UNSPSC 41112805: Rail downthrow measuring instrument

An instrument that measures the maximum downthrow volume of the running rail with the dynamic load conveyed from the train when it passes the train.

UNSPSC 41112805 Rail downthrow measuring instrument is a Commodity code that captures equipment and systems for rerailing and repositioning rail vehicles, specifically the specialized hydraulic lifting, jacking, cribbing, and support apparatus used by transit authorities to recover derailed or disabled rail cars. State and local governments procuring under this code are primarily transit authorities operating heavy rail and light rail systems. The Metropolitan Transit Authority of Harris County, Texas (METRO) exemplifies the typical buyer, soliciting comprehensive rerailing systems including lifting beams, hydraulic cylinders, pumps, hoses, control manifolds, and custom-outfitted support trucks. Contractors typically furnish equipment fabrication, installation, testing, operator training, and warranty coverage spanning three years from the manufacturer and one year for workmanship; all equipment must be new and suitable for repeated service in transit operations.

METRO issued an Invitation for Bids (IFB) on March 16, 2026 (IFBDOC2034259016) for rerailing equipment supply and re-rail truck outfitting, with sealed bids due April 15, 2026, via electronic submission through the EUNA (Bonfire) platform plus one hard copy, and public bid opening on April 16, 2026. The procurement included a pre-bid briefing on March 23, 2026, written question deadlines of March 26, 2026, and METRO's response commitment by March 31, 2026. The contract carries no small business participation goal and is 100% METRO-funded with no set-aside designations. The contract term runs one year from the effective date with an optional month-to-month extension for up to six additional months at the same prices and terms. Recent activity under this code appears limited to Texas transit authorities; no other state or local opportunities were identified in the source data.