臺灣博碩士論文加值系統

在電腦產業中，儲存裝置的主流已逐漸從機械式硬碟轉換為固態硬碟，固態硬碟中最關鍵的零組件為快閃記憶體(NAND flash memory)，雖然快閃記憶體在研發及製程持續的投入，但品質方面依舊有讀寫次數的限制，也因此電腦產業對於使用固態硬碟時的品質問題改善，及訂定出相關的客服策略，便一直是個重要議題。
網路的發達、電腦運算能力的增強，加速了資料量取得及累積，產生了大資料、海量資料等名詞，為了能從海量資料中取得重要有用的資訊，而有了資料挖礦技術，而其中廣泛利用的是關聯規則。
本研究以A電腦公司為研究對象，蒐集其客戶於世界各地所發生的固態硬碟錯誤資料八千多筆，運用資料挖礦及使用資料分析工具orange，並選擇關聯規則演算法中有效率演算法(Frequent Pattern Growth, FP-Growth) 作運算，設定最小支持度九十，最小信賴度十為門檻以找出錯誤狀況的關聯規則，並且根據規則提出改善策略有三點，進而分別針對固態硬碟整體錯誤的改善及對固態硬碟不同錯誤情況的改善:
一、 使用關聯規則以加速客服人員判定固態硬碟錯誤狀況
二、 從案子和平台的關聯規則來優化品質策略
三、 從時間以及地點的關聯規則來優化客服策略

In NB industry, the marketing trend about storage device, from HDD transformation to SSD, the most important key component of SSD is called NAND flash memory, SSD industry keep research and development for more higher density SSD, but they did not specialty to improve Program and Erase cycle about NAND flash.
Therefore NB industry still worry about SSD’s quality and how to service their customer in the world wide service and plan their related strategy, it’s a big concern
The development of the Internet and the enhancement of computer computing power have accelerated the acquisition and accumulation of data, In order to obtain important and useful information from massive data, there is data mining technology, and the most widely used one is the association rule.
This research is based on A computer company data which collect function fail SSD information in the worldwide, through data mining and data analyst tool Orange to process algorithm (Frequent Pattern Growth, FP-Growth) for find out association rule, the accomplishment is find out the rule which can help RMA team to judge SSD symptom and setting the strategy to keep improve SSD quality. Propose three strategies as below:
1. Use association rule to support service team judge SSD symptom process
2. Base on project and platform association rule to optimize quality strategy
3. Base on time and country association rule to optimize service strategy

摘 要 I
Abstract II
目 錄 III
圖目錄 IV
表目錄 V
第一章 緒論 1
1-1研究背景與動機 1
1-2研究目的 2
1-3論文架構 2
第二章 產品及產業背景介紹 4
2-1產業背景 4
2-2固態硬碟介紹 4
2-3 相關文獻探討 8
第三章 研究方法 9
3-1資料分析概論 9
3-2資料挖礦方法與流程 9
3-3關聯規則及其演算法 11
3-4資料處理工具Orange 16
第四章 實驗步驟及結果分析 21
4-1實驗方法執行流程 21
4-2資料前置處理 22
4-3 orange 設置說明 27
4-4 關聯規則結果 29
4-4-1錯誤狀況為其他的關聯規則 29
4-4-2錯誤狀況為無法識別的關聯規則 32
4-4-3錯誤狀況為其餘存儲元件無法識別的關聯規則 33
4-4-4錯誤狀況為壞軌的關聯規則 34
4-4-5錯誤狀況為記憶體壞掉的關聯規則 35
4-5改善品質及客服策略 36
第五章 結論 43
5-1結論 43
參考文獻 45

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