Deployment Key Performance Indicators for Sustainable Manufacturing

[EN] The Zero-Defect Manufacturing (ZDM) strategy, particularly the Zero Defect Zero Waste (ZDZW) methodology, emerges as a crucial approach to enhance sustainability in the global manufacturing supply chain. The European Union project `ZDZW¿, focusing on diverse industrial scenarios, addresses chal...

Descripción completa

Detalles Bibliográficos
Autores: Lario-Femenía, Joan|||0000-0003-4843-3334, Mateos-Luengo, Javier, Karadag, Sena, Goyal, Shashank
Tipo de recurso: artículo
Fecha de publicación:2026
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:dnet:riunet______::a09278857c42a5ec7e3b13841338e9cb
Acceso en línea:https://riunet.upv.es/handle/10251/235086
Access Level:acceso abierto
Palabra clave:Sustainability
Zero defects
Zero waste
KPI
Non-destructive inspection technologies
16.- Promover sociedades pacíficas e inclusivas para el desarrollo sostenible, facilitar acceso a la justicia para todos y crear instituciones eficaces, responsables e inclusivas a todos los niveles
Descripción
Sumario:[EN] The Zero-Defect Manufacturing (ZDM) strategy, particularly the Zero Defect Zero Waste (ZDZW) methodology, emerges as a crucial approach to enhance sustainability in the global manufacturing supply chain. The European Union project `ZDZW¿, focusing on diverse industrial scenarios, addresses challenges faced by industries such as plastics, metals, energy, ceramics, and consumer goods. Within this framework, the integration of ZDZW technologies, including Non-Destructive Inspection Technologies (NDIT) and artificial intelligence (AI), becomes pivotal. The industrial use case presented involves implementing ZDZW solutions in the thermoforming process for refrigerator inner body parts. This integration aims to automate quality assessment, reduce defects, and optimize production quality. The application of AI-enhanced thermal imaging and digital twin models provides real-time data for quality control, minimizing scrap rates and energy consumption. Sustainable Key Performance Indicators (KPIs) are defined to evaluate the impact of NDIT, emphasizing the reduction of scrap rates, carbon dioxide emissions, and overall environmental impact. The ZDZW methodology, positioned as part of the smart manufacturing ecosystem, contributes to innovative quality assurance, control, and sustainability services, aligning with the growing demand for sustainable production in the face of global challenges and disruptions.