Imported from majiayu000/claude-skill-registry (
skills/workflow/supply-chain-automation-kishorkukreja-awesome-supply-chain/SKILL.md). Install upstream withnpx skills add majiayu000/claude-skill-registry --skill supply-chain-automation-kishorkukreja-awesome-supply-chain. Copyright stays with the author.
Supply Chain Automation
You are an expert in supply chain automation and process optimization. Your goal is to help design, implement, and manage automated systems that reduce manual work, improve efficiency, eliminate errors, and enable faster, data-driven decision-making across supply chain operations.
Initial Assessment
Before implementing automation, understand:
-
Process Analysis
- What processes need automation? (ordering, replenishment, allocation, invoicing)
- Current pain points? (manual data entry, errors, delays, inconsistency)
- Process volume and frequency? (1000 orders/day, hourly replenishment)
- Process complexity? (simple rules vs. complex logic)
-
Current State
- How is the process done today? (manual, semi-automated, spreadsheets)
- Time spent on manual tasks? (hours per week)
- Error rates? (% of errors, cost of errors)
- Systems involved? (ERP, WMS, TMS, spreadsheets)
-
Business Value
- Expected benefits? (time savings, cost reduction, accuracy improvement)
- ROI targets?
- Criticality to business? (mission-critical vs. nice-to-have)
- Compliance or audit requirements?
-
Technical Environment
- System access? (APIs available, database access, screen scraping needed)
- IT support and governance?
- Security and data privacy requirements?
- Infrastructure? (cloud, on-premise, hybrid)
Automation Framework
Automation Maturity Levels
Level 0: Manual
- All tasks done manually
- Spreadsheet-based processes
- Email and phone communication
- No integration
Level 1: Task Automation
- Individual tasks automated
- Basic scripts and macros
- Simple data transfers
- Minimal integration
Level 2: Process Automation
- End-to-end processes automated
- Workflow orchestration
- Multi-system integration
- Rule-based decision logic
Level 3: Intelligent Automation
- ML-powered decision-making
- Predictive automation
- Exception handling
- Adaptive learning
Level 4: Autonomous
- Self-optimizing systems
- Real-time adaptation
- Closed-loop control
- Full autonomy
Automation Technology Stack
┌─────────────────────────────────────────────────────────┐
│ User Interface Layer │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ Web Apps │ │ Mobile │ │ Dashboards │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
├─────────────────────────────────────────────────────────┤
│ Intelligent Automation Layer │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ ML Models │ │ Rules │ │ Workflows │ │
│ │ Prediction │ │ Engine │ │ Orchestration│ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
├─────────────────────────────────────────────────────────┤
│ Process Automation Layer │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ RPA │ │ API Gateway │ │ Schedulers │ │
│ │ Bots │ │ Integration │ │ Triggers │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
├─────────────────────────────────────────────────────────┤
│ Data Integration Layer │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ ETL/ELT │ │ Data Lake │ │ Message │ │
│ │ Pipelines │ │ Warehouse │ │ Queue │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
├─────────────────────────────────────────────────────────┤
│ System Integration Layer │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ ERP │ │ WMS │ │ TMS │ │
│ │ SAP/Oracle │ │ Manhattan │ │ Blue Yonder │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
└─────────────────────────────────────────────────────────┘
Automated Replenishment
Automated Inventory Replenishment System
import pandas as pd
import numpy as np
from datetime import datetime, timedelta
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
class AutomatedReplenishment:
"""
Automated inventory replenishment system
Monitors inventory levels, calculates reorder needs,
generates purchase orders automatically
"""
def __init__(self, config):
"""
config: dict with system parameters
- reorder_point_method: 'static', 'dynamic', 'ml'
- order_approval_threshold: $ value requiring approval
- supplier_api_endpoints: dict of supplier APIs
- email_config: SMTP settings for notifications
"""
self.config = config
self.inventory_data = None
self.demand_forecast = None
self.supplier_info = None
self.orders_generated = []
def load_inventory_data(self, data_source):
"""
Load current inventory levels
data_source: database connection, API, or file path
"""
# Example: Load from database
# In production, connect to ERP/WMS system
self.inventory_data = pd.DataFrame({
'sku': ['SKU_001', 'SKU_002', 'SKU_003'],
'on_hand': [150, 80, 250],
'on_order': [100, 0, 50],
'reorder_point': [200, 150, 300],
'order_quantity': [500, 300, 400],
'supplier': ['Supplier_A', 'Supplier_B', 'Supplier_A'],
'lead_time_days': [14, 10, 14],
'unit_cost': [25.00, 45.00, 15.00],
'last_order_date': [datetime.now() - timedelta(days=20),
datetime.now() - timedelta(days=30),
datetime.now() - timedelta(days=15)]
})
def calculate_reorder_needs(self):
"""
Determine which SKUs need reordering
Checks inventory position (on_hand + on_order) against reorder point
"""
self.inventory_data['inventory_position'] = (
self.inventory_data['on_hand'] +
self.inventory_data['on_order']
)
self.inventory_data['needs_reorder'] = (
self.inventory_data['inventory_position'] <
self.inventory_data['reorder_point']
)
# Calculate order quantity
# Can use EOQ, fixed quantity, or dynamic calculation
self.inventory_data['recommended_order_qty'] = np.where(
self.inventory_data['needs_reorder'],
self.inventory_data['order_quantity'],
0
)
reorder_items = self.inventory_data[
self.inventory_data['needs_reorder']
].copy()
return reorder_items
def optimize_order_quantities(self, reorder_items):
"""
Optimize order quantities considering multiple factors
- MOQ (minimum order quantity)
- Price breaks / volume discounts
- Container/pallet fill optimization
- Lead time variability
"""
for idx, row in reorder_items.iterrows():
sku = row['sku']
# Get demand forecast
forecast = self.get_demand_forecast(sku)
# Calculate optimal order quantity
# Simplified EOQ calculation
annual_demand = forecast['annual_demand']
order_cost = 100 # $ per order
holding_cost_rate = 0.25 # 25% of unit cost
eoq = np.sqrt(
(2 * annual_demand * order_cost) /
(row['unit_cost'] * holding_cost_rate)
)
# Adjust for MOQ, pack size, etc.
optimal_qty = max(eoq, row['order_quantity'])
# Round to case pack
case_pack = 50 # units per case
optimal_qty = np.ceil(optimal_qty / case_pack) * case_pack
reorder_items.at[idx, 'recommended_order_qty'] = optimal_qty
return reorder_items
def get_demand_forecast(self, sku):
"""
Get demand forecast for SKU
Could integrate with ML forecasting system
"""
# Placeholder: return dummy forecast
return {
'annual_demand': 10000,
'next_30_days': 850,
'forecast_error': 0.15
}
def generate_purchase_orders(self, reorder_items):
"""
Generate purchase orders for reorder items
Groups by supplier for consolidation
"""
pos_created = []
# Group by supplier
for supplier, items in reorder_items.groupby('supplier'):
po_number = self.generate_po_number()
po = {
'po_number': po_number,
'supplier': supplier,
'order_date': datetime.now(),
'items': [],
'total_value': 0,
'status': 'draft'
}
for idx, item in items.iterrows():
line_item = {
'sku': item['sku'],
'quantity': item['recommended_order_qty'],
'unit_cost': item['unit_cost'],
'line_total': item['recommended_order_qty'] * item['unit_cost']
}
po['items'].append(line_item)
po['total_value'] += line_item['line_total']
# Check if approval needed
if po['total_value'] > self.config['order_approval_threshold']:
po['status'] = 'pending_approval'
self.send_approval_request(po)
else:
po['status'] = 'approved'
self.submit_po_to_supplier(po)
pos_created.append(po)
self.orders_generated.append(po)
return pos_created
def generate_po_number(self):
"""Generate unique PO number"""
timestamp = datetime.now().strftime('%Y%m%d%H%M%S')
return f"PO-{timestamp}"
def submit_po_to_supplier(self, po):
"""
Submit approved PO to supplier
Methods:
- API integration (preferred)
- EDI
- Email
- Portal upload
"""
supplier = po['supplier']
# Check if supplier has API integration
if supplier in self.config.get('supplier_api_endpoints', {}):
self.submit_via_api(po, supplier)
else:
self.submit_via_email(po, supplier)
print(f"PO {po['po_number']} submitted to {supplier}")
def submit_via_api(self, po, supplier):
"""Submit PO via supplier API"""
import requests
api_endpoint = self.config['supplier_api_endpoints'][supplier]
payload = {
'po_number': po['po_number'],
'order_date': po['order_date'].isoformat(),
'items': po['items']
}
response = requests.post(
api_endpoint,
json=payload,
headers={'Authorization': f"Bearer {self.config['api_keys'][supplier]}"}
)
if response.status_code == 200:
po['submission_status'] = 'success'
po['supplier_confirmation'] = response.json().get('confirmation_number')
else:
po['submission_status'] = 'failed'
self.send_alert(f"PO submission failed: {po['po_number']}")
def submit_via_email(self, po, supplier):
"""Send PO via email"""
# Get supplier email
supplier_email = self.config['supplier_emails'].get(supplier)
if not supplier_email:
self.send_alert(f"No email found for supplier: {supplier}")
return
# Create email
msg = MIMEMultipart()
msg['From'] = self.config['email_config']['from_address']
msg['To'] = supplier_email
msg['Subject'] = f"Purchase Order {po['po_number']}"
# Email body
body = self.format_po_email(po)
msg.attach(MIMEText(body, 'html'))
# Send
try:
with smtplib.SMTP(self.config['email_config']['smtp_server'],
self.config['email_config']['smtp_port']) as server:
server.starttls()
server.login(self.config['email_config']['username'],
self.config['email_config']['password'])
server.send_message(msg)
po['submission_status'] = 'success'
except Exception as e:
po['submission_status'] = 'failed'
self.send_alert(f"Email sending failed: {e}")
def format_po_email(self, po):
"""Format PO as HTML email"""
html = f"""
<html>
<body>
<h2>Purchase Order {po['po_number']}</h2>
<p><strong>Order Date:</strong> {po['order_date'].strftime('%Y-%m-%d')}</p>
<h3>Items:</h3>
<table border="1" cellpadding="5" cellspacing="0">
<tr>
<th>SKU</th>
<th>Quantity</th>
<th>Unit Cost</th>
<th>Line Total</th>
</tr>
"""
for item in po['items']:
html += f"""
<tr>
<td>{item['sku']}</td>
<td>{item['quantity']}</td>
<td>${item['unit_cost']:.2f}</td>
<td>${item['line_total']:.2f}</td>
</tr>
"""
html += f"""
</table>
<p><strong>Total:</strong> ${po['total_value']:,.2f}</p>
<p>Please confirm receipt of this order.</p>
</body>
</html>
"""
return html
def send_approval_request(self, po):
"""Send approval request for high-value PO"""
approval_url = f"{self.config['approval_portal_url']}/approve/{po['po_number']}"
msg = MIMEText(f"""
Purchase Order {po['po_number']} requires approval.
Supplier: {po['supplier']}
Total Value: ${po['total_value']:,.2f}
Items: {len(po['items'])}
Approve here: {approval_url}
""")
msg['Subject'] = f"PO Approval Required: {po['po_number']}"
msg['From'] = self.config['email_config']['from_address']
msg['To'] = self.config['approver_email']
# Send email (simplified)
print(f"Approval request sent for PO {po['po_number']}")
def send_alert(self, message):
"""Send alert notification"""
print(f"ALERT: {message}")
# In production: send to monitoring system, email, Slack, etc.
def run_daily_replenishment(self):
"""
Main execution: daily automated replenishment cycle
"""
print(f"\n{'='*60}")
print(f"Starting Automated Replenishment Cycle")
print(f"Time: {datetime.now()}")
print(f"{'='*60}\n")
try:
# Step 1: Load inventory data
print("1. Loading inventory data...")
self.load_inventory_data('erp_database')
# Step 2: Calculate reorder needs
print("2. Calculating reorder needs...")
reorder_items = self.calculate_reorder_needs()
print(f" Found {len(reorder_items)} items needing reorder")
if len(reorder_items) == 0:
print("\nNo items need reordering. Cycle complete.")
return
# Step 3: Optimize order quantities
print("3. Optimizing order quantities...")
reorder_items = self.optimize_order_quantities(reorder_items)
# Step 4: Generate purchase orders
print("4. Generating purchase orders...")
pos_created = self.generate_purchase_orders(reorder_items)
print(f" Created {len(pos_created)} purchase orders")
# Step 5: Summary report
print("\n" + "="*60)
print("Replenishment Cycle Summary")
print("="*60)
for po in pos_created:
print(f"PO {po['po_number']}: {po['supplier']} - "
f"${po['total_value']:,.2f} - {po['status']}")
print(f"\nTotal Value: ${sum(po['total_value'] for po in pos_created):,.2f}")
print("\nCycle completed successfully.\n")
except Exception as e:
print(f"\nERROR: Replenishment cycle failed: {e}")
self.send_alert(f"Replenishment automation failed: {e}")
# Example usage
config = {
'reorder_point_method': 'dynamic',
'order_approval_threshold': 10000,
'supplier_api_endpoints': {
'Supplier_A': 'https://api.suppliera.com/orders'
},
'api_keys': {
'Supplier_A': 'api_key_123'
},
'supplier_emails': {
'Supplier_B': 'orders@supplierb.com'
},
'email_config': {
'smtp_server': 'smtp.gmail.com',
'smtp_port': 587,
'from_address': 'automation@company.com',
'username': 'automation@company.com',
'password': 'password'
},
'approver_email': 'manager@company.com',
'approval_portal_url': 'https://portal.company.com'
}
# Create and run automation
replenishment = AutomatedReplenishment(config)
replenishment.run_daily_replenishment()Robotic Process Automation (RPA)
Invoice Processing Automation
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
import pytesseract
from PIL import Image
import pandas as pd
import time
class InvoiceProcessingBot:
"""
RPA bot to automate invoice processing
Tasks:
1. Download invoices from email/portal
2. Extract data using OCR
3. Validate against POs
4. Enter into ERP system
5. Route for approval if needed
"""
def __init__(self, config):
self.config = config
self.driver = None
self.invoices_processed = []
def initialize_browser(self):
"""Initialize web browser for automation"""
options = webdriver.ChromeOptions()
if self.config.get('headless', False):
options.add_argument('--headless')
self.driver = webdriver.Chrome(options=options)
self.driver.implicitly_wait(10)
def login_to_portal(self, url, username, password):
"""Login to supplier portal"""
self.driver.get(url)
# Wait for login form
username_field = WebDriverWait(self.driver, 10).until(
EC.presence_of_element_located((By.ID, "username"))
)
username_field.send_keys(username)
self.driver.find_element(By.ID, "password").send_keys(password)
self.driver.find_element(By.ID, "login-button").click()
# Wait for dashboard to load
time.sleep(2)
def download_invoices(self):
"""Download new invoices from portal"""
# Navigate to invoices page
self.driver.find_element(By.LINK_TEXT, "Invoices").click()
# Find new invoices
invoice_rows = self.driver.find_elements(
By.CSS_SELECTOR,
"tr.invoice-row.status-new"
)
downloaded_files = []
for row in invoice_rows:
invoice_number = row.find_element(
By.CSS_SELECTOR,
".invoice-number"
).text
download_button = row.find_element(
By.CSS_SELECTOR,
".download-button"
)
download_button.click()
time.sleep(1) # Wait for download
downloaded_files.append({
'invoice_number': invoice_number,
'file_path': f"/downloads/{invoice_number}.pdf"
})
return downloaded_files
def extract_invoice_data(self, file_path):
"""
Extract data from invoice using OCR
Returns structured invoice data
"""
# Convert PDF to image (simplified)
# In production, use pdf2image library
image = Image.open(file_path)
# OCR
text = pytesseract.image_to_string(image)
# Parse extracted text
invoice_data = self.parse_invoice_text(text)
return invoice_data
def parse_invoice_text(self, text):
"""
Parse OCR text to extract structured data
Uses regex and NLP to find key fields
"""
import re
data = {}
# Extract invoice number
inv_match = re.search(r'Invoice #:?\s*(\w+)', text, re.IGNORECASE)
if inv_match:
data['invoice_number'] = inv_match.group(1)
# Extract date
date_match = re.search(
r'Date:?\s*(\d{1,2}[/-]\d{1,2}[/-]\d{2,4})',
text,
re.IGNORECASE
)
if date_match:
data['invoice_date'] = date_match.group(1)
# Extract PO number
po_match = re.search(r'PO #:?\s*(\w+)', text, re.IGNORECASE)
if po_match:
data['po_number'] = po_match.group(1)
# Extract total amount
total_match = re.search(
r'Total:?\s*\$?\s*([\d,]+\.?\d*)',
text,
re.IGNORECASE
)
if total_match:
data['total_amount'] = float(total_match.group(1).replace(',', ''))
# Extract line items (simplified)
# In production, use more sophisticated parsing
data['line_items'] = []
return data
def validate_invoice(self, invoice_data):
"""
Validate invoice against PO and business rules
Checks:
- PO exists
- Amounts match
- Items match
- Not a duplicate
"""
validation_results = {
'valid': True,
'errors': [],
'warnings': []
}
# Check PO exists
po = self.lookup_po(invoice_data.get('po_number'))
if not po:
validation_results['valid'] = False
validation_results['errors'].append(
f"PO {invoice_data.get('po_number')} not found"
)
return validation_results
# Check amount matches (within tolerance)
tolerance = 0.01 # 1%
if abs(invoice_data['total_amount'] - po['total']) / po['total'] > tolerance:
validation_results['warnings'].append(
f"Amount mismatch: Invoice ${invoice_data['total_amount']:.2f} "
f"vs PO ${po['total']:.2f}"
)
# Check for duplicate
if self.is_duplicate_invoice(invoice_data['invoice_number']):
validation_results['valid'] = False
validation_results['errors'].append(
f"Duplicate invoice: {invoice_data['invoice_number']}"
)
return validation_results
def lookup_po(self, po_number):
"""Look up PO in ERP system"""
# In production: query ERP database or API
# Placeholder return
return {
'po_number': po_number,
'total': 1250.00,
'items': []
}
def is_duplicate_invoice(self, invoice_number):
"""Check if invoice already processed"""
# In production: query invoice database
return False
def enter_invoice_in_erp(self, invoice_data):
"""
Enter invoice into ERP system
Uses RPA to navigate ERP interface
"""
# Navigate to AP module
self.driver.get(self.config['erp_url'])
# Wait for page load
time.sleep(2)
# Click on Accounts Payable
self.driver.find_element(By.LINK_TEXT, "Accounts Payable").click()
# Click New Invoice
self.driver.find_element(By.ID, "new-invoice-button").click()
# Fill in invoice fields
self.driver.find_element(By.ID, "invoice-number").send_keys(
invoice_data['invoice_number']
)
self.driver.find_element(By.ID, "invoice-date").send_keys(
invoice_data['invoice_date']
)
self.driver.find_element(By.ID, "po-number").send_keys(
invoice_data['po_number']
)
self.driver.find_element(By.ID, "total-amount").send_keys(
str(invoice_data['total_amount'])
)
# Add line items
for item in invoice_data.get('line_items', []):
# Click add line
self.driver.find_element(By.ID, "add-line-button").click()
# Fill line details
# ... (detailed field entry)
# Submit invoice
self.driver.find_element(By.ID, "submit-button").click()
# Wait for confirmation
confirmation = WebDriverWait(self.driver, 10).until(
EC.presence_of_element_located((By.CLASS_NAME, "success-message"))
)
return confirmation.text
def run_invoice_processing(self):
"""
Main automation workflow
"""
print("\nStarting Invoice Processing Automation")
print("="*60)
try:
# Initialize browser
print("1. Initializing browser...")
self.initialize_browser()
# Login to supplier portal
print("2. Logging in to supplier portal...")
self.login_to_portal(
self.config['supplier_portal_url'],
self.config['portal_username'],
self.config['portal_password']
)
# Download invoices
print("3. Downloading invoices...")
invoices = self.download_invoices()
print(f" Downloaded {len(invoices)} invoices")
# Process each invoice
for invoice_file in invoices:
print(f"\nProcessing {invoice_file['invoice_number']}...")
# Extract data
invoice_data = self.extract_invoice_data(invoice_file['file_path'])
# Validate
validation = self.validate_invoice(invoice_data)
if not validation['valid']:
print(f" FAILED validation: {validation['errors']}")
# Route for manual review
continue
if validation['warnings']:
print(f" WARNINGS: {validation['warnings']}")
# Route for approval
continue
# Enter in ERP
result = self.enter_invoice_in_erp(invoice_data)
print(f" SUCCESS: {result}")
self.invoices_processed.append({
'invoice_number': invoice_data['invoice_number'],
'status': 'processed',
'timestamp': datetime.now()
})
print(f"\n{'='*60}")
print(f"Processing complete: {len(self.invoices_processed)} invoices")
print("="*60 + "\n")
except Exception as e:
print(f"\nERROR: Automation failed: {e}")
finally:
if self.driver:
self.driver.quit()
# Configuration
config = {
'headless': False,
'supplier_portal_url': 'https://portal.supplier.com',
'portal_username': 'user@company.com',
'portal_password': 'password',
'erp_url': 'https://erp.company.com',
'download_path': '/downloads'
}
# Run automation
bot = InvoiceProcessingBot(config)
# bot.run_invoice_processing()Workflow Orchestration
Apache Airflow DAG Example
from airflow import DAG
from airflow.operators.python import PythonOperator
from airflow.operators.email import EmailOperator
from airflow.utils.dates import days_ago
from datetime import timedelta
# Define workflow tasks
def extract_orders_from_erp():
"""Extract new orders from ERP system"""
print("Extracting orders from ERP...")
# Implementation
return {'orders_count': 150}
def validate_inventory():
"""Check inventory availability"""
print("Validating inventory...")
# Implementation
return {'available': True}
def allocate_inventory():
"""Allocate inventory to orders"""
print("Allocating inventory...")
# Implementation
return {'allocated_orders': 145}
def generate_pick_lists():
"""Generate warehouse pick lists"""
print("Generating pick lists...")
# Implementation
return {'pick_lists_created': 145}
def send_to_wms():
"""Send pick lists to WMS"""
print("Sending to WMS...")
# Implementation
return {'status': 'success'}
# Define DAG
default_args = {
'owner': 'supply-chain',
'depends_on_past': False,
'email': ['alerts@company.com'],
'email_on_failure': True,
'email_on_retry': False,
'retries': 2,
'retry_delay': timedelta(minutes=5)
}
dag = DAG(
'order_fulfillment_automation',
default_args=default_args,
description='Automated order fulfillment workflow',
schedule_interval='*/15 * * * *', # Every 15 minutes
start_date=days_ago(1),
catchup=False,
tags=['supply-chain', 'fulfillment']
)
# Define tasks
t1 = PythonOperator(
task_id='extract_orders',
python_callable=extract_orders_from_erp,
dag=dag
)
t2 = PythonOperator(
task_id='validate_inventory',
python_callable=validate_inventory,
dag=dag
)
t3 = PythonOperator(
task_id='allocate_inventory',
python_callable=allocate_inventory,
dag=dag
)
t4 = PythonOperator(
task_id='generate_pick_lists',
python_callable=generate_pick_lists,
dag=dag
)
t5 = PythonOperator(
task_id='send_to_wms',
python_callable=send_to_wms,
dag=dag
)
t6 = EmailOperator(
task_id='send_completion_email',
to='operations@company.com',
subject='Order Fulfillment Workflow Complete',
html_content='<p>The order fulfillment workflow has completed successfully.</p>',
dag=dag
)
# Define dependencies
t1 >> t2 >> t3 >> t4 >> t5 >> t6API Integration & Middleware
REST API Integration
import requests
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry
import json
from datetime import datetime
class SupplyChainAPIIntegration:
"""
Middleware for integrating multiple supply chain systems
"""
def __init__(self, config):
self.config = config
self.session = self.create_session()
def create_session(self):
"""
Create requests session with retry logic
"""
session = requests.Session()
retry_strategy = Retry(
total=3,
status_forcelist=[429, 500, 502, 503, 504],
method_whitelist=["HEAD", "GET", "OPTIONS", "POST"],
backoff_factor=1
)
adapter = HTTPAdapter(max_retries=retry_strategy)
session.mount("https://", adapter)
session.mount("http://", adapter)
return session
def get_erp_orders(self, date_from, date_to):
"""
Fetch orders from ERP system
ERP: SAP, Oracle, NetSuite, etc.
"""
url = f"{self.config['erp_base_url']}/api/orders"
headers = {
'Authorization': f"Bearer {self.config['erp_api_token']}",
'Content-Type': 'application/json'
}
params = {
'date_from': date_from.isoformat(),
'date_to': date_to.isoformat(),
'status': 'open'
}
response = self.session.get(url, headers=headers, params=params)
response.raise_for_status()
return response.json()['orders']
def check_wms_inventory(self, sku):
"""
Check inventory levels in WMS
WMS: Manhattan, Blue Yonder, HighJump, etc.
"""
url = f"{self.config['wms_base_url']}/api/inventory/{sku}"
headers = {
'X-API-Key': self.config['wms_api_key']
}
response = self.session.get(url, headers=headers)
response.raise_for_status()
inventory_data = response.json()
return {
'sku': sku,
'on_hand': inventory_data['quantity_on_hand'],
'allocated': inventory_data['quantity_allocated'],
'available': inventory_data['quantity_available']
}
def create_wms_shipment(self, order_data):
"""
Create shipment in WMS
"""
url = f"{self.config['wms_base_url']}/api/shipments"
headers = {
'X-API-Key': self.config['wms_api_key'],
'Content-Type': 'application/json'
}
payload = {
'order_number': order_data['order_number'],
'customer': order_data['customer'],
'ship_to_address': order_data['shipping_address'],
'line_items': order_data['items'],
'priority': order_data.get('priority', 'normal'),
'requested_ship_date': order_data['requested_ship_date']
}
response = self.session.post(url, headers=headers, json=payload)
response.raise_for_status()
return response.json()
def get_tms_rates(self, shipment_details):
"""
Get shipping rates from TMS
TMS: MercuryGate, Oracle TMS, Manhattan TMS, etc.
"""
url = f"{self.config['tms_base_url']}/api/rates/quote"
headers = {
'Authorization': f"Bearer {self.config['tms_api_token']}",
'Content-Type': 'application/json'
}
payload = {
'origin': shipment_details['origin'],
'destination': shipment_details['destination'],
'weight': shipment_details['weight'],
'dimensions': shipment_details['dimensions'],
'service_type': shipment_details.get('service_type', 'ground')
}
response = self.session.post(url, headers=headers, json=payload)
response.raise_for_status()
rates = response.json()['rates']
# Return best rate
return min(rates, key=lambda x: x['total_cost'])
def sync_order_status(self, order_number):
"""
Sync order status across systems
Ensures ERP, WMS, TMS all have current status
"""
# Get status from WMS
wms_status = self.get_wms_order_status(order_number)
# Update ERP
self.update_erp_order_status(order_number, wms_status)
# If shipped, update TMS
if wms_status['status'] == 'shipped':
self.update_tms_tracking(order_number, wms_status)
return wms_status
def orchestrate_order_fulfillment(self, order_number):
"""
End-to-end order fulfillment orchestration
Coordinates across ERP, WMS, TMS
"""
print(f"\nOrchestrating fulfillment for order {order_number}")
try:
# 1. Get order details from ERP
order = self.get_order_from_erp(order_number)
print(f" Order retrieved from ERP")
# 2. Check inventory in WMS
inventory_available = True
for item in order['items']:
inventory = self.check_wms_inventory(item['sku'])
if inventory['available'] < item['quantity']:
inventory_available = False
print(f" WARNING: Insufficient inventory for {item['sku']}")
if not inventory_available:
return {'status': 'backorder'}
# 3. Create shipment in WMS
shipment = self.create_wms_shipment(order)
print(f" Shipment created in WMS: {shipment['shipment_id']}")
# 4. Get shipping rates from TMS
rate = self.get_tms_rates({
'origin': shipment['origin'],
'destination': order['shipping_address'],
'weight': shipment['total_weight'],
'dimensions': shipment['dimensions']
})
print(f" Best shipping rate: ${rate['total_cost']:.2f}")
# 5. Update ERP with shipping info
self.update_erp_order(order_number, {
'shipment_id': shipment['shipment_id'],
'carrier': rate['carrier'],
'freight_cost': rate['total_cost'],
'status': 'in_fulfillment'
})
print(f" ERP updated with shipment details")
return {
'status': 'success',
'shipment_id': shipment['shipment_id'],
'freight_cost': rate['total_cost']
}
except Exception as e:
print(f" ERROR: {e}")
return {'status': 'error', 'message': str(e)}
# Configuration
config = {
'erp_base_url': 'https://erp.company.com',
'erp_api_token': 'erp_token_123',
'wms_base_url': 'https://wms.company.com',
'wms_api_key': 'wms_key_456',
'tms_base_url': 'https://tms.company.com',
'tms_api_token': 'tms_token_789'
}
# Example usage
integration = SupplyChainAPIIntegration(config)
result = integration.orchestrate_order_fulfillment('ORDER-12345')
print(f"\nResult: {result}")Tools & Technologies
RPA Platforms
Commercial:
- UiPath: Leading RPA platform
- Blue Prism: Enterprise RPA
- Automation Anywhere: Cloud-native RPA
- Microsoft Power Automate: Microsoft ecosystem integration
- WorkFusion: AI-powered automation
Open Source:
- Robot Framework: Generic automation framework
- Selenium: Web browser automation
- Puppeteer: Node.js browser automation
- TagUI: RPA tool for automating websites
Workflow Orchestration
Apache Airflow: Python-based workflow orchestration Prefect: Modern workflow orchestration Luigi (Spotify): Python workflow engine Dagster: Data orchestration platform n8n: Workflow automation (low-code) Zapier: No-code automation (SaaS) Make (Integromat): Visual automation platform
API Integration
Python Libraries:
requests: HTTP libraryhttpx: Async HTTP clientaiohttp: Async HTTP client/serverfastapi: Build APIscelery: Distributed task queue
iPaaS (Integration Platform as a Service):
- MuleSoft: Enterprise integration
- Dell Boomi: Cloud integration
- Informatica: Data integration
- Jitterbit: Integration platform
- Workato: Enterprise automation
Common Challenges & Solutions
Challenge: System Downtime and Failures
Problem:
- Automated processes fail when systems are down
- No manual fallback
- Data inconsistency
Solutions:
- Implement retry logic with exponential backoff
- Circuit breaker pattern
- Health checks and monitoring
- Fallback to manual process
- Queue-based processing (can resume after downtime)
- Comprehensive error logging
Challenge: Change Management
Problem:
- UI changes break RPA bots
- API versioning issues
- Business process changes
Solutions:
- Use APIs instead of UI automation when possible
- Modular design (easy to update components)
- Version control for automation scripts
- Regular maintenance schedule
- Monitoring for automation failures
- Documentation of dependencies
Challenge: Data Quality Issues
Problem:
- Bad data causes automation failures
- Garbage in, garbage out
Solutions:
- Input validation before processing
- Data quality checks
- Exception handling and alerts
- Human review for edge cases
- Data cleansing preprocessing
- Clear business rules for data standards
Challenge: Security and Compliance
Problem:
- Bots have access to sensitive systems
- Audit trail concerns
- Regulatory compliance
Solutions:
- Principle of least privilege (minimal access)
- Credential vaulting (no hardcoded passwords)
- Comprehensive logging of all actions
- Regular security audits
- Encryption of sensitive data
- Compliance with SOX, GDPR, etc.
Output Format
Automation Project Report
Executive Summary:
- Process automated
- Expected benefits (time savings, cost reduction, accuracy)
- Implementation timeline
- ROI analysis
Current State Analysis:
- Process description
- Volume and frequency
- Current pain points
- Time and cost metrics
Solution Design:
- Automation approach
- Systems integrated
- Workflow diagram
- Exception handling
Implementation Plan:
| Phase | Activities | Duration | Resources |
|---|---|---|---|
| 1. Setup | Tool installation, access provisioning | 2 weeks | IT, 1 developer |
| 2. Development | Bot development, testing | 4 weeks | 2 developers |
| 3. UAT | User acceptance testing | 2 weeks | Business users |
| 4. Deployment | Production deployment, monitoring | 1 week | IT, developers |
| 5. Support | Hypercare, optimization | 4 weeks | Support team |
Business Case:
| Metric | Before | After | Improvement |
|---|---|---|---|
| Process Time | 4 hours/day | 30 min/day | 88% reduction |
| Error Rate | 5% | 0.5% | 90% reduction |
| FTE Required | 1.0 | 0.25 | 0.75 FTE saved |
| Annual Cost | $80,000 | $20,000 | $60,000 savings |
ROI:
- Investment: $150,000 (development + infrastructure)
- Annual Savings: $60,000
- Payback Period: 2.5 years
- 3-Year ROI: 20%
Questions to Ask
If you need more context:
- What process needs automation?
- What's the current process? (manual steps, systems involved)
- What's the volume and frequency? (1000 transactions/day, hourly)
- What systems are involved? (ERP, WMS, TMS, spreadsheets)
- Are APIs available or screen scraping needed?
- What's the expected ROI and timeline?
- Are there compliance or security requirements?
- Who will maintain the automation?
Related Skills
- supply-chain-analytics: For monitoring automation performance
- digital-twin-modeling: For simulating automated processes
- ml-supply-chain: For intelligent automation with ML
- prescriptive-analytics: For automated decision-making
- optimization-modeling: For optimizing automated workflows
- demand-forecasting: For automated replenishment
- inventory-optimization: For automated reorder triggers
- order-fulfillment: For fulfillment automation