A data-driven life cycle cost model for tender evaluation of metro pantograph carbon strips.

Statistical analysis of pantograph carbon strip procurement reveals substantial performance variation among suppliers and indicates that prevalent scoring methods often fall into a “low-bid trap,” yielding economically suboptimal outcomes. To address this issue, this study introduced a data-driven, discounted life cycle cost bidding model and applied it to Chongqing Metro Line 6 as a case study. The model treats high-frequency consumable expenditures as uniform annuity streams and integrates empirically estimated wear rates and service life variability into net present value cost functions for procurement, maintenance, inventory, and mileage non-compliance penalties. Application of the model produced a pronounced rank reversal: the supplier selected by the traditional lowest-bid rule incurred a life cycle cost roughly 1.6 times that of the best-value supplier. Sensitivity analysis showed that this cost-ratio and the resulting ranking did not change for discount rates between 0% and 8%, demonstrating that the economic advantage of greater durability persists when the time value of money is considered. Unlike static weighting schemes, the proposed framework explicitly monetizes both engineering variability and timing of cash flows, offering a principled basis to distinguish suppliers by actual operational value and thereby reducing adverse selection in public-transit infrastructure procurement.