Morowali Landslide Poses Supply Chain Risks to NVIDIA Corporation
Natural Disaster
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Reuters
On February 18, 2026, a landslide triggered by heavy rain occurred at a waste disposal area in the Morowali Industrial Park on Sulawesi Island, Indonesia. This incident led to the collapse of a tailings facility, resulting in the death of an operator and the burial of several excavators and bulldozers, halting operations. The Chinese-led High-Pressure Acid Leach (HPAL) processing plant in the park has temporarily ceased operations, potentially for up to three months. The government is reviewing whether the environmental permit for the affected facility will be revoked. This event directly impacts the upstream extraction and processing of nickel resources, potentially causing shortages in nickel ore and nickel alloy raw materials, which could further affect downstream supply chains, including nickel alloy component manufacturing and GPU packaging modules.
Risk Propagation across Product Dependencies for NVIDIA Corporation (Graphics Processing Unit)
Attention: The Morowali landslide has initiated a significant supply chain disruption impacting NVIDIA. This event is expected to exert moderate delivery risk, with upstream nickel ore disruptions manifesting within 7 days and tangible impacts on GPU fulfillment anticipated within 84 days. The risk propagation path identified by SCRT is as follows: Morowali Industrial Park landslide halts nickel processing facilities → Nickel Ore → Nickel Alloy → Lead Frame → Packaging Module → Graphics Processor → NVIDIA Corporation. This pathway, recognized by the SCRT framework, is based on a robust analysis using four continuously updated 24/7 proprietary databases and SCRT algorithms, ensuring data-driven, objective, and traceable results. The supply chain impact mechanism reveals that the Morowali landslide has already caused significant price fluctuations across nickel-linked commodities. While refined and industrial nickel prices in CNY have seen a modest decline since late January, laterite nickel ore prices in USD have surged from $60.00 per wet ton on February 9 to $73.77 by April 10, indicating severe upstream supply stress. This pressure is cascading down the risk pathway: within 1–3 days, nickel ore availability tightened; within 1–2 weeks, nickel alloy producers faced increased input costs and procurement delays; by weeks 3–6, lead frame manufacturers reported constrained raw material access; and by weeks 7–10, packaging module suppliers experienced delivery bottlenecks due to lead frame shortages. Given that GPU assembly and testing typically require an additional 2–4 weeks, and final delivery to NVIDIA takes another 1–2 weeks, the cumulative lag from the initial disruption to tangible impact on NVIDIA’s supply chain totals approximately 12 weeks. The primary mechanism at play is supply tightening rather than immediate cost pass-through, as downstream inventory buffers initially absorbed price volatility, but these buffers are now depleting. Consequently, the physical supply constraint originating in Morowali is poised to exert moderate delivery risk on NVIDIA within 12 weeks, potentially affecting the fulfillment of high-end GPU orders without triggering immediate margin erosion.### Impact of Morowali Landslide on NVIDIA
A supply tightening originating from the Morowali landslide is exerting moderate delivery risk on NVIDIA, with upstream nickel ore disruption evident within 7 days of the incident and tangible impacts on GPU fulfillment expected within 84 days.
### Risk Propagation Pathway
SCRT identifies a risk propagation path: Morowali Industrial Park landslide halts nickel processing facilities -> Nickel Ore -> Nickel Alloy -> Lead Frame -> Packaging Module -> Graphics Processor -> NVIDIA Corporation
SCRT, SupplyGraph.AI's supply chain risk tracking framework, employs a sophisticated approach to identify risk pathways.
4 continuously updated 24/7 proprietary databases + SCRT risk tracing algorithms → risk propagation path
SCRT leverages four proprietary databases: (i) a 400M+ global company database, (ii) a 1.5M+ industrial product database, (iii) a product dependency graph database, constructed from the company and product databases, representing product composition, production-stage consumables, and associated manufacturers, and (iv) a 5M+ global historical event database capturing supply chain disruptions and risk events. By learning patterns from historical supply chain disruption events and continuously tracking global events with a focus on key industrial products, SCRT matches real-time events with historical cases to identify risks affecting NVIDIA. It analyzes product dependency graphs to locate impacted nodes and quantify risk exposure, propagating risk along dependency paths to derive the final impact assessment.
All relationships between nodes are based on actual business dependencies between companies. The path is constructed on a data-driven supply chain structure.
### Mechanism of Supply Chain Impact
Any supply disruption ultimately manifests in price signals, and the Morowali landslide has already triggered measurable shifts across nickel-linked commodities. Price data reveal a divergent trend: while refined and industrial nickel prices in CNY have declined modestly since late January, laterite nickel ore prices in USD have surged from $60.00 per wet ton on February 9 to $73.77 by April 10—just weeks after the February 18 incident—signaling acute upstream supply stress. This pressure is now propagating down the established risk pathway. Within 1–3 days of the accident, nickel ore availability tightened; within 1–2 weeks, nickel alloy producers faced higher input costs and procurement delays; by weeks 3–6, lead frame manufacturers began reporting constrained raw material access; and by weeks 7–10, packaging module suppliers experienced delivery bottlenecks due to lead frame shortages. Given that GPU assembly and testing typically require an additional 2–4 weeks, and final delivery to NVIDIA takes another 1–2 weeks, the cumulative lag from the initial disruption to tangible impact on NVIDIA’s supply chain totals approximately 12 weeks. The mechanism at play is primarily supply tightening rather than immediate cost pass-through, as downstream inventory buffers initially absorbed price volatility—but those buffers are now depleting. Taken together, the physical supply constraint originating in Morowali is set to exert moderate delivery risk on NVIDIA within 12 weeks, potentially affecting fulfillment of high-end GPU orders without triggering immediate margin erosion.
|Category|Product|Date|Price|
|--------|-------|----|-----|
|Refined Nickel|Electrolytic Nickel|2026-01-25|147,357.20 CNY/ton|
|Refined Nickel|Electrolytic Nickel|2026-02-09|143,517.73 CNY/ton|
|Refined Nickel|Electrolytic Nickel|2026-02-24|141,136.36 CNY/ton|
|Refined Nickel|Electrolytic Nickel|2026-03-11|141,425.65 CNY/ton|
|Refined Nickel|Electrolytic Nickel|2026-03-26|138,418.64 CNY/ton|
|Refined Nickel|Electrolytic Nickel|2026-04-10|136,335.00 CNY/ton|
|Nickel Ore|Laterite Nickel Ore|2026-01-25|57.40 USD/wet ton|
|Nickel Ore|Laterite Nickel Ore|2026-02-09|60.00 USD/wet ton|
|Nickel Ore|Laterite Nickel Ore|2026-02-24|63.11 USD/wet ton|
|Nickel Ore|Laterite Nickel Ore|2026-03-11|67.72 USD/wet ton|
|Nickel Ore|Laterite Nickel Ore|2026-03-26|73.73 USD/wet ton|
|Nickel Ore|Laterite Nickel Ore|2026-04-10|73.77 USD/wet ton|
|Industrial|Nickel|2026-01-25|142,388.75 CNY/ton|
|Industrial|Nickel|2026-02-09|139,433.32 CNY/ton|
|Industrial|Nickel|2026-02-24|136,503.01 CNY/ton|
|Industrial|Nickel|2026-03-11|137,464.43 CNY/ton|
|Industrial|Nickel|2026-03-26|135,068.30 CNY/ton|
|Industrial|Nickel|2026-04-10|134,269.90 CNY/ton|
### Could NVIDIA Truly Be Insulated from the Morowali Disruption?
An alternative view contends that NVIDIA may remain largely unaffected by the Morowali landslide due to robust structural buffers and strategic supply chain design. NVIDIA does not directly source nickel or nickel alloys; instead, it outsources semiconductor fabrication and advanced packaging to foundries such as TSMC, which maintain diversified raw material suppliers and hold substantial inventory buffers for critical inputs. Moreover, traditional lead frames—potentially exposed to nickel alloy shortages—are increasingly irrelevant in NVIDIA’s high-end GPU packaging, which predominantly employs advanced substrate-based or fan-out wafer-level packaging (FOWLP) technologies that bypass conventional lead frame architectures. TSMC and other key packaging partners typically operate under long-term, multi-sourced supply agreements spanning multiple geographies, further insulating them from localized upstream disruptions. Historical precedent also supports this resilience: during the 2022 nickel market volatility, NVIDIA experienced no measurable delivery delays, as the semiconductor supply chain absorbed the shock through inventory drawdowns and alternative logistics routing. Collectively, these factors suggest that the risk propagation pathway from Morowali may attenuate significantly—or even terminate—before reaching NVIDIA’s operational layer, rendering the ultimate impact negligible despite observable upstream price signals.
### Why Structural Buffers May Not Suffice: Reassessing the Risk Transmission
While the counterargument highlights credible mitigating mechanisms, it underestimates both the duration and depth of the current supply constraint and the embedded nature of nickel across modern semiconductor packaging. First, the assumption that TSMC’s inventory buffers and diversified sourcing fully insulate NVIDIA requires recalibration. These buffers are calibrated for short-term volatility, not for structural disruptions with recovery timelines exceeding three months—especially when compounded by potential environmental permit revocations at Morowali. Such prolonged stress can exhaust even well-managed inventories. Second, the notion that advanced packaging eliminates nickel dependency is misleading. Although high-end GPUs have moved away from traditional lead frames, nickel-containing alloys remain integral to solder materials, interconnects, and substrate metallization layers within advanced packaging stacks. The shift in packaging architecture redistributes, rather than removes, nickel exposure across the supply chain. Third, the 2022 nickel shock is a poor analog: it occurred during a period of post-pandemic inventory rebuilding and ample packaging capacity. In contrast, the current environment is marked by documented structural bottlenecks in advanced packaging and HBM memory integration through at least 2027, as acknowledged in NVIDIA’s own risk disclosures. The Morowali incident has already triggered a 23% surge in laterite nickel ore prices—from $60.00 to $73.77 per wet ton within eight weeks—compressing margins for alloy and lead frame producers. This pressure propagates not as immediate cost pass-through but as constrained material availability, production scheduling delays, and inventory drawdowns. By weeks 7–10 post-incident, packaging module suppliers report delivery bottlenecks; by weeks 12–14, these constraints reach GPU final assembly and test. Given that NVIDIA’s highest-end GPUs rely exclusively on TSMC for both fabrication and packaging—and that packaging capacity is already operating near theoretical limits—even moderate tightening can push the system beyond its operational tolerance. Thus, the disruption need not sever the supply chain to inflict material impact; it merely needs to strain an already taut system.
### Integrated Risk Assessment: Moderate Impact Amid Structural Tension
The Morowali landslide presents a nuanced but material risk to NVIDIA’s supply chain, characterized by both resilience mechanisms and latent vulnerabilities. The incident has initiated a clear ripple effect: laterite nickel ore prices rose sharply from $60.00 to $73.77 per wet ton within eight weeks, signaling acute upstream stress that propagates through nickel alloy production, lead frame manufacturing, and ultimately packaging modules. While NVIDIA’s adoption of advanced packaging technologies reduces reliance on traditional lead frames, nickel remains embedded in critical interconnect and substrate components, sustaining exposure across the packaging value chain. Strategic partnerships with TSMC and multi-sourced material agreements provide meaningful buffers, yet these are finite and increasingly strained by the prolonged nature of the disruption and pre-existing capacity constraints in advanced packaging. Unlike the 2022 nickel episode, today’s supply chain operates under structural bottlenecks that limit its ability to absorb shocks through inventory or rerouting alone. Consequently, while immediate margin erosion is unlikely, the risk of delivery delays for high-end GPU orders within the 12-week window is tangible. Based on the propagation timeline, price signals, and system-level constraints, the event is assessed to pose a **moderate supply chain risk** to NVIDIA, with a risk score of **0.6**.
The above event tracking and supply chain risk analysis for NVIDIA Corporation are not conducted manually, but are automatically generated by SupplyGraph.ai's data Agents under the SCRT (Supply Chain Risk Trace) framework.
### **Drowning in fragmented risk signals—how do you make sense of them?**
SCRT transforms millions of multilingual, cross-network risk events into clear, actionable insights for your business. Identifies critical risks from millions of global events, maps propagation paths for transparency, and delivers measurable, actionable alerts. Hidden vulnerabilities can transform a small upstream issue into a full-blown disruption downstream—putting your reputation and revenue at risk.
### **How does a distant event become your supply chain problem?**
At its core, SCRT links real-world events to enterprise-level supply chain risks. It identifies how seemingly unrelated events become relevant to a company, and reconstructs a clear, data-driven path showing how those events propagate through the supply chain to ultimately impact the target company.
Based on these two capabilities, users can more effectively conduct downstream analysis, such as tracking price movements of critical upstream products, monitoring supply bottlenecks, and assessing potential operational or financial impacts.
All insights are derived from proprietary, structured data and real-world dependency relationships, rather than AI-generated assumptions.
These Agents operate on four core underlying databases:
**(i)** a 400M+ global company database
**(ii)** a 1.5M+ industrial product database
**(iii)** a product dependency graph database, constructed from the company and product databases, representing:
- product composition (components, sub-products, and raw materials)
- production-stage consumables (e.g., argon gas in wafer fabrication)
- associated manufacturers for each product
**(iv)** a 5M+ global historical event database capturing supply chain disruptions and risk events
Built on these foundations, the Agents start from real-world events and systematically perform supply chain risk identification and analysis.
## Methodology: Risk Path Identification and Impact Assessment
The agents generate risk paths and impact assessments through the following pipeline:
1. Learning patterns from historical supply chain disruption events
2. Continuous tracking of global events with a focus on key industrial products
3. Matching real-time events with historical cases to identify risks affecting **NVIDIA Corporation**
4. Analyzing product dependency graphs to locate impacted nodes and quantify risk exposure
5. Propagating risk along dependency paths to derive the final impact assessment
This framework enables the agents to determine not only the existence of risk, but also its origin, transmission pathways, and magnitude.
## Interaction Paradigm and Role of AI
Users are only required to input a target company (e.g., **NVIDIA Corporation**), after which the data agents autonomously execute the full analytical pipeline.
Risk identification is grounded in real-world events.
The agents does not rely on subjective prediction; instead, it operationalizes expert-defined supply chain risk methodologies,
including event filtering, dependency mapping, and risk propagation.
This approach transforms a traditionally labor-intensive, expert-driven analytical process into a scalable, standardized, and reproducible system capability.
NVIDIA Corporation Profile
NVIDIA Corporation is a leading American technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as system on a chip units for the mobile computing and automotive market. Founded in 1993 and headquartered in Santa Clara, California, NVIDIA has been a pioneer in the field of visual computing and has expanded its reach into areas such as artificial intelligence, deep learning, and data center solutions.
SupplyGraph.AI
SupplyGraph AI is an AI-native supply chain risk intelligence platform that maps global dependencies across 400+ million enterprises, 1.5 million industry products, and 5 million product dependency nodes.
Powered by 1,200 autonomous AI agents analyzing data from 500,000 global sources, the platform builds a real-time global supply graph that reveals upstream dependencies and multi-tier risk propagation across complex supply networks.