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

Abstract

Este estudio analiza cómo las innovaciones impulsadas por inteligencia artificial están transformando las cadenas de valor en la industria manufacturera, en el contexto de la evolución desde la Industria 4.0 hacia la Industria 6.0. Mediante una metodología mixta, que incluye entrevistas semiestructuradas con 86 actores clave del sector cerámico y revisión de fuentes secundarias, se propone un modelo conceptual que integra tecnologías digitales, sostenibilidad sistémica y cumplimiento regulatorio (CSRD). Los resultados muestran que la IA, los gemelos digitales y la automatización cognitiva mejoran la resiliencia operativa, la personalización, la trazabilidad y la sostenibilidad en redes B2B. El estudio concluye que la Industria 6.0 representa un paradigma cognitivo-tecnológico centrado en la simbiosis humano-máquina, la sostenibilidad sistémica y la gobernanza ética. Aunque centrado en la industria cerámica, el modelo ofrece una base para futuras investigaciones en otros sectores manufactureros.

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.