Big Data Driven Manufacturing and Industry 4.0

Abstract

In an Industry 4.0 smart factory, cyber-physical technologies enable the seamless integration of independent discrete systems into a context-sensitive manufacturing environment. This integration optimizes manufacturing processes through decentralized information exchange and real-time communication. An intelligent production system can continuously collect and analyze manufacturing data from shop-floor systems while leveraging decision-support functions to control and enhance operations. Data-driven manufacturing relies on extensive datasets spanning a product’s entire life cycle—from conceptual design to end use and disposal. This perspective paper examines real-world applications of Big Data in manufacturing and highlights its impact on production processes. Additionally, it provides a comprehensive evaluation of key principles underpinning modern data architecture, streamlined data access and flow, digital manufacturing advancements, shop-floor efficiency, and the operational flexibility of Industry 4.0 smart factories. Study findings reveal that the rapid advancement of technoware (machinery and tools), humanware (skills and expertise), infoware (data and procedures), and orgaware (organizational integration) is transforming manufacturing. Industry 4.0 technologies, including data science, AI-boosted machine learning, and interoperability standards for manufacturing, enable real-time decision-making, increased efficiency, and cost reduction.

Description

This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

Publisher

Jomard Publishing

Date of publication

Summer 8-5-2026

Language

english

Persistent identifier

http://hdl.handle.net/10950/5140

Document Type

Article

Publisher Citation

Ali, M. (2026). Big Data Driven Manufacturing and Industry 4.0. Journal of Modern Technology and Engineering, 11(2), 196-219. https://doi.org/10.62476/jmte112196.

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