## 3 Machining Quality Prediction Method Based on XGBoost Hyperparameter Optimization
### Identification of Key Processing Characteristics of Marine Diesel Engine Piston  
A piston can be divided into three parts: the top, the head, and the skirt. Figure 3 shows the piston's structure. Due to the large size of marine medium-speed diesel engine pistons, they are typically processed in two parts. The piston skirt, being a thin-walled part with poor rigidity and a complex structure, requires a more intricate machining process. For crucial quality characteristics, it is essential to control the size, shape, and surface roughness within tight tolerance ranges to ensure the piston's machining quality and performance. The arrangement of piston process procedures should follow basic principles: rough machining first, then finishing, and processing the benchmark first, then other features. The machining process of a piston can be broadly divided into three stages: rough machining, semi-finishing, and finishing. The main processes of rough machining include rough turning of the outer circle and end face, rough boring, and milling of both sides of the plane. Semi-finishing processes involve semi-finish turning of the cylindrical end face and ring groove and semi-finish boring. Finishing processes include finishing the end face and stop and fine model line and fine boring. After these primary processes, auxiliary processes such as trimming and deburring, coloring, and flaw detection in the skirt are necessary. Figure 2: Flowchart of key quality characteristic identification and quality prediction method for marine diesel engine piston machining based on information entropy and XGBoost hyperparameter optimization. The inner surface of the skirt must be free of defects like cracks and cold scars. Additionally, the skirt undergoes graphitization treatment, and the surface receives anti-rust treatment. The comprehensive process card for a specific type of marine medium-speed diesel engine piston is shown in Table 2.  
The proposed method was applied to analyze a sample of machining data from 29 marine medium-speed diesel engine pistons processed by a particular company in the same batch. Table 3 shows a portion of the organized data, with the header including process, workstation, dimension type, design dimension, upper deviation, lower deviation, \begin{table}
\begin{tabular}{c c c} \hline \hline
**Process Number** & **Description of Operation** & **Processing Units** \\ \hline
1 & Forging blank & - \\
2 & Rough turning of the outer diameter and end & \\  & face and drilling & \\  & Ultrasonic inspection is carried out according to & \\  & GB/T 6519-2000 Grade A. If oxide films, & \\
3 & non-metallic inclusions, pores, and cracks in the & - \\  & macrostructure are non-compliant, an inspection & \\  & can be performed according to GB/T 6519-2000 & \\  & Grade AA & \\
4 & Scribing & \\
5 & Rough boring & \\
6 & Finish turning of the end face and shoulder & \\
7 & Semi-finish turning of the outer diameter and & \\  & end face, grooving, counterboring, and reaming & \\
8 & Drilling and reaming & \\
9 & Semi-finish boring of holes, milling oil grooves, & \\  & and arcs & \\
10 & Milling of two side planes & \\
11 & Vibration stress relief & - \\
12 & Finishing the shoulder & \\
13 & Precision turning of the contour line & \\
14 & Finish boring of holes & \\  & & \\
15 & Milling of two side planes and rounded corners & \\  & & \\
16 & Finishing and deburring & \\
17 & Dye penetrant inspection of the skirt interior & - \\
18 & Final inspection & Inspection platform \\
19 & Cleaning and packaging & Cleaning machine \\
20 & Skirt graphite treatment & - \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Piston comprehensive process card. Figure 3: Piston structure. and each part number. Among these, the data for upper deviation and lower deviation significantly impact subsequent calculations. To analyze the machining quality, divide the length of each machining quality distribution interval corresponding to each quality characteristic in Table 3 into multiple equally spaced sub-intervals.