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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsKIOXIA says its Yokkaichi Plant uses AI to help engineers analyze manufacturing and inspection data at a scale difficult to handle by intuition alone. The company reports that its production and test systems generate about 3 billion data points a day; AI-assisted analysis helps identify defect causes and improvement opportunities, while engineers decide what the findings mean and what actions to take.
What the Yokkaichi Plant makes and how large it is
The plant is in Yokkaichi City, Mie Prefecture, Japan, and manufactures flash memory. KIOXIA also identifies SSDs among the products associated with the facility. The company says the plant was established in 1992 and that Fab 7 was completed in 2022. Its July 2025 feature describes the site as a large, continually evolving manufacturing complex.
| Plant detail | KIOXIA-reported figure |
|---|---|
| Site area | 694,000 square meters, which KIOXIA compares with about 98 soccer fields (2025) |
| Production facilities | Seven (2025) |
| Workers | Approximately 10,000 (2025) |
| Data generated | About 3 billion data points per day from production and testing systems (2025) |
These figures are KIOXIA’s descriptions of its own facility, not independently measured comparisons. The company’s Yokkaichi Plant page gives current facility information.
Why KIOXIA says the plant uses AI
Flash-memory manufacturing produces information across many stages: equipment readings, inspection results, wafer transport and cleanroom operations, as well as detailed tests of finished memory. KIOXIA says those systems together generate about 3 billion data points per day. The practical challenge is turning that volume into useful signals about quality, process conditions and productivity.
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In a KIOXIA-hosted interview published July 21, 2025, process integration engineer Yukako Tanaka described the breadth of that information: “The entire lifecycle of wafers, from the moment they enter the cleanrooms through the manufacturing process to the moment they leave as finished products, is converted into data.”
KIOXIA describes using machine learning to estimate possible defect causes, deep learning to classify images, and analytics to locate issues and potential process improvements. Its smart-factory overview says fab data are collected, structured and stored for big-data analysis. It also describes digital representations of sensor data, human task records, judgments and text that can be used in AI-based analysis and simulation.
The company presents AI as decision support rather than an autonomous factory operator. Analysis can clarify patterns and uncertainty; engineers still determine which problem matters, interpret the results and choose whether to adjust a process. Tanaka said, “This would not be possible if you had to rely solely on an engineer’s intuition. It has only become possible with the advances in data analysis made possible by AI. If we can feed highly reliable results back into the manufacturing process, improvements can be made more quickly. AI gives us the materials on which to build decision-making,”
KIOXIA reports one example: automated defect analysis reduced analysis time by 99%. The company’s feature does not provide all baseline details or describe an independent evaluation, so this is a reported example for that application—not a general performance guarantee or a verified estimate of plant-wide savings.
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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →More detail on the data flow and digital representations appears in KIOXIA’s Smart Factory overview.
How KIOXIA describes AI training for engineers
KIOXIA’s July 2025 interview feature describes internal AI projects and workshops, with a focus on helping engineers—particularly younger engineers—learn how to apply AI to manufacturing work. Projects may run for several months to half a year and conclude with poster-style presentations. The feature says the initiative grew from three people at its start to 200 participants over two years. These are company-reported participation figures; they do not establish that every engineer completed training or received a formal credential.
The program is framed as practical adoption, not simply instruction in AI tools. KIOXIA describes the need to coordinate the people who build applications, the engineers who use them and the company’s IT infrastructure. That approach reflects the plant’s operating reality: useful analysis depends on engineering context and on systems that make relevant data accessible.
Separate from AI workshops, KIOXIA’s 2025 environmental report says annual environmental and energy education is provided to employees working on the premises, including employees of resident companies. That is a distinct program, not evidence about AI-training participation.
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How this fits the plant’s wider manufacturing role
Yokkaichi’s scale and data-intensive workflow help explain why KIOXIA emphasizes both analytics and people. Plant general manager Kazuhiro Shimizu said, “Engineers are entering a phase where they must consider how to utilize AI while developing products,” and, “While it’s important to use IT and AI to aim for higher productivity, it’s the employees working here that are the real backbone of the factory,”
The facility also operates within a long-running manufacturing partnership. On January 29, 2026, KIOXIA and SanDisk announced a five-year extension of their Yokkaichi joint-venture agreements: agreements that had been due to expire on December 31, 2029, now run through December 31, 2034. The companies said the arrangement supports stable production of advanced 3D flash memory. This agreement provides partnership context; it does not independently validate the plant’s AI results.
For the company’s account of its AI work and training initiative, see the July 2025 interview feature. KIOXIA’s broader plant description is in its July 2025 smart-factory feature, and its environmental-education description is in the 2025 Yokkaichi Plant Environmental Report.
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