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AI-Powered Business Intelligence in Manufacturing: A Technical Overview

Year: 2025

Type: article

Abstract: This comprehensive article explores the transformative impact of Artificial Intelligence (AI) and Business Intelligence (BI) integration in manufacturing environments within the Industry 4.0 framework. The article examines the implementation methodologies, architectural considerations, and performance metrics across various manufacturing domains, including predictive maintenance, quality control, and supply chain optimization. The article demonstrates significant improvements in operational efficiency, cost reduction, and product quality through AI-powered systems. Through detailed analysis of edge computing integration, advanced AI capabilities, and enterprise system architecture, the article provides insights into both current implementations and future technological considerations, offering a roadmap for manufacturing organizations pursuing digital transformation.

Source: International Journal of Scientific Research in Computer Science Engineering and Information Technology

DOI: 10.32628/cseit25112411

Author: Indraneel Madabhushini

Institution: University of Southern Queensland

Language: English

Topic: Impact of AI and Big Data on Business and Society

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4408364893

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