AI-DRIVEN ADAPTIVE MANUFACTURING SYSTEMS: AN ENTERPRISE ARCHITECTURE FRAMEWORK FOR COGNITIVE MANUFACTURING

The enterprise architecture framework for integrating artificial intelligence in manufacturing systems establishes a foundation for creating adaptive and selfoptimizing production environments.The framework tackles fundamental challenges in data integration, model deployment, real-time decision-making, human-AI collaboration, and safety protocols while ensuring operational stability.Through implementation across diverse manufacturing facilities, substantial improvements emerge in production efficiency, quality control, energy optimization, and predictive maintenance capabilities.Detailed insights into architectural components illuminate the path to successful AI integration, encompassing data source integration, model training pipelines, decision engine architectures, operator interface design, and reliability engineering practices.Implementation results validate the framework's effectiveness in enhancing manufacturing operations while maintaining rigorous safety and compliance standards.

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Publication Details

Journal
INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND INFORMATION TECHNOLOGY
Published
2025-02-07
DOI
https://doi.org/10.34218/ijrcait_08_01_129
Primary Topic
Manufacturing Process and Optimization
Type
article
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0.00
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article

AI-DRIVEN ADAPTIVE MANUFACTURING SYSTEMS: AN ENTERPRISE ARCHITECTURE FRAMEWORK FOR COGNITIVE MANUFACTURING

Ramesh Mahankali
INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND INFORMATION TECHNOLOGY
Manufacturing Process and Optimization
article

AI-DRIVEN ADAPTIVE MANUFACTURING SYSTEMS: AN ENTERPRISE ARCHITECTURE FRAMEWORK FOR COGNITIVE MANUFACTURING

Ramesh Mahankali
article en

Abstract

The enterprise architecture framework for integrating artificial intelligence in manufacturing systems establishes a foundation for creating adaptive and selfoptimizing production environments.The framework tackles fundamental challenges in data integration, model deployment, real-time decision-making, human-AI collaboration, and safety protocols while ensuring operational stability.Through implementation across diverse manufacturing facilities, substantial improvements emerge in production efficiency, quality control, energy optimization, and predictive maintenance capabilities.Detailed insights into architectural components illuminate the path to successful AI integration, encompassing data source integration, model training pipelines, decision engine architectures, operator interface design, and reliability engineering practices.Implementation results validate the framework's effectiveness in enhancing manufacturing operations while maintaining rigorous safety and compliance standards.

INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND INFORMATION TECHNOLOGYVol. 8(1)
System Science Applications (United States) (US), Research Applications (United States) (US), Advanced Applications (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 98%
Manufacturing Process and Optimization
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AI-DRIVEN ADAPTIVE MANUFACTURING SYSTEMS: AN ENTERPRISE ARCHITECTURE FRAMEWORK FOR COGNITIVE MANUFACTURING — Ramesh Mahankali · INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND INFORMATION TECHNOLOGY (2025) | TGRS Research Map | TGRS