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| import React, { useState, useRef } from 'react'; | ||
| import { Canvas, useFrame } from '@react-three/fiber'; | ||
| import { XR, ARButton, Controllers, Hands } from '@react-three/xr'; | ||
| import { OrbitControls, Text, Sky, ContactShadows, Environment, Float, Box } from '@react-three/drei'; | ||
| import * as THREE from 'three'; | ||
| import { ethers } from 'ethers'; | ||
|
|
||
| // --- Components --- | ||
|
|
||
| // Digital Twin: Warehouse / Cargo Box | ||
| function CargoBox({ position, color, speed = 0.01 }) { | ||
| const meshRef = useRef(); | ||
| const [hovered, setHovered] = useState(false); | ||
|
|
||
| useFrame((state) => { | ||
| if (meshRef.current) { | ||
| // Move box back and forth to simulate movement in a warehouse | ||
| meshRef.current.position.z += speed * Math.sin(state.clock.elapsedTime); | ||
|
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. issue (bug_risk): The cargo box Z-position update will drift over time instead of oscillating around a fixed point. Since you're incrementing const baseZ = useRef(position[2]);
useFrame((state) => {
if (meshRef.current) {
meshRef.current.position.z = baseZ.current + speed * Math.sin(state.clock.elapsedTime);
}
});This keeps the motion bounded around the initial Z position. |
||
| } | ||
| }); | ||
|
|
||
| return ( | ||
| <Float speed={2} rotationIntensity={0.5} floatIntensity={0.5}> | ||
| <Box | ||
| ref={meshRef} | ||
| position={position} | ||
| args={[0.5, 0.5, 0.5]} | ||
| onPointerOver={() => setHovered(true)} | ||
| onPointerOut={() => setHovered(false)} | ||
| > | ||
| <meshStandardMaterial color={hovered ? 'orange' : color} /> | ||
| </Box> | ||
| </Float> | ||
| ); | ||
| } | ||
|
|
||
| // Digital Twin: Warehouse Floor | ||
| function Warehouse() { | ||
| return ( | ||
| <group> | ||
| <mesh rotation={[-Math.PI / 2, 0, 0]} receiveShadow> | ||
| <planeGeometry args={[20, 20]} /> | ||
| <meshStandardMaterial color="#222" /> | ||
| </mesh> | ||
| <gridHelper args={[20, 20, 0xffffff, 0x444444]} rotation={[-Math.PI / 2, 0, 0]} /> | ||
|
|
||
| {/* Some shelving units simulated by boxes */} | ||
| <Box position={[-2, 0.5, -2]} args={[1, 1, 4]}> | ||
| <meshStandardMaterial color="#555" /> | ||
| </Box> | ||
| <Box position={[2, 0.5, -2]} args={[1, 1, 4]}> | ||
| <meshStandardMaterial color="#555" /> | ||
| </Box> | ||
|
|
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| {/* Moving Cargo */} | ||
| <CargoBox position={[-1, 0.5, 0]} color="#8B4513" speed={0.02} /> | ||
| <CargoBox position={[1, 0.5, -1]} color="#CD853F" speed={0.015} /> | ||
| <CargoBox position={[0, 0.5, -2]} color="#DEB887" speed={0.01} /> | ||
| </group> | ||
| ); | ||
| } | ||
|
|
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| // --- Main Component --- | ||
|
|
||
| const INCOTERMS_DATA = { | ||
| "EXW": "Ex Works: Buyer takes all risk from seller's door.", | ||
| "FOB": "Free On Board: Seller covers costs until goods are on ship.", | ||
| "CIF": "Cost, Insurance, and Freight: Seller pays to destination port.", | ||
| "DDP": "Delivered Duty Paid: Seller covers all costs including taxes." | ||
| }; | ||
|
|
||
| export default function SupplyChainPlatform() { | ||
| const [activeTab, setActiveTab] = useState('twin'); | ||
| const [selectedTerm, setSelectedTerm] = useState('EXW'); | ||
| const [trackingId, setTrackingId] = useState(''); | ||
| const [aiStatus, setAiStatus] = useState('Idle'); | ||
| const [blockchainLog, setBlockchainLog] = useState([]); | ||
|
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| const logToBlockchain = async (event) => { | ||
| setAiStatus('Securing data on blockchain...'); | ||
| // Simulate ethers interaction | ||
| const hash = ethers.id(event + Date.now()); | ||
| const newLog = { event, hash: hash.substring(0, 16) + '...', time: new Date().toLocaleTimeString() }; | ||
| setBlockchainLog([newLog, ...blockchainLog].slice(0, 5)); | ||
|
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. issue (bug_risk): State update for
setBlockchainLog(prev => [newLog, ...prev].slice(0, 5)); |
||
| await new Promise(r => setTimeout(r, 800)); | ||
| setAiStatus('Data Verified.'); | ||
| }; | ||
|
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| const runAIPrediction = () => { | ||
| setAiStatus('AI Analyzing supply chain routes...'); | ||
| setTimeout(() => { | ||
| setAiStatus('Optimal route found: Route A-7 via Singapore. Delay Probability: 5%.'); | ||
| logToBlockchain('Route Optimization Run'); | ||
| }, 1500); | ||
| }; | ||
|
|
||
| return ( | ||
| <div className="supply-chain-container" style={{ color: 'white', textAlign: 'left', padding: '20px' }}> | ||
| <h2>Supply Chain & Digital Twin Platform</h2> | ||
|
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| <div className="tabs" style={{ marginBottom: '20px', display: 'flex', gap: '10px' }}> | ||
| <button onClick={() => setActiveTab('twin')}>Digital Twin (3D)</button> | ||
| <button onClick={() => setActiveTab('incoterms')}>Incoterms</button> | ||
| <button onClick={() => setActiveTab('logistics')}>Logistics AI</button> | ||
| </div> | ||
|
|
||
| {activeTab === 'twin' && ( | ||
| <div style={{ width: '100%', height: '500px', background: '#000', borderRadius: '10px', overflow: 'hidden', position: 'relative' }}> | ||
| <ARButton /> | ||
| <Canvas shadows camera={{ position: [5, 5, 5], fov: 50 }}> | ||
| <XR> | ||
| <Sky sunPosition={[100, 20, 100]} /> | ||
| <Environment preset="warehouse" /> | ||
| <ambientLight intensity={0.5} /> | ||
| <pointLight position={[10, 10, 10]} castShadow /> | ||
|
|
||
| <Warehouse /> | ||
|
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||
| <Text position={[0, 4, -5]} fontSize={0.5} color="white"> | ||
| Warehouse Digital Twin | ||
| </Text> | ||
|
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||
| <Controllers /> | ||
| <Hands /> | ||
| <OrbitControls /> | ||
| <ContactShadows opacity={0.4} scale={20} blur={2} far={4.5} /> | ||
| </XR> | ||
| </Canvas> | ||
| <div style={{ position: 'absolute', bottom: 10, left: 10, background: 'rgba(0,0,0,0.6)', padding: '10px', fontSize: '12px' }}> | ||
| Interactive 3D Simulation. Use mouse to rotate. Box movement simulates AGVs (Automated Guided Vehicles). | ||
| </div> | ||
| </div> | ||
| )} | ||
|
|
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| {activeTab === 'incoterms' && ( | ||
| <div style={{ background: '#222', padding: '20px', borderRadius: '10px' }}> | ||
| <h3>Incoterms 2020 Navigator</h3> | ||
| <select | ||
| value={selectedTerm} | ||
| onChange={(e) => setSelectedTerm(e.target.value)} | ||
| style={{ padding: '10px', borderRadius: '5px', width: '100%', marginBottom: '20px' }} | ||
| > | ||
| {Object.keys(INCOTERMS_DATA).map(term => ( | ||
| <option key={term} value={term}>{term}</option> | ||
| ))} | ||
| </select> | ||
| <div style={{ padding: '20px', border: '1px solid #444', borderRadius: '5px' }}> | ||
| <strong>{selectedTerm}:</strong> {INCOTERMS_DATA[selectedTerm]} | ||
| </div> | ||
| </div> | ||
| )} | ||
|
|
||
| {activeTab === 'logistics' && ( | ||
| <div style={{ display: 'grid', gridTemplateColumns: '1fr 1fr', gap: '20px' }}> | ||
| <div style={{ background: '#222', padding: '20px', borderRadius: '10px' }}> | ||
| <h3>Logistics Optimizer</h3> | ||
| <input | ||
| type="text" | ||
| placeholder="Enter Tracking ID (e.g. SHIP-123)" | ||
| value={trackingId} | ||
| onChange={(e) => setTrackingId(e.target.value)} | ||
| style={{ padding: '10px', width: '80%', marginBottom: '10px' }} | ||
| /> | ||
| <button onClick={runAIPrediction} style={{ display: 'block' }}>Run AI Analysis</button> | ||
| <p style={{ marginTop: '20px', color: '#aaa' }}>Status: <span style={{ color: '#00ff00' }}>{aiStatus}</span></p> | ||
| </div> | ||
|
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| <div style={{ background: '#222', padding: '20px', borderRadius: '10px' }}> | ||
| <h3>Blockchain Audit Trail</h3> | ||
| <ul style={{ listStyle: 'none', padding: 0 }}> | ||
| {blockchainLog.length === 0 && <li>No entries yet.</li>} | ||
| {blockchainLog.map((log, i) => ( | ||
| <li key={i} style={{ fontSize: '12px', borderBottom: '1px solid #333', padding: '5px 0' }}> | ||
| [{log.time}] {log.event} <br/> | ||
| <small style={{ color: '#888' }}>Hash: {log.hash}</small> | ||
| </li> | ||
| ))} | ||
| </ul> | ||
| </div> | ||
| </div> | ||
| )} | ||
|
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| <footer style={{ marginTop: '30px', fontSize: '12px', color: '#666' }}> | ||
| Supply Chain AI Services Software v1.0.0 | Integrated with Digital Twin & Web3 Ledger. | ||
| </footer> | ||
| </div> | ||
| ); | ||
| } | ||
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| # Supply Chain & Logistics AI Platform | ||
|
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| This platform provides a suite of tools for managing supply chain logistics, including a Digital Twin simulation, Incoterms navigator, and AI-driven logistics optimization. | ||
|
|
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| ## Features | ||
|
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| 1. **Digital Twin (3D Simulation):** | ||
| * A real-time 3D representation of a warehouse environment. | ||
| * Visualizes Automated Guided Vehicles (AGVs) and cargo movement. | ||
| * Built with React Three Fiber and Three.js. | ||
| * Supports AR/VR modes. | ||
|
|
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| 2. **Incoterms Navigator:** | ||
| * Comprehensive guide to Incoterms 2020 (EXW, FOB, CIF, DDP, etc.). | ||
| * Clarifies responsibilities and risks for buyers and sellers. | ||
|
|
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| 3. **AI Logistics Engine:** | ||
| * **Delay Predictor:** Uses heuristics to predict shipment delays based on distance and weather conditions. | ||
| * **Inventory Risk Analysis:** Analyzes stock levels against demand forecasts to identify stockout risks. | ||
| * **Route Optimization:** Simulates optimal routing for logistics efficiency. | ||
|
|
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| 4. **Blockchain Audit Trail:** | ||
| * Secures logistics events on a decentralized ledger using Ethers.js. | ||
| * Provides a transparent and immutable history of supply chain operations. | ||
|
|
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| ## Components | ||
|
|
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| ### CLI Tool (Python) | ||
| Located in `supply_chain_platform/supply_chain_main.py`. | ||
| Provides a command-line interface for: | ||
| - Incoterms lookup. | ||
| - AI Delay prediction. | ||
| - Inventory risk assessment. | ||
|
|
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| **Usage:** | ||
| ```bash | ||
| python3 supply_chain_platform/supply_chain_main.py | ||
| ``` | ||
|
|
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| ### Web Interface (React) | ||
| Integrated into the main application dashboard under the "Supply Chain" tab. | ||
| Includes: | ||
| - **Digital Twin View**: Interactive 3D warehouse. | ||
| - **Incoterms Navigator**: Interactive dropdown guide. | ||
| - **Logistics AI Dashboard**: Real-time AI analysis and Blockchain logging. | ||
|
|
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| ## File Structure | ||
| ``` | ||
| supply_chain_platform/ | ||
| ├── supply_chain_main.py # Main CLI application | ||
| ├── ai_logistics_engine.py # Mock AI logic for logistics | ||
| ├── incoterms_data.json # Database of trade terms | ||
| └── README.md # This documentation | ||
| src/ | ||
| └── SupplyChainPlatform.jsx # React frontend component | ||
| ``` | ||
|
|
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| ## Future Enhancements | ||
| - Integration with real-time IoT sensors for live Digital Twin updates. | ||
| - Advanced NLP for automated Incoterm selection from contracts. | ||
| - Real blockchain integration with Ethereum/Polygon testnets. |
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| import random | ||
| import time | ||
|
|
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| class AILogisticsEngine: | ||
| """Mock AI Engine for Logistics Optimization.""" | ||
|
|
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| def predict_delivery_delay(self, route_distance, weather_condition): | ||
| """Predicts delay based on route distance and weather.""" | ||
| # Simple heuristic-based 'AI' | ||
| base_delay = route_distance / 1000 # 1 hour per 1000km base | ||
|
|
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| weather_multipliers = { | ||
| "clear": 1.0, | ||
| "rain": 1.2, | ||
| "storm": 2.0, | ||
| "snow": 1.8 | ||
| } | ||
|
|
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| multiplier = weather_multipliers.get(weather_condition.lower(), 1.0) | ||
| predicted_delay = base_delay * multiplier * random.uniform(0.9, 1.1) | ||
|
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| return round(predicted_delay, 2) | ||
|
|
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| def optimize_route(self, checkpoints): | ||
| """Simulates route optimization (Traveling Salesman Problem mock).""" | ||
| # Just shuffles for simulation | ||
| optimized = list(checkpoints) | ||
| random.shuffle(optimized) | ||
| return optimized | ||
|
|
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| def analyze_supply_chain_risk(self, inventory_level, demand_forecast): | ||
| """Analyzes risk of stockout.""" | ||
| if inventory_level < (demand_forecast * 0.5): | ||
| return "HIGH: Risk of stockout within 48 hours." | ||
| elif inventory_level < demand_forecast: | ||
| return "MEDIUM: Low stock, replenishment recommended." | ||
| else: | ||
| return "LOW: Healthy inventory levels." | ||
|
|
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| if __name__ == "__main__": | ||
| engine = AILogisticsEngine() | ||
| print(f"Predicted Delay: {engine.predict_delivery_delay(5000, 'storm')} hours") |
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| { | ||
| "EXW": { | ||
| "name": "Ex Works", | ||
| "description": "The seller makes the goods available at their premises. The buyer bears all costs and risks of moving the goods to the destination.", | ||
| "responsibilities": "Buyer covers all costs and risks from the seller's door." | ||
| }, | ||
| "FOB": { | ||
| "name": "Free On Board", | ||
| "description": "The seller delivers the goods on board the vessel nominated by the buyer at the named port of shipment.", | ||
| "responsibilities": "Seller covers costs until goods are on the ship. Buyer covers everything after." | ||
| }, | ||
| "CIF": { | ||
| "name": "Cost, Insurance, and Freight", | ||
| "description": "The seller delivers the goods on board the vessel and pays the costs and freight to bring the goods to the named port of destination.", | ||
| "responsibilities": "Seller covers freight and insurance to the destination port." | ||
| }, | ||
| "DDP": { | ||
| "name": "Delivered Duty Paid", | ||
| "description": "The seller delivers the goods to the buyer, cleared for import and not unloaded from any arriving means of transport at the named place of destination.", | ||
| "responsibilities": "Seller covers all costs and risks including import duties and taxes." | ||
| } | ||
| } |
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suggestion (performance): Pulling in the full
ethersbundle on the client for a mock hash may be unnecessarily heavy.Since this hash is only for a simulated log, pulling in all of
ethersjust forethers.idis likely overkill for the client bundle. You could instead:crypto.subtle.digest(for modern browsers), orThis reduces bundle size and keeps the frontend snappier.