Precision Feed Control Using Constant Cutting Force Strategies

To address the issue of fluctuating cutting loads and constantly changing cutting states when milling gas turbine prop parts at a constant feed rate—which negatively impacts workpiece quality and tool life—a study on cutting parameter optimization based on constant cutting force control was conducted. The cutting force was simulated and analyzed using AdvantEdge metal cutting finite element simulation software. By optimizing the cutting parameters, we were able to control the peak value of the cutting force. The feasibility and accuracy of the simulation optimization were confirmed through actual cutting experiments.

 

PART.01 Introduction

Milling typically uses a processing method characterized by a constant cutting depth and feed rate. However, the inherent complexity and diversity of milling operations often lead to variations in the cutting state, causing fluctuations in the cutting load. This inconsistency can negatively affect the quality of the workpiece and the lifespan of the tool. Traditionally, feed rates have been selected based on experience and cutting manuals, which frequently results in tools operating under a light load for most of the cutting process. This approach fails to maximize the performance of the machine tool and significantly reduces the processing speed.

If the cutting feed rate is simply increased, it can lead to problems such as vibration in high-load areas. Feed speed control can be categorized into online and offline methods. The online method involves real-time collection of sensor signals during machining and making adjustments to the machining conditions based on the feedback received. This approach is rarely used due to its high cost and low reliability. The more common method is offline feed speed adjustment, which optimizes the machine tool’s feed speed based on a cutting model. This method modifies the machining file to achieve effective control, ensuring an ideal cutting load. It allows the machine tool’s feed system to operate efficiently—fast when needed and slow when appropriate—thereby enhancing machining productivity.

Third Wave AdvantEdge is a metal cutting simulation software that employs the finite element method to accurately simulate physical parameters such as cutting force, temperature, and stress during the cutting process. By using AdvantEdge, users can obtain cutting performance data under various cutting parameters, providing valuable insights for optimizing these parameters. The Production Module can analyze cutting force, material removal rate, and peak temperature using a comprehensive assessment of machine tools, workpieces, tools, material data, and NC programs. It optimizes cutting force and temperature by adjusting the feed speed and cutting speed in the NC program.

This paper aims to address the issue of fluctuating cutting loads and significant variance in cutting conditions that can occur with a constant feed speed during milling. Using the rough milling process of gas turbine strut parts as a case study, we employ the AdvantEdge Production Module for simulation analysis and perform actual cutting verifications. By optimizing the feed speed, we establish a technical approach that maintains a relatively constant cutting force, ultimately improving processing efficiency and extending tool life.

 

PART 02 Cutting test plan

2.1 Part structure

The gas turbine strut part and its blank model are shown in Figure 1. The workpiece material is 1Cr18Ni9Ti stainless steel forging, and the part being processed in this operation is the middle surface.

 

2.2 Processing technology plan

The structural forms of parts and blanks were analyzed, focusing on the surface processing of the middle section. A process plan was developed that involves first conducting rough milling, followed by fine milling on a three-axis vertical CNC milling machine. During the rough milling stage, the bulk of the material was removed quickly while maintaining a relatively uniform allowance for fine milling. In the fine milling phase, the allowance was evenly removed to ensure better surface quality.

The rough milling process consists of two steps. First, a larger diameter milling cutter (φ63mm) is used to rapidly eliminate the majority of the blank material. Next, a smaller diameter milling cutter (φ25mm) is employed to remove residual material from the corners on both sides, resulting in a more uniform allowance for the fine milling process. To achieve a higher material removal rate and improve processing efficiency during rough milling, a method with a constant cutting depth of 1mm per layer was utilized. The CNC processing program was created using CAM software. The tool trajectories for the two steps in the rough milling stage are illustrated in Figure 2.

2.3 Tool parameters

The experiment utilized two tools: a φ63mm R6mm round blade milling cutter (Tool T1) and a φ25mm R5mm round blade milling cutter (Tool T2). Detailed parameters for these tools are provided in Table 1. Both tools are made from coated carbide, which is well-suited for machining the 1Cr18Ni9Ti stainless steel material used for the pillar.

 

PART 03 Cutting force simulation analysis

3.1 Cutting parameters before optimization

In traditional methods for selecting feed speed, the feed speeds for the two steps are determined using a combination of experience and trial cutting. Based on the cutting tool trajectory generated by CAM software, it is important to maintain smooth cutting throughout the entire processing operation. Therefore, the cutting parameters for both steps are established through actual trial cutting, as shown in Table 2.

 

3.2 AdvantEdge cutting force simulation

In the AdvantEdge Production Module, a simulation environment is established where machine tool and tool parameters are configured. A part blank model is imported, the workpiece material is selected, and the CNC program’s tool path trajectory is read. The software is then executed to simulate virtual milling at a constant feed rate of 400 mm/min, which allows us to obtain a graph of cutting force changes over time.

Our primary focus is on the change in tangential force, as this has the most significant impact on the lathe process. The results of the cutting force simulation before optimization are illustrated in Figure 3. The total program processing time was 8251.3 seconds. The T1 tool was used for processing during the first 5586.6 seconds, followed by the T2 tool. Throughout the entire program execution, the tangential force exhibited considerable fluctuations.

The peak tangential force for the T1 tool reached 1141 N, while the average tangential force was 322 N. For the T2 tool, the peak tangential force was 520 N, with an average of 170 N. These simulation results accurately represent the actual cutting conditions: the tangential force is zero when the tool is idle, it gradually increases during cutting, remains relatively stable during steady cutting, and rises again at the corners.

 

3.3 Feed rate optimization based on constant cutting force

Cutting force is a key parameter to consider during the cutting process. Its magnitude not only impacts the quality of the processing but also influences tool wear and overall processing efficiency. Methods for controlling cutting force include altering the tool shape, material, and cutting parameters. By adjusting cutting parameters, such as the feed rate, it is possible to reduce cutting force, thereby enhancing processing efficiency and extending tool life.

The optimization of feed rate primarily falls into two categories: constant material removal rate control and constant cutting force control optimization. This study adopts the method of feed rate control with a focus on maintaining constant cutting force, optimizing the feed rate based on the peak cutting force as the limiting constraint.

From the tangential force-time curve shown before optimization in Figure 3, we observe relatively uniform tangential forces for the two tools: Tool 1 (T1) measures 322N, while Tool 2 (T2) measures 170N. These values serve as the peak cutting force constraint targets for the two tools. After setting the optimization target to limit the peak cutting force and define the maximum feed speed, the AdvantEdge ProductionModule will automatically optimize and adjust the CNC program. This is accomplished without changing the tool trajectory; instead, the feed speed for each tool path is optimized to maintain a constant cutting force at the peak value while ensuring the maximum feed speed does not exceed the specified target.

In cases where cutting force varies within a single CNC program instruction, multiple points will be interpolated to segment the program. Different feed speeds will then be assigned to each segment, all while keeping the tool trajectory unchanged. The comparison of the CNC programs before and after optimization is provided in Table 3.

 

After optimizing the CNC program, we conducted a cutting force simulation on the revised program. The results of this simulation are displayed in Figure 4. It shows that the processing time of the optimized CNC program has been reduced to 5299.3 seconds. Specifically, the T1 tool was used for processing for 3785.2 seconds before switching to the T2 tool afterwards. Several cutting force peaks have been eliminated, leading to a significant reduction in cutting force fluctuations.

Figure 5 presents a comparison of the cutting force simulation results before and after optimization. The tangential force-time curve prior to optimization exhibited considerable fluctuations in cutting force, whereas the curve after optimization shows a much more stable cutting force. This demonstrates a clear reduction in cutting time and an efficiency improvement of 35.78%. Additionally, the cutting force peaks are now more controllable, resulting in a more stable cutting force. This stability is likely to positively impact tool life and enhance the surface quality of the processed parts.

PART 04 Verification of simulation optimization results

The optimized CNC program, validated through cutting simulation, was used to conduct trial cuts on a real object. This verification aimed to ensure that the optimized processing time matched the simulation results, that the cutting efficiency was improved, and that the cutting conditions remained stable throughout the CNC manufacturing process.

Figure 6 illustrates the application of the optimized CNC program for processing pillar parts. In Figure 6a, a large-diameter φ63mm milling cutter is utilized to quickly remove excess material, while Figure 6b displays the use of a small-diameter φ25mm milling cutter to eliminate processing residues from the corners on both sides.

After conducting actual processing trials, it was confirmed that the cutting time aligned with the CNC program’s simulated time, resulting in a 35.78% improvement in processing efficiency. Additionally, the entire cutting process remained stable, without significant tool vibrations caused by excessive cutting loads. Notable speed reductions occurred during initial cuts and at corners where cutting loads were high, while acceleration was observed when the cutting width was smaller at the edges. This achieved the desired effect of cutting quickly when needed and slowing down when required, successfully reaching the optimization goals.

 

 

PART 5 Conclusion

This paper addresses the issue of fluctuating cutting forces during the milling of gas turbine prop parts, which often necessitates a reduction in overall feed speed and leads to low processing efficiency. The objective is to achieve a constant cutting force by optimizing the feed speed among the cutting parameters. The feasibility and effectiveness of this optimization are validated through simulations using metal cutting finite element software, as well as actual cutting tests. Results indicate that by optimizing the feed speed, it is possible to maintain a consistent cutting force. This approach brings several benefits, including improved processing quality and efficiency, decreased tool wear, and reduced vibrations. These findings hold significant practical implications and engineering application value.

 

 

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