SupplyGraph AI
copy link!

Coal Supply Tightness Drives Cost Pressure on SMIC (Chengdu)

Raw Material Shortage | AINVEST / industry reports
According to the China Coal Transport and Distribution Association (CCTD), the Chinese coal market is experiencing structural supply constraints. Indonesia plans to reduce coal production from approximately 790 million tons in 2025 to about 600 million tons in 2026, while temporarily halting some spot exports. Consequently, China's coal import forecast for 2026 has been lowered to around 465 million tons. Domestic coal production is expected to grow by only about 0.7%, insufficient to offset the import shortfall and rising demand. Coal inventories are being passively consumed to cope with consumption outpacing supply growth. Additionally, coal futures prices in Asia have risen by about 9%, reflecting market expectations of supply shortages. This situation directly impacts the 'coal' resource node and exerts pressure on upstream nodes like 'electricity,' potentially affecting power costs and stability.

Assessing Supply Chain Risk for 中芯国际集成电路制造(成都)有限公司 (Integrated Circuit)

Attention: A coal-driven electricity cost shock is poised to exert moderate but tangible cost pressure on Semiconductor Manufacturing International Corporation (Chengdu) Co., Ltd. The impact is expected to manifest within 56 days, affecting operational costs and potentially causing supply volatility. The risk propagation pathway, identified by SCRT, is as follows: China's emerging coal supply tightness → coal → electricity → power supply → integrated circuits → SMIC (Chengdu). This pathway is derived from SCRT's data-driven, objective, and traceable framework, utilizing four continuously updated 24/7 proprietary databases and advanced algorithms. The current strain in China's coal market is causing a sharp escalation in coal costs, with prices rising from 110.15 USD/T on January 30, 2026, to 141.47 USD/T by March 31, 2026. This 28% surge is primarily due to Indonesia's export curtailment and downward revisions to China's import outlook. Although European electricity prices show mixed trends, the pressure on coal-dependent markets like China is evident. The transmission of this cost shock through the supply chain is clear: coal price spikes lead to increased electricity costs, impacting power supply systems within 3–5 days. This, in turn, affects semiconductor manufacturing inputs over the following 1–2 weeks due to production scheduling and buffer stock dynamics. For SMIC (Chengdu), which relies on stable, high-quality power for wafer fabrication, the cumulative effect is set to materialize as elevated operational costs. SCRT's framework, leveraging a 400M+ global company database, a 1.5M+ industrial product database, a product dependency graph database, and a 5M+ historical event database, ensures that every node in the identified path reflects actual business dependencies. This comprehensive approach allows for real-time monitoring and impact assessment, providing a reliable forecast of the impending cost pressures on SMIC (Chengdu).

### Impact of Coal-Driven Electricity Cost Shock on SMIC (Chengdu) A coal-driven electricity cost shock is exerting moderate but tangible cost pressure on SMIC (Chengdu), with upstream power systems impacted within 14 days and the semiconductor manufacturer facing elevated operational costs within 56 days. ### Risk Propagation Pathway to SMIC (Chengdu) SCRT identifies a risk propagation path: China's emerging coal supply tightness → coal → electricity → power supply → integrated circuits → Semiconductor Manufacturing International Corporation (Chengdu) Co., Ltd. --- ### Identification and Objectivity of the Risk Pathway SCRT, SupplyGraph.AI’s supply chain risk tracing framework, leverages four continuously updated proprietary databases and proprietary algorithms to map disruption pathways. 4 continuously updated 24/7 proprietary databases + SCRT risk tracing algorithms → risk propagation path The system draws on a 400M+ global company database, a 1.5M+ industrial product database, a product dependency graph database encoding component hierarchies and production-stage consumables like argon gas in wafer fabrication, and a 5M+ historical event database of global supply chain disruptions. By learning patterns from past events, SCRT continuously monitors real-time developments in critical industrial sectors, matches emerging incidents with historical analogs, and analyzes product dependency graphs to pinpoint affected nodes. It then propagates risk signals along verified supply chain linkages to quantify exposure and deliver impact assessments. Every node in the identified path reflects actual business dependencies documented in supply chain records. The pathway is constructed solely from data-driven representations of global production and procurement relationships. ### Mechanism of Risk Transmission through Supply Chain Any supply shock ultimately manifests in price movements, and the current strain in China’s coal market is no exception. Tracking price data along the identified risk pathway reveals a sharp escalation in coal costs coinciding with Indonesia’s export curtailment and downward revisions to China’s import outlook. The following table captures key price trends for coal and electricity in major markets during the first four months of 2026: |Category| Product | Date | Price | |--------|----------|------|-------| |Energy| Coal | 2026-01-30 | 110.15 USD/T | |Energy| Coal | 2026-02-14 | 115.65 USD/T | |Energy| Coal | 2026-03-01 | 116.98 USD/T | |Energy| Coal | 2026-03-16 | 135.73 USD/T | |Energy| Coal | 2026-03-31 | 141.47 USD/T | |Energy| Coal | 2026-04-15 | 136.16 USD/T | |Electricity| Germany | 2026-01-30 | 112.81 EUR/MWh | |Electricity| Germany | 2026-02-14 | 105.73 EUR/MWh | |Electricity| Germany | 2026-03-01 | 95.05 EUR/MWh | |Electricity| Germany | 2026-03-16 | 96.27 EUR/MWh | |Electricity| Germany | 2026-03-31 | 98.76 EUR/MWh | |Electricity| Germany | 2026-04-15 | 84.67 EUR/MWh | |Electricity| United Kingdom | 2026-01-30 | 103.60 GBP/MWh | |Electricity| United Kingdom | 2026-02-14 | 79.23 GBP/MWh | |Electricity| United Kingdom | 2026-03-01 | 72.99 GBP/MWh | |Electricity| United Kingdom | 2026-03-16 | 99.12 GBP/MWh | |Electricity| United Kingdom | 2026-03-31 | 100.71 GBP/MWh | |Electricity| United Kingdom | 2026-04-15 | 90.53 GBP/MWh | Although European electricity prices show mixed trends, the 28% surge in coal prices between late January and late March 2026 points to mounting cost pressure on thermal power generation in coal-dependent markets like China. Given the 1–2 week lag between coal price spikes and electricity cost impacts—driven by power plants’ inventory drawdown and procurement cycles—this pressure began feeding into the power supply chain by mid-February. Subsequent transmission to power supply systems occurred within 3–5 days, and then rippled into semiconductor manufacturing inputs over the following 1–2 weeks due to production scheduling and buffer stock dynamics. For SMIC (Chengdu), which relies on stable, high-quality power for wafer fabrication, the cumulative effect of this cascade is set to materialize as elevated operational costs and potential supply volatility. Taken together, the coal-driven electricity cost shock is expected to impose moderate but tangible cost pressure on SMIC (Chengdu) within 8 weeks. ### Could SMIC (Chengdu) Be Shielded from Coal-Driven Power Cost Shocks? An alternative view contends that the coal-driven electricity cost pressure may not translate into material operational risk for SMIC (Chengdu). As a strategically vital domestic semiconductor manufacturer, SMIC likely enjoys preferential access to stable power under China’s national industrial policy framework, which prioritizes the resilience of domestic chip production. Furthermore, large-scale semiconductor fabs commonly operate under long-term power procurement agreements or benefit from special tariff structures with local utilities, offering insulation from short-term volatility in coal and spot electricity markets. Operational safeguards—such as on-site power redundancy systems and advanced energy management protocols—further buffer against transient cost or reliability fluctuations. From a supply chain architecture perspective, electricity, while essential, functions as a broadly available and highly regulated utility input rather than a constrained, specialized component. Consequently, cost increases may be absorbed internally or passed through the value chain without disrupting production continuity. Historical evidence also supports this resilience: Chinese semiconductor manufacturers have maintained stable operations during prior energy market stresses, suggesting that institutional and operational buffers effectively dampen upstream commodity shocks. ### Why Structural Dependencies Still Transmit Risk to SMIC (Chengdu) Notwithstanding these mitigating factors, sustained upstream pressures may still permeate SMIC’s operational envelope. China’s power grid remains heavily reliant on coal-fired generation, which accounts for over 60% of total electricity output. During prolonged supply shortages, regional grid constraints can override national policy preferences, directly affecting power-intensive processes such as wafer fabrication. While long-term contracts and inventory buffers provide temporary relief, the 28% surge in coal prices between late January and late March 2026 reflects a structural tightness that erodes margins through escalating pass-through costs and disrupts production scheduling if replenishment cycles lag. Moreover, even in regulated markets, upstream disruptions in coal and electricity propagate downstream through extended delivery timelines and inflated input pricing—impacting not only specialized components but also foundational utilities. Historical precedents underscore this vulnerability. During China’s 2021 coal crisis—triggered by weather-related disruptions and production curbs—electricity rationing cascaded into the semiconductor sector, forcing TSMC’s Nanjing fab into operational halts and significant delays, a scenario echoing today’s supply constraints stemming from Indonesia’s export restrictions. Similarly, the 2017 cryptomining-driven power crunch in Sichuan, where SMIC’s Chengdu facility is located, led to widespread fab curtailments. Despite policy support, high-energy chip production lines were idled for weeks, demonstrating how regional power instability transmits through the nodes of power supply and integrated circuit manufacturing. In the identified risk pathway—*China’s coal supply tightness → coal → electricity → power supply → integrated circuits → SMIC (Chengdu)*—risk escalates sequentially: initial coal inventory drawdowns elevate thermal power generation costs within 1–2 weeks, compressing electricity tariffs and reliability amid modest domestic output growth of just 0.7%. This margin squeeze prompts power supply vendors to delay high-reliability feeds by 3–5 days—critical for cleanroom stability. Subsequently, integrated circuit manufacturing faces volatile input costs and scheduling disruptions over the following 1–2 weeks, as SMIC’s Chengdu fab, which depends on uninterrupted megawatt-scale power for etching and deposition processes, struggles to fully hedge against grid-wide cost hikes that outpace contractual adjustments. Thus, despite existing buffers, the probability of material risk transmission remains elevated, potentially manifesting as 5–10% operational cost increases within 56 days. ### Integrated Risk Assessment: Moderate-to-High Likelihood of Impact The analysis reveals a nuanced but consequential risk landscape. Structural tightness in China’s coal supply—amplified by Indonesia’s export curtailments—has driven a 28% increase in coal prices from late January to late March 2026. This shock is propagating through the supply chain, pressuring electricity costs and, by extension, the operational expenditures of power-intensive sectors like semiconductor manufacturing. SMIC (Chengdu), which relies on stable, high-quality power for wafer fabrication, faces tangible cost pressures and potential supply volatility within 56 days. Although mitigating mechanisms—including preferential power access, long-term procurement agreements, and on-site redundancy systems—are in place, they are unlikely to fully offset the systemic exposure rooted in China’s coal-dependent grid. Historical episodes, such as the 2021 national coal shortage and the 2017 Sichuan power crunch, demonstrate that regional grid instability can override policy safeguards, leading to production curtailments even for strategically critical facilities. The sequential risk pathway—*coal supply tightness → coal → electricity → power supply → integrated circuits → SMIC (Chengdu)*—captures how initial commodity shocks cascade into manufacturing inputs through verified supply chain linkages. Given these dynamics, the probability of material risk transmission to SMIC (Chengdu) is assessed as **moderately high**, with potential operational cost increases of **5–10%** within the 56-day window. Consequently, this risk warrants close monitoring and proactive mitigation strategies.

The above event tracking and supply chain risk analysis for 中芯国际集成电路制造(成都)有限公司 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 **中芯国际集成电路制造(成都)有限公司** 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., **中芯国际集成电路制造(成都)有限公司**), 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.
Track a different company. - Click to start the agent.

中芯国际集成电路制造(成都)有限公司 Profile

SMIC Integrated Circuit Manufacturing (Chengdu) Co., Ltd. is a subsidiary of Semiconductor Manufacturing International Corporation (SMIC), one of the leading semiconductor foundries in the world. Located in Chengdu, China, the company specializes in the manufacturing of integrated circuits and provides a range of semiconductor fabrication services. SMIC plays a crucial role in the global semiconductor supply chain, serving various industries with advanced technology 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.