import cadquery as cq import numpy as np import matplotlib.pyplot as plt import gradio as gr import os # Ensure there's a directory for saving files if not os.path.exists("generated_files"): os.makedirs("generated_files") # Function for Progressive Die Design def generate_die(length, width, thickness): try: # Generate the die design 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) # Save the die to a file filename = "generated_files/progressive_die.step" cq.exporters.export(die, filename) # Return success message and file path for download return f"Progressive die design saved. [Download the file](/{filename})" except Exception as e: return f"Error generating die: {str(e)}" # Function for Stress Analysis def stress_analysis(force, die_width, die_height, material_strength): try: # Validate inputs to avoid invalid calculations if force <= 0 or die_width <= 0 or die_height <= 0 or material_strength <= 0: return "All values must be positive." # Calculate stress and safety factor stress = force / (die_width * die_height) safety_factor = material_strength / stress # Create stress analysis plot fig, ax = plt.subplots() ax.bar(["Stress", "Material Strength"], [stress, material_strength]) ax.set_ylabel("Stress (MPa)") ax.set_title("Stress Analysis") plt.tight_layout() # Ensure the plot is displayed correctly plt.close(fig) # Close the plot so it doesn't render twice # Return the results and plot return f"Safety Factor: {round(safety_factor, 2)}", fig except Exception as e: return f"Error in stress analysis: {str(e)}", None # Function for Tool Optimization def optimize_tool(speed, feed_rate, depth_of_cut, material): try: # Adjust tool life estimate based on material material_factor = {"Steel": 1.0, "Aluminum": 0.8, "Titanium": 1.2} tool_life = 1000 / (speed * feed_rate * depth_of_cut * material_factor.get(material, 1.0)) recommended_speed = 0.8 * speed recommended_feed_rate = 0.9 * feed_rate # Return optimization results 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)} # Gradio interface functions def progressive_die_interface(length, width, thickness): return generate_die(length, width, thickness) def stress_analysis_interface(force, width, height, material_strength): return stress_analysis(force, width, height, material_strength) def tool_optimization_interface(speed, feed_rate, depth_of_cut, material): return optimize_tool(speed, feed_rate, depth_of_cut, material) # Create the Gradio Interface with gr.Blocks() as app: gr.Markdown("## Press Tool AI Suite") gr.Markdown("Select a tool below to get started:") with gr.Tabs(): # Tab for Progressive Die Design 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="Output") die_button = gr.Button("Generate Die") die_button.click(progressive_die_interface, inputs=[length, width, thickness], outputs=die_output) # Tab for Stress Analysis with gr.Tab("Stress Analysis"): gr.Markdown("### 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) safety_factor_output = gr.Textbox(label="Safety Factor") stress_chart = gr.Plot() stress_button = gr.Button("Analyze Stress") stress_button.click(stress_analysis_interface, inputs=[force, die_width, die_height, material_strength], outputs=[safety_factor_output, stress_chart]) # Tab for Tool Optimization 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(tool_optimization_interface, inputs=[speed, feed_rate, depth_of_cut, material], outputs=optimization_results) # Launch the app app.launch()