Production
https://prod.org.br/article/doi/10.1590/0103-6513.20240047
Production
Research Article

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

Tushar D. Bhoite; Rajesh B. Buktar

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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

Keywords

Productivity enhancement, Indian auto component manufacturing, Supply chain, IoT (Internet of Things), Neural networks, Bayesian networks, Predictive maintenance, Real-time monitoring, Optimization, Efficiency

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Submitted date:
05/13/2024

Accepted date:
02/06/2025

67e6e833a953952837757155 production Articles
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