Supply Chain Management projects for M.E., M.Tech, Masters, MS abroad, and PhD students. These Supply Chain Management projects are designed for final year project submissions, research work, and publishing research papers. These research projects guide students to learn, practice, and complete their academic submissions successfully. Each project includes complete source code, project report, PPT, a tutorial, documentation, and a research paper.
Latest Supply Chain Management Projects
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A Situation Based Predictive Approach for Cybersecurity Intrusion Detection and Prevention Using Machine Learning and Deep Learning Algorithms in Wireless Sensor Networks of Industry 4.0
The project aims to improve cybersecurity in wireless sensor networks used in Industry 4.0. It focuses on detecting and preventing cyber-attacks in real time. Machine learning and deep learning algorithms are applied to classify and prioritize threats. The framework uses Decision Tree and MLP models for multi-class intrusion detection and an Autoencoder for binary classification. The goal is to provide accurate, intelligent, and prioritized protection for industrial networks. -
A Framework for Investigating the Adoption of Key Technologies: Presentation of the Methodology and Explorative Analysis of Emerging Practices
This project studies how new technologies like AI, blockchain, 3D printing, and IoT are used in businesses. It reads and analyzes thousands of research papers to find patterns in how companies adopt these technologies. The goal is to identify practices that improve business performance. The study also highlights which practices are most common and could become future standards. -
Linking Digital Servitization and Industrial Sustainability Performance: A Configurational Perspective on Smart Solution Strategies
This project studies how manufacturing companies can help their customers become more sustainable using smart technologies. It looks at how artificial intelligence, focusing on outcomes, working with partners, and creating value together can improve customer performance. The researchers analyzed data from 180 Swedish firms to find strategies that work best. They identified five strategies, with one focused on using technology and partnerships to actively support customer operations. -
A IoT-Based Framework for Cross-Border E-Commerce Supply Chain Using Machine Learning and Optimization
This project uses artificial intelligence to make online international trade more efficient. It builds a smart system that predicts how much of each product customers will buy. The system learns from real data to help businesses manage their supply chains better. As a result, deliveries become faster and operations more accurate.
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