| 摘要註: |
模具鋼內因為由許多合金元素所強化組成,因此在各性質上皆有特殊的表現,像是良好的硬度、紅熱硬度、耐磨耗性、適當的韌性等,所以用途相當的廣泛,其中碳化物的析出對模具鋼的性質影響甚巨,因此如何有效的控制碳化物的種類和分佈就可以掌握材料的性質展現。本實驗將以商用H13鋼材為基礎從各個面向探討顯微組織、熱處理以及合金元素對於材料機械性質(硬度)與熱性質(熱傳導率)的影響,並針對各個熱處理階段的碳化物以萃取法進行分析鑑定,並歸納出碳化物之析出機制,於元素影響上則統計實驗所得之數據以多項是迴歸之手法量化元素對於H13熱性質與機械性質之影響程度。得到結果顯示AISI H13之碳化物析出機制於各熱處理階段:退火態碳化物主要種類為MC、M23C6、M7C3、M6C,淬火後試片碳化物主要種類為MC及M7C3,經回火後之試片碳化物主要種類為MC、M23C6、M6C。在元素之影響上,實驗結果顯示錳(Mn)的添加會些微降低熱傳導率,對硬度並無顯著的影響,碳(C)含量的提升僅對硬度提升有影響;而降低鉻(Cr)與矽(Si)含量對於熱傳導率有顯著的助益,最大值可達27.73W⋅m-1K-1。多元線性迴歸結果顯示矽、錳、鉻、鉬元素含量與熱傳導率(λ)呈現負相關之關係,而碳、釩元素含量對熱傳導率(λ)較無顯著影響。 Due to the effect of strengthening by alloy elements, die steel has a lot of outstanding performance on many characteristics, like good hardness, red hot hardness, wear resistance and appropriate toughness, etc... So quite a wide range of purposes could it be used. Especially, the precipitation of carbides on the nature of the die steel impact is very huge, so to effectively control the type and distribution of carbide can grasp the property of steel. The research of this articale is going to observe the influence of the micro structure, heat treatment and alloy elements adding on mechanical properties (Hardness) and thermal properties (Thermal conductivity), based on AISI H13 die steel. And analysis to identify and summarize the carbide precipitation mechanism at each heat treatment stage by extraction method. On the effect of elements, we statistical experimental data obtained from the Multiple Linear Regression to quantify the elements for H13 and mechanical properties of the thermal properties influence level. The results obtained shows the mechanism of AISI H13 carbide precipitation at each stage of heat treatment, the main kinds of carbides in annealed H13 get MC, M23C6, M7C3, M6C, in as quenched H13 get MC, M7C3, in tempered H13 get MC, M23C6, M6C. On the situ of adding alloy elements, the result shows, adding Mn can slightly lower the thermal conductivity, but done no significant effect on the hardness, adding C only do a lot of effect on hardness, but no influence on thermal conductivity, lowing Cr and Si can significantly increaseing the thermal conductivity till 27.73W⋅m-1K-1. The Multiple Linear Regression result obtained Si, Mn, Cr, Mo content and thermal conductivity (λ) negative correlation of the relationship, C, V showed less connective between content and thermal conductivity (λ). |