Productivity enhancement in Indian auto component manufacturing supply chain with IoT using neural networks

Abstract

Paper aims: The research aims to investigating the impact of implementing Internet of Things (IoT) using Bayesian networks in the supply chain of manufacturing of Indian auto components enterprises to achieve enhanced productivity and reduced failure rates. Originality: The research’s originality lies in exploring IoT’s impact with Bayesian Networks in Indian auto component manufacturing, showcasing Industry 4.0 applications. Research method: The research utilizes Bayesian Network analysis to investigate IoT’s impact in Indian auto component manufacturing supply chains, validating findings through Industry 4.0-based IoT implementation and a pilot study. Main findings: Implementing IoT in Indian auto component manufacturing enhanced industry performance, productivity, and reduced failure rates with Industry 4.0 technologies. Implications for theory and practice: The research offers theoretical insights into IoT and Industry 4.0’s impact on the automotive industries and practical solutions for practitioners