• 葉青峻
    葉青峻 2021/03/10 09:31

    晶片處理高度有序化的本質增加了對不同處理步驟之間度量方法的需求。晶片測試度量裝置被用於檢驗晶片仍然完好且沒有被前面的處理步驟損壞。如果If the number of dies—the 積體電路s that will eventually become chips—當一塊晶片測量失敗次數超過一個預先設定的閾值時,晶片將被廢棄而非繼續後續的處理製程。
    晶片處理高度有序化的本質增加了對不同處理步驟之間度量方法的需求。晶片測試度量裝置被用於檢驗晶片仍然完好且沒有被前面的處理步驟損壞。如果If the number of dies—the 積體電路s that will eventually become chips—當一塊晶片測量失敗次數超過一個預先設定的閾值時,晶片將被廢棄而非繼續後續的處理製程。


    化學氣相沉積 (CVD)
    物理氣相沉積 (PVD)
    分子束磊晶 (MBE)
    電化學沉積 (ECD),見電鍍
    化學機械平坦化 (CMP)

    IC Assembly and Testing 封裝測試
    Wafer Testing 晶片測試
    Visual Inspection外觀檢測
    Wafer Probing電性測試
    FrontEnd 封裝前段
    Wafer BackGrinding 晶背研磨
    Wafer Mount晶圓附膜
    Wafer Sawing晶圓切割
    Die attachment上片覆晶
    Wire bonding焊線
    BackEnd 封裝後段
    Post Mold Cure後固化
    De-Junk 去節
    Plating 電鍍
    Marking 列印
    Trimform 成形
    Lead Scan 檢腳
    Final Test 終測
    Electrical Test電性測試
    Visual Inspection光學測試
    Baking 烘烤



    Device yield

    Device yield or die yield is the number of working chips or dies on a wafer, given in percentage since the number of chips on a wafer (Die per wafer, DPW) can vary depending on the chips' size and the wafer's diameter. Yield degradation is a reduction in yield, which historically was mainly caused by dust particles, however since the 1990s, yield degradation is mainly caused by process variation, the process itself and by the tools used in chip manufacturing, although dust still remains a problem in many older fabs. Dust particles have an increasing effect on yield as feature sizes are shrunk with newer processes. Automation and the use of mini environments inside of production equipment, FOUPs and SMIFs have enabled a reduction in defects caused by dust particles. Device yield must be kept high to reduce the selling price of the working chips since working chips have to pay for those chips that failed, and to reduce the cost of wafer processing. Yield can also be affected by the design and operation of the fab.

    Tight control over contaminants and the production process are necessary to increase yield. Contaminants may be chemical contaminants or be dust particles. "Killer defects" are those caused by dust particles that cause complete failure of the device (such as a transistor). There are also harmless defects. A particle needs to be 1/5 the size of a feature to cause a killer defect. So if a feature is 100 nm across, a particle only needs to be 20 nm across to cause a killer defect. Electrostatic electricity can also affect yield adversely. Chemical contaminants or impurities include heavy metals such as Iron, Copper, Nickel, Zinc, Chromium, Gold, Mercury and Silver, alkali metals such as Sodium, Potassium and Lithium, and elements such as Aluminum, Magnesium, Calcium, Chlorine, Sulfur, Carbon, and Fluorine. It is important for those elements to not remain in contact with the silicon, as they could reduce yield. Chemical mixtures may be used to remove those elements from the silicon; different mixtures are effective against different elements.

    Several models are used to estimate yield. Those are Murphy's model, Poisson's model, the binomial model, Moore's model and Seeds' model. There is no universal model; a model has to be chosen based on actual yield distribution (the location of defective chips) For example, Murphy's model assumes that yield loss occurs more at the edges of the wafer (non-working chips are concentrated on the edges of the wafer), Poisson's model assumes that defective dies are spread relatively evenly across the wafer, and Seeds's model assumes that defective dies are clustered together.[25]

    Smaller dies cost less to produce (since more fit on a wafer, and wafers are processed and priced as a whole), and can help achieve higher yields since smaller dies have a lower chance of having a defect. However, smaller dies require smaller features to achieve the same functions of larger dies or surpass them, and smaller features require reduced process variation and increased purity (reduced contamination) to maintain high yields. Metrology tools are used to inspect the wafers during the production process and predict yield, so wafers predicted to have too many defects may be scrapped to save on processing costs.[26]