import cadquery as cq import numpy as np import matplotlib.pyplot as plt import pyvista as pv from reportlab.lib.pagesizes import letter from reportlab.pdfgen import canvas import gradio as gr import os # Function for Progressive Die Design def generate_die(length, width, thickness): try: output_dir = "outputs" os.makedirs(output_dir, exist_ok=True) # Ensure output directory exists # Create die geometry plate = cq.Workplane("XY").box(length, width, thickness) punch = cq.Workplane("XY").rect(10, 10).extrude(5).translate((length / 4, width / 4, thickness / 2)) die = plate.cut(punch) # Export STEP file filename = os.path.join(output_dir, "progressive_die.step") cq.exporters.export(die, filename) return filename except Exception as e: return f"Error generating die: {str(e)}" def visualize_die(length, width, thickness): try: output_dir = "outputs" os.makedirs(output_dir, exist_ok=True) # Ensure output directory exists # Create die geometry plate = cq.Workplane("XY").box(length, width, thickness) punch = cq.Workplane("XY").rect(10, 10).extrude(5).translate((length / 4, width / 4, thickness / 2)) die = plate.cut(punch) # Export STL file for visualization stl_file = os.path.join(output_dir, "progressive_die.stl") cq.exporters.exportShape(die.val(), "STL", stl_file) # Generate 3D visualization screenshot pv.global_theme.off_screen = True # Ensure off-screen rendering mesh = pv.read(stl_file) plotter = pv.Plotter(off_screen=True) plotter.add_mesh(mesh, color="blue") screenshot = os.path.join(output_dir, "progressive_die_visualization.png") plotter.screenshot(screenshot) # Ensure the screenshot file exists if not os.path.exists(screenshot): raise FileNotFoundError("Screenshot file was not generated.") return screenshot except Exception as e: return f"Error visualizing die: {str(e)}" # Function for Stress Analysis (including thermal stress and fatigue strength) def stress_analysis(force, die_width, die_height, material_strength, temperature_change=50, alpha=1e-5, elastic_modulus=200000, fatigue_strength=150): try: # Mechanical stress stress = force / (die_width * die_height) # Stress = Force / Area safety_factor = material_strength / stress # Safety Factor = Material Strength / Stress # Thermal stress thermal_stress = elastic_modulus * alpha * temperature_change # Fatigue strength fatigue_stress = fatigue_strength # Generate data for plotting x = np.linspace(1, 100, 100) # Operational range (e.g., % load) stress_curve = stress * x / 100 # Simulated stress material_strength_curve = np.full_like(x, material_strength) # Constant material strength safety_factor_curve = material_strength_curve / stress_curve # Varying safety factor thermal_stress_curve = np.full_like(x, thermal_stress) # Constant thermal stress fatigue_strength_curve = np.full_like(x, fatigue_stress) # Constant fatigue strength # Create combined graph fig, ax = plt.subplots(figsize=(10, 6)) ax.plot(x, stress_curve, label="Stress (σ)", color="blue") ax.plot(x, material_strength_curve, label="Material Strength (σ_y)", color="green") ax.plot(x, safety_factor_curve, label="Safety Factor (SF)", color="orange") ax.plot(x, thermal_stress_curve, label="Thermal Stress (σ_thermal)", color="purple") ax.plot(x, fatigue_strength_curve, label="Fatigue Strength (σ_fatigue)", color="brown") ax.axhline(1, color="red", linestyle="--", label="Critical Safety Threshold (SF=1)") ax.set_title("Combined Stress Analysis Parameters") ax.set_xlabel("Operational Range (%)") ax.set_ylabel("Parameter Value (MPa or Unitless)") ax.legend() ax.grid() plt.tight_layout() plt.close(fig) return f"Safety Factor: {round(safety_factor, 2)}", fig except Exception as e: return f"Error in stress analysis: {str(e)}", None # Tool Optimization Function def optimize_tool(speed, feed_rate, depth_of_cut, material): """ Optimizes machining parameters for maximum tool life. """ try: # Simple formula for tool life estimation tool_life = 1000 / (speed * feed_rate * depth_of_cut) # Recommend adjustments for better tool life recommended_speed = 0.8 * speed recommended_feed_rate = 0.9 * feed_rate return { "Estimated Tool Life (hrs)": round(tool_life, 2), "Recommended Speed (m/min)": round(recommended_speed, 2), "Recommended Feed Rate (mm/rev)": round(recommended_feed_rate, 2), } except Exception as e: return {"Error": str(e)} # Create Gradio App with gr.Blocks() as app: gr.Markdown("## Press Tool AI Suite") gr.Markdown("Select a tool below to get started:") with gr.Tabs(): with gr.Tab("Progressive Die Design"): gr.Markdown("### Enter Dimensions for Progressive Die") length = gr.Number(label="Length (mm)", value=100) width = gr.Number(label="Width (mm)", value=50) thickness = gr.Number(label="Thickness (mm)", value=10) die_output = gr.Textbox(label="STEP File Location") visualization_output = gr.Image(label="3D Visualization") die_button = gr.Button("Generate Die") die_button.click( lambda l, w, t: (generate_die(l, w, t), visualize_die(l, w, t)), inputs=[length, width, thickness], outputs=[die_output, visualization_output], ) with gr.Tab("Stress Analysis"): gr.Markdown("### Select Simulation Tool and Enter Parameters for Stress Analysis") force = gr.Number(label="Force (N)", value=10000) die_width = gr.Number(label="Width (m)", value=0.05) die_height = gr.Number(label="Height (m)", value=0.01) material_strength = gr.Number(label="Material Strength (MPa)", value=250) temperature_change = gr.Number(label="Temperature Change (°C)", value=50) alpha = gr.Number(label="Thermal Expansion Coefficient (1/°C)", value=1e-5) elastic_modulus = gr.Number(label="Elastic Modulus (MPa)", value=200000) fatigue_strength = gr.Number(label="Fatigue Strength (MPa)", value=150) safety_factor_output = gr.Textbox(label="Safety Factor") stress_chart = gr.Plot() stress_button = gr.Button("Analyze Stress") stress_button.click( lambda f, dw, dh, ms, tc, a, em, fs: stress_analysis(f, dw, dh, ms, tc, a, em, fs), inputs=[force, die_width, die_height, material_strength, temperature_change, alpha, elastic_modulus, fatigue_strength], outputs=[safety_factor_output, stress_chart], ) with gr.Tab("Tool Optimization"): gr.Markdown("### Enter Machining Parameters for Tool Optimization") speed = gr.Number(label="Cutting Speed (m/min)", value=100) feed_rate = gr.Number(label="Feed Rate (mm/rev)", value=0.2) depth_of_cut = gr.Number(label="Depth of Cut (mm)", value=1.0) material = gr.Dropdown(choices=["Steel", "Aluminum", "Titanium"], label="Material", value="Steel") optimization_results = gr.JSON(label="Optimization Results") optimize_button = gr.Button("Optimize Tool") optimize_button.click( lambda s, fr, dc, m: optimize_tool(s, fr, dc, m), inputs=[speed, feed_rate, depth_of_cut, material], outputs=optimization_results, ) # Launch the app app.launch()