Integration of Lean Analytics and Industry 6.0: A Novel Meta-Theoretical Framework for Antifragile, Generative AI-Orchestrated, Circular–Regenerative, and Hyper-Connected Manufacturing Ecosystems

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Authors: Mohammad Shahin, Mazdak Maghanaki, F. Frank Chen
Cited by: 7
References: 124

Abstract

The convergence of Lean manufacturing principles with Industry 4.0 has yielded significant operational improvements, yet the emerging paradigm of Industry 6.0—characterized by antifragile, autonomous, and sustainable systems—demands a fundamental rethinking of existing analytical frameworks. This paper introduces the Industry 6.0 Lean Analytics (I6LA) Framework, a novel meta-theoretical approach that integrates Lean principles with the core concepts of Industry 6.0. By systematically analyzing the limitations of current Lean analytics in the context of Industry 6.0 requirements, we identify critical gaps in areas such as system resilience, AI-driven autonomy, and circular economy integration. The I6LA Framework addresses these gaps through four new theoretical pillars: Antifragile Lean Systems Theory, generative AI-Orchestrated Value Streams, Circular–Regenerative Analytics, and Hyper-Connected Ecosystem Integration. This research provides a new set of mathematical models for measuring antifragility, generative orchestration efficiency, and circularity, offering a comprehensive analytical toolkit for the next generation of manufacturing. The framework’s primary contribution is a paradigm shift from optimizing stable, human-in-the-loop systems to managing dynamic, autonomous ecosystems that thrive on volatility and are regenerative by design. This paper provides both a robust theoretical foundation and practical implementation guidance for organizations navigating the transition to Industry 6.0.

Fields of Study & Subjects

Digital Transformation in Industry Supply Chain Resilience and Risk Management Flexible and Reconfigurable Manufacturing Systems

Publication details

Journal / source
Big Data and Cognitive Computing
Publisher
MDPI AG
Volume
10
Issue
2
Pages
65–65
Publication date
17 February 2026
Language
EN