Boxplot
Additive Manufacturing Precision
Dimensional accuracy distribution by 3D printer technology
Output
Python
import matplotlib.pyplot as plt
import numpy as np
np.random.seed(42)
printers = ['FDM', 'SLA', 'SLS', 'DLP', 'Metal PBF']
data = [
np.random.normal(0, 0.15, 150),
np.random.normal(0, 0.05, 150),
np.random.normal(0, 0.08, 150),
np.random.normal(0, 0.04, 150),
np.random.normal(0, 0.03, 150)
]
fig, ax = plt.subplots(figsize=(10, 6), dpi=100)
ax.set_facecolor('#0a0a0f')
fig.patch.set_facecolor('#0a0a0f')
colors = ['#F54927', '#27F5B0', '#276CF5', '#F5276C', '#F5D327']
bp = ax.boxplot(data, widths=0.55, patch_artist=True, showfliers=True,
flierprops=dict(marker='D', markerfacecolor='#5314E6', markersize=3, alpha=0.5),
medianprops=dict(color='white', linewidth=2.5))
for patch, color in zip(bp['boxes'], colors):
patch.set_facecolor(color)
patch.set_alpha(0.85)
patch.set_edgecolor(color)
for i, color in enumerate(colors):
bp['whiskers'][i*2].set_color(color)
bp['whiskers'][i*2+1].set_color(color)
bp['caps'][i*2].set_color(color)
bp['caps'][i*2+1].set_color(color)
ax.axhline(0.1, color='#6CF527', linewidth=1, linestyle='--', alpha=0.6)
ax.axhline(-0.1, color='#6CF527', linewidth=1, linestyle='--', alpha=0.6, label='Tolerance')
ax.set_xticklabels(printers)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_color('#333333')
ax.spines['bottom'].set_color('#333333')
ax.yaxis.grid(True, color='#1a1a2e', linewidth=0.5, zorder=0)
ax.set_axisbelow(True)
ax.tick_params(axis='both', colors='#888888', labelsize=9, length=0, pad=8)
ax.set_ylabel('Deviation (mm)', fontsize=11, color='white', fontweight='500')
ax.set_title('3D Printer Dimensional Accuracy', fontsize=14, color='white', fontweight='bold', pad=15)
ax.legend(loc='upper right', facecolor='#0a0a0f', edgecolor='#333333', labelcolor='white')
plt.tight_layout()
plt.show()
Library
Matplotlib
Category
Statistical
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