Efficient Machine Learning Methods for Hard Disk Drive Yield Prediction Improvement

Hirunyawanakul, Anusara; Kerdprasop, Nittaya; Kerdprasop, Kittisak

doi:10.18178/ijmlc.2020.10.2.926

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A Hard Disk Drive1

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2024

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Cited by 2 publications

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“…The HDD is a non-volatile digital data storage device that utilizes magnetic storage technology to store and retrieve data on durable material disks [8]. The production of HDD involves the assembly of hardware components sourced from various vendors, performed by each production machine.…”

Section: A Hard Disk Drivementioning

confidence: 99%

Building a Rule-Based Expert System to Enhance the Hard Disk Drive Manufacturing Processes

Kirdponpattara,

Sooraksa,

Boonjing

2024

IEEE Access

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The manufacturing of hard disk drives involves the intricate assembly of numerous components, making the testing process time-consuming and resource intensive. To optimize the manufacturing process and increase testing efficiency, the development of a rule-based expert system is proposed. This system leverages predictive models constructed from assembly process data to identify potentially defective hard drives before undergoing extensive testing. By preemptively identifying defects, this approach substantially reduces testing time and enhances tester capacity. Given the categorical and imbalanced nature of assembly data, Decision Trees are employed as the prediction model. Specifically, three Decision Tree algorithms are explored: ID3, C4.5, and CART. In addition, four feature selection techniques, namely Information

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Section: A Hard Disk Drivementioning

confidence: 99%