Title: Blockchain-Enabled Traceability in Smart Manufacturing: Enhancing Data Integrity and Supply Chain Transparency
Authors: Ahmad Muhammad Tahir, Garima Joon, Umema Ahmed
Volume: 9
Issue: 11
Pages: 11-27
Publication Date: 2025/11/28
Abstract:
The industry 4.0 era presents unprecedented opportunities for transforming manufacturing through digitalization. However, ensuring robust traceability and data integrity across complex global supply chains (SCs) remains a significant challenge, leading to issues like counterfeiting, quality control lapses, and inefficiencies. This research explores the synergistic potential of blockchain technology, integrated with the Internet of Things (IoT) Artificial Intelligence (AI), to establish highly secure, transparent, and immutable traceability systems within smart manufacturing (SM) environments. We delve into the fundamental concepts of these core technologies and propose comprehensive system architecture. The research critically examines diverse use cases across key sectors: automotive, pharmaceuticals, and electronics-highlighting tangible benefits such as enhanced product authentication, optimized recall management, and improved regulatory compliance. Concurrently, it addresses the multifaceted challenges, including scalability, interoperability, and cost. Ethical and regulatory considerations, specifically relating to data privacy and governance, are discussed in depth. Finally, the research outlines promising future research directions, including advancements in cross-chain interoperability, AI-driven analytics on blockchain data, and the role of these technologies in fostering sustainable development goals. The aim is to provide a holistic understanding of how this technological convergence can pave the way for more resilient, efficient, and trustworthy manufacturing ecosystems globally.