In this study, we explore the production process and machining performance of as-cast QT550-7 ductile iron, focusing on the influence of copper and manganese additions. Ductile iron casting is widely used in automotive and industrial applications due to its excellent mechanical properties, and understanding the role of alloying elements is crucial for optimizing performance. Our investigation employs a cupola-electric furnace duplex smelting method to produce ductile cast iron with targeted compositions, and we analyze how variations in Cu and Mn affect microstructure, hardness, tensile strength, and elongation. The goal is to establish a stable production process for QT550-7 ductile iron that meets industry standards while minimizing costs and enhancing machinability.
Ductile iron, also known as ductile cast iron, is characterized by its spherical graphite nodules embedded in a metallic matrix, which impart high strength and ductility. The QT550-7 grade specifically requires a tensile strength of at least 550 MPa and an elongation of 7% or more, making it suitable for components like automotive chassis and hubs. In our research, we emphasize the importance of chemical composition control, particularly the Cu and Mn ratios, to achieve the desired as-cast properties without additional heat treatment. This approach not only reduces production time but also lowers energy consumption, aligning with sustainable manufacturing practices for ductile iron casting.
The experimental procedure involved melting raw materials in a cupola furnace to desulfurize and form iron ingots, followed by remelting in a 50 kg medium-frequency induction furnace. The molten ductile iron was treated at 1600°C using a pit-inoculation method for spheroidization and inoculation. Key reagents included an MgRE alloy with 5% Mg and 2% rare earths as the spheroidizing agent, added at 1.5% of the iron weight, and 75% ferrosilicon as the inoculant, added at 1.0%. We prepared spectroscopic samples, step blocks, and Y-blocks to evaluate hardness distribution, tensile properties, and microstructure. The base iron composition was controlled to approximately 3.70% C, 1.00% Si, 0.20% Mn, ≤0.02% S, and ≤0.05% P, with Cu and Mn variations introduced to study their effects on ductile cast iron performance.
Chemical analysis of the specimens revealed compositions within the target ranges, as summarized in Table 1. We adjusted Cu and Mn levels to create three distinct sample groups, ensuring that carbon equivalents (CE) were calculated using the formula: $$ CE = C + \frac{Si}{3} $$ where C and Si are in weight percent. This parameter is critical for predicting the castability and graphitization potential in ductile iron. The measured compositions consistently showed carbon contents of 3.68–3.74%, silicon of 2.48–2.60%, manganese of 0.39–0.73%, and copper of 0.17–0.53%, with residual magnesium and rare earths maintained below 0.04% to avoid excessive carbide formation.
| Sample ID | C | Si | Mn | P | S | Mgres | REres | Cu | CE |
|---|---|---|---|---|---|---|---|---|---|
| B1 | 3.68 | 2.60 | 0.53 | ≤0.03 | ≤0.02 | 0.027 | 0.025 | 0.25 | 4.55 |
| C2 | 3.70 | 2.50 | 0.39 | ≤0.03 | ≤0.02 | 0.035 | 0.025 | 0.53 | 4.53 |
| D2 | 3.74 | 2.48 | 0.73 | ≤0.03 | ≤0.02 | 0.026 | 0.028 | 0.17 | 4.57 |
Mechanical properties and metallographic structures were evaluated from Y-block specimens, with results presented in Table 2. All samples exhibited spheroidization grades of 3, nodule sizes of 6–7, and pearlite contents ranging from 35% to 60%. Tensile strength varied between 585 and 602 MPa, elongation from 7.50% to 12.73%, and hardness from 198 to 235 HB. Sample C2, with high Cu and low Mn, showed the highest elongation (12.73%) and finer graphite nodules, indicating improved ductility. In contrast, sample D2, with low Cu and high Mn, had the highest hardness (235 HB) and pearlite content (60%), but lower plasticity. This underscores the significant impact of Cu and Mn ratios on the performance of ductile iron casting. The relationship between hardness and composition can be approximated by: $$ HB = k_1 \cdot Mn + k_2 \cdot Cu + C $$ where k1 and k2 are coefficients derived from regression analysis, and C is a constant. For instance, higher Mn content increases hardness more pronouncedly in thinner sections due to accelerated cooling, which we further investigated through step-block hardness tests.
| Sample ID | Tensile Strength (MPa) | Elongation (%) | Hardness (HB) | Spheroidization Grade | Nodule Size Grade | Graphite Count per mm² | Pearlite Content (%) |
|---|---|---|---|---|---|---|---|
| B1 | 587 | 8.86 | 198 | 3 | 6 | 100 | 35–45 |
| C2 | 585 | 12.73 | 204 | 3 | 6 | 130 | 55 |
| D2 | 602 | 7.50 | 235 | 3 | 6 | 100 | 60 |
To assess machinability, we conducted hardness measurements on step-blocks with sections of 15, 30, 50, and 70 mm thickness, as detailed in Table 3. The results show that sample D2 (high Mn, low Cu) had the highest hardness across all sections, with values up to 262 HB at 15 mm, compared to 219 HB for B1. The hardness difference between the thickest and thinnest sections was 27–34 HB, which is below the contract requirement of 40 HB, indicating uniform hardness distribution due to effective inoculation. This uniformity is vital for ductile iron components subjected to machining, as it prevents tool wear and ensures consistent surface finish. The effect of cooling rate on hardness can be modeled using: $$ \Delta HB = \alpha \cdot e^{-\beta \cdot t} $$ where ΔHB is the hardness change, t is the section thickness, and α and β are material constants. For ductile cast iron, faster cooling in thinner sections amplifies the hardening effect of Mn, making it essential to optimize composition for specific applications.
| Sample ID | 15 mm Avg | 30 mm Avg | 50 mm Avg | 70 mm Avg | Hardness Difference |
|---|---|---|---|---|---|
| B1 | 219 | 209 | 198 | 225 | 27 |
| C2 | 250 | 233 | 216 | 219 | 34 |
| D2 | 262 | 241 | 232 | 237 | 31 |
Microhardness analysis of sample C2, as illustrated in the linked figure below, revealed values ranging from 210 HV to 323 HV, with an average of 255.5 HV. This indicates the absence of hard spots that could impair machinability, comparable to benchmark ductile iron castings from industry. The microstructure of ductile iron casting typically consists of graphite nodules in a ferrite-pearlite matrix, and the ratio influences mechanical properties. For instance, the volume fraction of pearlite (Vp) can be estimated from chemical composition using: $$ V_p = k_3 \cdot Mn + k_4 \cdot Cu $$ where k3 and k4 are empirical factors. In our case, higher Cu promotes graphitization and refines pearlite, enhancing toughness, while Mn strengthens but may reduce ductility if excessive.
Field trials were conducted on single-tire wheel hubs (27 kg, wall thicknesses of 10 mm and 25 mm) to validate the laboratory findings. Using the optimized composition of 3.7–3.8% C, 2.4–2.6% Si, 0.5–0.6% Mn, and 0.2–0.3% Cu, we processed 425 kg of ductile iron in a pit-type spheroidizing ladle. The treatment temperature was maintained at 1510–1520°C, with spheroidizer and inoculant additions as before. Chemical analysis of production samples confirmed consistency, as shown in Table 4. The resulting ductile cast iron exhibited tensile strengths of 573–582 MPa, elongations of 8.2–12.9%, and hardness values of 195–206 HB in Y-blocks, with spheroidization grades of 3–4 and pearlite contents of 45–55%. Hardness measurements on the wheel hubs (Table 5) showed a maximum of 237 HB and a minimum of 205 HB, with differences up to 32 HB, meeting performance standards and demonstrating good machinability for ductile iron components.
| Element | C | Si | Mn | P | S | Mg | Cu | CE |
|---|---|---|---|---|---|---|---|---|
| Content | 3.77 | 2.41 | 0.51 | 0.032 | 0.013 | 0.037 | 0.23 | 4.58 |
| Sample ID | Hardness (HB) | Spheroidization Grade | Nodule Size Grade | Pearlite Content (%) |
|---|---|---|---|---|
| B1-1 | 217 | 3 | 7 | 45 |
| B1-2 | 221 | 3 | 7 | 45 |
| B1-3 | 217 | 4 | 7 | 45 |
| B1-4 | 224 | 3 | 7 | 45 |
| B1-5 | 217 | 3 | 7 | 45 |
| B1-6 | 228 | 4 | 7 | 45 |
| B2-1 | 225 | 3 | 7 | 45 |
| B2-2 | 218 | 4 | 7 | 45 |
| B2-3 | 205 | 3 | 7 | 45 |
| B2-4 | 213 | 3 | 7 | 45 |
| B2-5 | 234 | 3 | 7 | 55 |
| B2-6 | 237 | 3 | 7 | 55 |
In conclusion, our research demonstrates that as-cast QT550-7 ductile iron can be reliably produced with controlled Cu and Mn ratios to achieve desired mechanical properties and machinability. The optimal composition ranges are 3.7–3.8% C, 2.4–2.6% Si, 0.5–0.6% Mn, and 0.25–0.35% Cu, resulting in spheroidization grades of 3–4, nodule sizes of 6–7, and pearlite contents of 35–60%. High Mn and low Cu combinations yield higher hardness and strength, suitable for automotive chassis and hubs, while high Cu and low Mn provide better ductility and stability for applications like crankshafts. The hardness uniformity across sections, with differences below 40 HB, ensures excellent machining performance for ductile iron casting. This study highlights the importance of alloy design in ductile cast iron production and offers a cost-effective approach for industrial applications.
Further analysis of the ductile iron microstructure reveals that the graphite nodule count and size distribution play a critical role in determining tensile properties. We observed that samples with higher Cu content, such as C2, had finer graphite nodules (130 per mm²) compared to others, which contributed to their superior elongation. The relationship between nodule count (N) and mechanical properties can be expressed as: $$ \sigma_b = \sigma_0 + k_5 \cdot \ln(N) $$ where σb is the tensile strength, σ0 is a base strength value, and k5 is a constant. This logarithmic dependence underscores the importance of inoculation efficiency in ductile iron casting processes. Additionally, the pearlite formation kinetics in ductile cast iron can be described using the Johnson-Mehl-Avrami-Kolmogorov equation: $$ V_p = 1 – \exp(-k \cdot t^n) $$ where Vp is the pearlite volume fraction, t is time, and k and n are parameters influenced by cooling rate and composition.
The economic implications of using Cu and Mn in ductile iron production are significant. Copper, though more expensive, enhances graphitization and reduces the risk of carbide formation, leading to better machinability and lower tool wear. Manganese, being cheaper, can be used to increase strength but requires careful control to avoid brittleness. In large-scale ductile iron casting, the cost-benefit analysis often favors Mn-rich compositions for non-critical parts, whereas Cu-rich mixes are preferred for high-integrity components. Our field trials confirmed that the optimized process reduces scrap rates and improves production efficiency, making it viable for mass production of QT550-7 ductile iron parts.
In summary, the successful production of as-cast QT550-7 ductile iron relies on a balanced approach to alloying, with Cu and Mn serving as key modifiers. The insights from this study can be extended to other grades of ductile cast iron, promoting advancements in foundry technology. Future work could explore the effects of other elements like Ni or Mo on the performance of ductile iron casting, further expanding its application range. Overall, our findings contribute to the broader understanding of ductile iron metallurgy and support the development of more sustainable and cost-effective manufacturing processes.