feat: production data flow

.gitignore

@@ -1,3 +1,4 @@
 .DS_Store
+.idea/
 .venv
 __pycache__/

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 
 from src.chat import respond
+from src.production.flow import play_fn, pause_fn, reset_fn
 
 custom_theme = gr.themes.Base(
     primary_hue="blue",
@@ -28,21 +29,34 @@ with gr.Blocks(theme=custom_theme) as demo:
                 with gr.Row():
                     with gr.Column(scale=2):
                         with gr.Group():
-                            button1 = gr.Button("Start Production")
-                            button2 = gr.Button("Restart Production")
-                            button3 = gr.Button("Stop Production")
-
-                            output1 = gr.Textbox(label="Sortie", visible=False)
-                            output2 = gr.Textbox(label="Sortie", visible=False)
-                            output3 = gr.Textbox(label="Sortie", visible=False)
-
-                            button1.click(fn=None, outputs=output1)
-                            button2.click(fn=None, outputs=output2)
-                            button3.click(fn=None, outputs=output3)
+                            play = gr.Button("▶️ Play")
+                            pause = gr.Button("⏸️ Pause")
+                            reset = gr.Button("🔄 Reset")
 
             with gr.Column(scale=2):
-                with gr.Group():
-                    gr.Markdown('### Display Graphs here')
+                display_df = gr.DataFrame(
+                    label="Production Data",
+                    headers=[
+                        "Part ID", "Timestamp", "Position", "Orientation", "Tool ID",
+                        "Compliance", "Event", "Error Code", "Error Description",
+                        "Downtime Start", "Downtime End"
+                    ]
+                )
+                play.click(
+                        fn=play_fn,
+                        inputs=None,
+                        outputs=display_df,
+                    )
+                pause.click(
+                    fn=pause_fn,
+                    inputs=None,
+                    outputs=None
+                )
+                reset.click(
+                    fn=reset_fn,
+                    inputs=None,
+                    outputs=None
+                )
 
     with gr.Tab("Description"):
         gr.Markdown(

requirements.txt

@@ -1,2 +1,4 @@
 huggingface_hub==0.25.2
-gradio
+gradio
+numpy
+pandas

src/production/downtime.py

@@ -0,0 +1,64 @@
+from datetime import timedelta
+
+machine_errors = {
+    "E001": {
+        "description": "Calibration Error",
+        "cause": "The machine is not correctly calibrated.",
+        "solution": "Recalibrate the machine according to the manufacturer's specifications.",
+        "downtime": timedelta(hours=2)
+    },
+    "E002": {
+        "description": "Motor Overheating",
+        "cause": "The motor has exceeded the maximum operating temperature.",
+        "solution": "Stop the machine and let it cool down. Check the cooling system.",
+        "downtime": timedelta(hours=3)
+    },
+    "E003": {
+        "description": "Material Jam",
+        "cause": "Accumulation of material in the processing area.",
+        "solution": "Clean the processing area and check the feeding mechanisms.",
+        "downtime": timedelta(minutes=15)
+    },
+    "E004": {
+        "description": "Sensor Error",
+        "cause": "A sensor is not functioning correctly.",
+        "solution": "Check the sensor connections and replace if necessary.",
+        "downtime": timedelta(hours=1, minutes=30)
+    },
+    "E005": {
+        "description": "Power Failure",
+        "cause": "Electrical supply interrupted.",
+        "solution": "Check the electrical supply and fuses. Restart the machine.",
+        "downtime": timedelta(minutes=30)
+    },
+    "E006": {
+        "description": "Software Error",
+        "cause": "Bug in the machine control software.",
+        "solution": "Restart the software or update the firmware.",
+        "downtime": timedelta(hours=1)
+    },
+    "E007": {
+        "description": "Wear and Tear of Parts",
+        "cause": "The machine parts are worn out.",
+        "solution": "Inspect the parts and replace if necessary.",
+        "downtime": timedelta(hours=1)
+    },
+    "E008": {
+        "description": "Communication Error",
+        "cause": "Communication problem between different machine modules.",
+        "solution": "Check communication cables and protocols.",
+        "downtime": timedelta(hours=2)
+    },
+    "E009": {
+        "description": "Low Lubricant Level",
+        "cause": "The lubricant level is insufficient.",
+        "solution": "Refill the lubricant reservoir according to specifications.",
+        "downtime": timedelta(minutes=15)
+    },
+    "E010": {
+        "description": "Positioning Error",
+        "cause": "The tooling is not positioning correctly.",
+        "solution": "Check the positioning mechanisms and recalibrate if necessary.",
+        "downtime": timedelta(hours=1)
+    }
+}

src/production/flow.py

@@ -0,0 +1,138 @@
+import time
+import random
+import numpy as np
+import pandas as pd
+from datetime import datetime, timedelta
+
+from .downtime import machine_errors
+
+PRODUCTION = False
+PROD_STATE = {
+    "current_time": None,
+    "part_id": None,
+    "data": None
+}
+
+def synthetic_data():
+    """
+    Generate synthetic production data for a manufacturing process.
+    """
+    global PROD_STATE
+    data = PROD_STATE["data"] if PROD_STATE["data"] else []
+    current_time = PROD_STATE["current_time"] if PROD_STATE["current_time"] else datetime.now()
+    part_id = PROD_STATE["part_id"] if PROD_STATE["part_id"] else 1
+    non_compliance_rates = {
+        1: 0.05,
+        2: 0.10,
+        3: 0.03,
+        4: 0.07
+    }
+
+    for _ in range(1000):
+        if not PRODUCTION:
+            break
+
+        if random.random() < 0.001:
+            error_key = random.choice(list(machine_errors.keys()))
+            error = machine_errors[error_key]
+            downtime = error["downtime"]
+
+            data.append({
+                "timestamp": current_time.strftime("%Y-%m-%d %H:%M:%S"),
+                "event": "Machine Error",
+                "error_code": error_key,
+                "error_description": error["description"],
+                "downtime_start": current_time.strftime("%Y-%m-%d %H:%M:%S"),
+                "downtime_end": (current_time + downtime).strftime("%Y-%m-%d %H:%M:%S")
+            })
+
+            current_time += downtime
+        else:
+            position = np.random.normal(loc=0.4, scale=0.03)
+            orientation = np.random.normal(loc=0.4, scale=0.06)
+            tool_id = (part_id % 4) + 1
+
+            if random.random() < non_compliance_rates[tool_id]:
+                position = np.random.normal(loc=0.4, scale=0.2)
+                orientation = np.random.normal(loc=0.4, scale=0.3)
+
+            compliance = 'OK' if (0.3 <= position <= 0.5) and (0.2 <= orientation <= 0.6) else 'NOK'
+
+            data.append({
+                "part_id": part_id,
+                "timestamp": current_time.strftime("%Y-%m-%d %H:%M:%S"),
+                "position": round(position, 4),
+                "orientation": round(orientation, 4),
+                "tool_id": tool_id,
+                "compliance": compliance
+            })
+
+            print(f"     - part {part_id} data generated")
+            part_id += 1
+            time.sleep(1)
+
+        current_time += timedelta(seconds=1)
+
+    PROD_STATE["data"] = data
+    PROD_STATE["current_time"] = current_time
+    PROD_STATE["part_id"] = part_id
+
+    return data
+
+def update_display(data):
+    """
+    Update production data in real-time.
+    """
+    display_data = []
+    for row in data:
+        display_data.append({
+            "Part ID": row.get("part_id", "N/A"),
+            "Timestamp": row.get("timestamp", "N/A"),
+            "Position": row.get("position", "N/A"),
+            "Orientation": row.get("orientation", "N/A"),
+            "Tool ID": row.get("tool_id", "N/A"),
+            "Compliance": row.get("compliance", "N/A"),
+            "Event": row.get("event", "N/A"),
+            "Error Code": row.get("error_code", "N/A"),
+            "Error Description": row.get("error_description", "N/A"),
+            "Downtime Start": row.get("downtime_start", "N/A"),
+            "Downtime End": row.get("downtime_end", "N/A")
+        })
+    return pd.DataFrame(display_data)
+
+
+def play_fn():
+    """
+    Start the production simulation and generate synthetic data.
+    """
+    print("=== Continuation production ===")
+    global PRODUCTION
+    PRODUCTION = True
+    while PRODUCTION:
+        data = synthetic_data()
+        display_data = update_display(data)
+        yield display_data
+        time.sleep(1)
+
+
+def pause_fn():
+    """
+    Pause the production simulation.
+    """
+    print("=== Stopping production ===")
+    global PRODUCTION
+    PRODUCTION = False
+
+
+def reset_fn():
+    """
+    Reset the production state and clear the data.
+    """
+    print("=== RESET DONE ===")
+    global PRODUCTION, PROD_STATE
+    PRODUCTION = False
+    PROD_STATE = {
+        "current_time": None,
+        "part_id": None,
+        "data": None
+    }