects
  • Financial stability documentation

Dokumenter

3 dokumenter tilgængelige med AI-resuméer

OCDS RecordDOC
076454-2026_ocds_record.json

Intet resumé tilgængeligt for dette dokument.

Vis
OCDS Release PackageDOC
076454-2026_ocds_release.json

Intet resumé tilgængeligt for dette dokument.

Vis
Official PDF VersionPDF
076454-2026_official.pdf

Intet resumé tilgængeligt for dette dokument.

Vis

Forhåndsvisning af Dokumenter

Tilmeld dig for at se dokumentresuméer og analyser

Kvalitetsscore

Omfattende kvalitetsanalyse af dette udbud, der scorer juridisk overholdelse, klarhed, fuldstændighed, retfærdighed, praktisk anvendelighed, datakonsistens og bæredygtighed på en skala fra 0-100 med detaljeret opdeling og anbefalinger.

Log ind

Tilføj til pipeline