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Aisin considers price pass-throughs amid growing concerns over DRAM shortages in automotive supply chain
Tuesday, March 10, 2026 at 08:05 PM
Aisin is considering passing through costs as concerns grow regarding a potential shortage of DRAM components in the automotive supply chain. The company is signaling a transition to a more constrained supply environment for memory chips used in vehicle parts.
Context
The Japanese automotive Tier 1 supplier Aisin is considering price pass-throughs as it prepares for a projected DRAM shortage expected to impact the global automotive supply chain by Q1 2026. While Aisin anticipates the direct internal impact on its operations may be limited, the broader risk of disruption within the Toyota Group ecosystem has prompted the company to explore risk diversification and price adjustments. The looming memory crunch is largely attributed to leading manufacturers like Samsung and SK Hynix pivoting production capacity toward High Bandwidth Memory (HBM) for AI data centers, reducing the supply of traditional automotive-grade memory.
This development comes as Aisin reports a strong FYE2026 2Q performance, with revenue reaching 2,472.0 billion yen and operating profit jumping 70.9% to 96.0 billion yen. Despite these gains, the supplier faces rising costs from electrification and geopolitical supply risks, such as the recent Nexperia export halt. By signaling potential price increases now, Aisin is attempting to protect its margins against structural shifts in the semiconductor industry that prioritize high-margin AI chips over general-purpose automotive components.
Sources (8)
[PDF] AISIN Sustainability Data Book 2024Automotive Technology Insight | Forecasts | Industry News | Supply Chain auto chip shortage, Page 17 - KED GlobalToyota, suppliers weather Nexperia chip export halt with minimal disruptionList of Aisin transmissions - WikipediaElectronic Components Sales Market Analysis and Forecast
AISIN Selects Siemens for AUTOSAR ECU Development - EE Times Asia Automotive Grade DRAM Market with Geographic Segmentation,
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