Litcius/Paper detail

AI-Driven Transformations in Manufacturing: Bridging Industry 4.0, 5.0, and 6.0 in Sustainable Value Chains

Andrés Fernández‐Miguel, Fernando E. García‐Muiña, Susana Ortíz-Marcos, Mariano Jiménez, Alfonso Pedro Fernández del Hoyo, Davide Settembre‐Blundo

2025Future Internet9 citationsDOIOpen Access PDF

Abstract

This study investigates how AI-driven innovations are reshaping manufacturing value chains through the transition from Industry 4.0 to Industry 6.0, particularly in resource-intensive sectors such as ceramics. Addressing a gap in the literature, the research situates the evolution of manufacturing within the broader context of digital transformation, sustainability, and regulatory demands. A mixed-methods approach was employed, combining semi-structured interviews with key industry stakeholders and an extensive review of secondary data, to develop an Industry 6.0 model tailored to the ceramics industry. The findings demonstrate that artificial intelligence, digital twins, and cognitive automation significantly enhance predictive maintenance, real-time supply chain optimization, and regulatory compliance, notably with the Corporate Sustainability Reporting Directive (CSRD). These technological advancements also facilitate circular economy practices and cognitive logistics, thereby fostering greater transparency and sustainability in B2B manufacturing networks. The study concludes that integrating AI-driven automation and cognitive logistics into digital ecosystems and supply chain management serves as a strategic enabler of operational resilience, regulatory alignment, and long-term competitiveness. While the industry-specific focus may limit generalizability, the study underscores the need for further research in diverse manufacturing sectors and longitudinal analyses to fully assess the long-term impact of AI-enabled Industry 6.0 frameworks.

Topics & Concepts

Supply chainEnablingIndustry 4.0SustainabilityManufacturingContext (archaeology)Transparency (behavior)Bridging (networking)Industrial organizationBusinessBusiness modelProcess managementAmbidexterityComputer scienceCognitive computingValue chainSupply chain managementInteroperabilityKnowledge managementAutomationDigital economyAnalyticsDirectiveCircular economyMultidisciplinary approachSustainable developmentOperational excellenceExploratory researchMarketingValue (mathematics)Triple bottom lineCorporate governanceDigital transformationAdvanced manufacturingDigital Transformation in IndustrySustainable Supply Chain ManagementEconomic and Technological Innovation