<p>Disruptions in machine-tool component supply can propagate to downstream capital-goods production through bottleneck parts, requalification delays, and commissioning losses. This study develops a T2NN–ITARA–ALWAS decision-support framework for diagnosing supplier disruption risk in a focal machine-tool component supply network. Using a three-round Delphi process with eight experts, 19 disruption risk factors are identified and organized into four dimensions: disasters and public health events, external human disruptions, policy and institutional risks, and internal system and operational failures. The experts then evaluate the severity and occurrence of these factors for 13 key suppliers in a cross-border supply base. Type-2 neutrosophic numbers are used to preserve expert hesitation and indeterminacy, ITARA derives objective criterion weights, and ALWAS generates composite supplier risk scores and rankings. The results identify earthquakes, insufficient IT infrastructure, political and regulatory instability, nationalism, and quality problems as the most discriminative disruption drivers, and reveal a clear high-risk supplier tier. Comparisons with benchmark MCDM aggregators indicate that the proposed ranking is largely stable. Robustness is further examined through three sensitivity analyses involving changes in the ITARA indifference threshold, the weight of the most influential criterion, and the relative importance of the two ALWAS aggregation strategies. The study provides an auditable decision-support approach for supplier segmentation and continuity planning, and offers empirical evidence on the disruption drivers that most strongly differentiate supplier risk exposure in capital-goods supply networks.</p>