South Korean media reports that delivery cycles for key semiconductor equipment components have "more than doubled."

The surge in semiconductor demand driven by artificial intelligence is spreading upstream in the industry chain, creating severe bottlenecks in key component manufacturing. South Korean industry sources indicate that delivery times for core components needed for semiconductor manufacturing equipment have generally more than doubled, with some key components manufactured in Japan experiencing wait times as long as 40 months. These supply chain delays not only threaten the normal production schedules of equipment manufacturers but may also impact the capital expenditure plans of major global chipmakers such as Samsung Electronics and SK Hynix.

According to South Korea's Electronic News on September 16, citing industry sources, several South Korean semiconductor equipment companies have reported increasingly severe difficulties in procuring components. An executive at deposition equipment manufacturer A stated that the delivery cycle for related components has extended from four months to ten months. Laser process equipment manufacturer B faces an even more extreme situation, with the wait time for its required key components manufactured in Japan now extended to 40 months, and even paying a premium cannot expedite delivery.

Industry insiders warn that the combined effect of component shortages and equipment delivery delays will significantly increase the likelihood of postponements in global semiconductor manufacturing infrastructure investment , potentially impacting ongoing projects at Samsung Electronics in Pyeongtaek and SK Hynix in Longin.

Surge in demand overwhelms supply chains

The immediate trigger for this round of component shortages is the surge in demand driven by the AI wave. With the significant increase in shipments of AI semiconductors and memory chips, the demand for semiconductor manufacturing equipment has expanded dramatically. However, suppliers of core components such as modules, upon which equipment production depends, failed to expand their production capacity in advance, thus creating a supply-demand gap.

An industry insider bluntly stated, "Even if component manufacturers start expanding production now, they will not be able to meet current demand." He also pointed out that due to the uncertainty surrounding when the AI-driven semiconductor supercycle will end, component manufacturers are generally taking a wait-and-see approach to large-scale capacity expansion investments. This is especially true for the Japanese component industry—as a crucial pillar of semiconductor equipment manufacturing, Japanese suppliers have historically been conservative in their capacity investment , a characteristic that is particularly evident in the current tight supply situation.

Packaging equipment manufacturer Company C, despite having established a domestic component supply chain, was not immune to the impact. An executive at the company stated that while domestic sourcing was better than overseas, delivery times were still about 50% longer than normal – components that previously took four months to arrive now require more than six months.

Equipment delivery delays propagate downstream

The pressure of component shortages has been transmitted downstream in the supply chain to the equipment delivery stage. It is understood that semiconductor manufacturers are currently experiencing twice the normal time to receive equipment, with major global chip manufacturers, currently undergoing large-scale capital expenditure cycles, being particularly affected.

A semiconductor equipment industry insider predicted that "the combination of equipment delivery delays and component supply shortages has significantly increased the likelihood of delays in global semiconductor production infrastructure investment," and specifically named Samsung Electronics' Pyeongtaek project and SK Hynix's Longin project as being affected.

This means that South Korea's domestic capacity expansion plan, which was originally considered one of the main investment themes in AI infrastructure, is facing substantial obstacles from the supply chain level.

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