• Title/Summary/Keyword: 수명 예측 최적화

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A method for optimizing lifetime prediction of a storage device using the frequency of occurrence of defects in NAND flash memory (낸드 플래시 메모리의 불량 발생빈도를 이용한 저장장치의 수명 예측 최적화 방법)

  • Lee, Hyun-Seob
    • Journal of Internet of Things and Convergence
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    • v.7 no.4
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    • pp.9-14
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    • 2021
  • In computing systems that require high reliability, the method of predicting the lifetime of a storage device is one of the important factors for system management because it can maximize usability as well as data protection. The life of a solid state drive (SSD) that has recently been used as a storage device in several storage systems is linked to the life of the NAND flash memory that constitutes it. Therefore, in a storage system configured using an SSD, a method of accurately and efficiently predicting the lifespan of a NAND flash memory is required. In this paper, a method for optimizing the lifetime prediction of a flash memory-based storage device using the frequency of NAND flash memory failure is proposed. For this, we design a cost matrix to collect the frequency of defects that occur when processing data in units of Drive Writes Per Day (DWPD). In addition, a method of predicting the remaining cost to the slope where the life-long finish occurs using the Gradient Descent method is proposed. Finally, we proved the excellence of the proposed idea when any defect occurs with simulation.

Optimization of the Tool Life Prediction Using Genetic Algorithm (유전 알고리즘을 이용한 공구 수명 예측 최적화)

  • Kong, Jung-Shik
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.11
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    • pp.338-343
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    • 2018
  • Recently, a computer numerical control (CNC) machine is used widely for mold making in various industries. In the operation of a CNC machine, the production quality and safety of workers are becoming increasingly important as the product process increases. A variety of tool life prediction studies has been conducted to standardize the quality of production and improve reproducibility. When the tool life is predicted using the conventional tool life equation, there is a large error between the experimental result and result by the conventional tool life equation. In this paper, an algorithm that can predict the precise tool life was implemented using a genetic algorithm.