Zero Defect Manufacturing (ZDM) has evolved from a long-standing quality philosophy into a comprehensive, data-driven, and sustainability-oriented paradigm for modern industry. This editorial introduces the Special Issue on ZDM, which comprises twelve papers that collectively advance the scientific, technological, and managerial foundations for achieving defect-free production in digitally connected manufacturing environments. The issue builds upon the ZDM life-cycle framework, which integrates core strategies within a continuous loop of data collection, analysis, decision-making, and adaptive learning. The collected contributions address key enabling domains, including data analytics, artificial intelligence, explainable AI, digital assets, cost modelling, human–AI collaboration, human-centric implementation, machine-vision maturity assessment, and the integration of Lean, Industry 4.0, and Industry 5.0 principles. Collectively, they demonstrate the growing maturity of ZDM as both a research field and an industrial practice. Emerging directions highlight sustainability and circularity, standardisation through interoperable data architectures such as AAS and GAIA-X, and human-centric readiness for implementation. The future outlook identifies six research priorities, semantic interoperability, hybrid intelligence, lifecycle integration, standardised benchmarks, cybersecurity, and human-centric design, positioning ZDM as a cornerstone for resilient, intelligent, and sustainable manufacturing.
Zero Defect Manufacturing – from vision to integrated industrial reality
Solina, Vittorio;
2026-01-01
Abstract
Zero Defect Manufacturing (ZDM) has evolved from a long-standing quality philosophy into a comprehensive, data-driven, and sustainability-oriented paradigm for modern industry. This editorial introduces the Special Issue on ZDM, which comprises twelve papers that collectively advance the scientific, technological, and managerial foundations for achieving defect-free production in digitally connected manufacturing environments. The issue builds upon the ZDM life-cycle framework, which integrates core strategies within a continuous loop of data collection, analysis, decision-making, and adaptive learning. The collected contributions address key enabling domains, including data analytics, artificial intelligence, explainable AI, digital assets, cost modelling, human–AI collaboration, human-centric implementation, machine-vision maturity assessment, and the integration of Lean, Industry 4.0, and Industry 5.0 principles. Collectively, they demonstrate the growing maturity of ZDM as both a research field and an industrial practice. Emerging directions highlight sustainability and circularity, standardisation through interoperable data architectures such as AAS and GAIA-X, and human-centric readiness for implementation. The future outlook identifies six research priorities, semantic interoperability, hybrid intelligence, lifecycle integration, standardised benchmarks, cybersecurity, and human-centric design, positioning ZDM as a cornerstone for resilient, intelligent, and sustainable manufacturing.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


