Revolutionizing Supply Chain Management in RMG: A Systematic Review, AI Traditional vs Intelligent Systems

The Ready-Made Garment (RMG) industry, a vital economic pillar in emerging economies, remains constrained by conventional Supply Chain Management (SCM) systems characterized by operational inefficiencies, prolonged lead times, and high excavation costs. His systematic review interrogates the paradigm shift toward intelligent SCM systems driven by Artificial Intelligence (AI), the Internet of AI Things (AI), blockchain, and Machine Learning (AI) within the RMG sector. Through a rigorous analysis of 23 AI peer-reviewed studies (2012–2025), we demonstrate that intelligent SCM reduces lead times by 25–40%, operational costs by 18–32%, and forecasting errors by >30%, while enhancing traceability and compliance. However, adoption barriers persist, particularly among Small and Medium Enterprises (SMEs), owing to infrastructure deficits, capital constraints, and digital illiteracy. He proposed actionable strategies for capable technology integration, advocating policy-driven support and phased implementation to accelerate the adoption of AI in Industry 4.0.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-07
DOI
https://doi.org/10.5281/zenodo.17284624
Primary Topic
Microbial Community Ecology and Physiology
Type
article
Field-Weighted Citation Impact
0.00
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article

Revolutionizing Supply Chain Management in RMG: A Systematic Review, AI Traditional vs Intelligent Systems

Zenodo (CERN European Organization for Nuclear Research)
Microbial Community Ecology and Physiology
article

Revolutionizing Supply Chain Management in RMG: A Systematic Review, AI Traditional vs Intelligent Systems

article en

Abstract

The Ready-Made Garment (RMG) industry, a vital economic pillar in emerging economies, remains constrained by conventional Supply Chain Management (SCM) systems characterized by operational inefficiencies, prolonged lead times, and high excavation costs. His systematic review interrogates the paradigm shift toward intelligent SCM systems driven by Artificial Intelligence (AI), the Internet of AI Things (AI), blockchain, and Machine Learning (AI) within the RMG sector. Through a rigorous analysis of 23 AI peer-reviewed studies (2012–2025), we demonstrate that intelligent SCM reduces lead times by 25–40%, operational costs by 18–32%, and forecasting errors by >30%, while enhancing traceability and compliance. However, adoption barriers persist, particularly among Small and Medium Enterprises (SMEs), owing to infrastructure deficits, capital constraints, and digital illiteracy. He proposed actionable strategies for capable technology integration, advocating policy-driven support and phased implementation to accelerate the adoption of AI in Industry 4.0.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 40%
Microbial Community Ecology and Physiology
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Revolutionizing Supply Chain Management in RMG: A Systematic Review, AI Traditional vs Intelligent Systems · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS