Smart Manufacturing for Zero-Defect Production Approach
Manufacturing companies strive for higher quality products, cost reduction, and efficient resource usage. Embracing Industry 4.0 technologies like IoT, Big Data, and AI can lead to Zero-Defect Manufacturing and improved sustainability in SME ecosystems through innovative partnerships and cutting-edge solutions.
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Presentation Transcript
I3 Instrument Strand 2a: Smart Manufacturing Z0DIAC: ZERODEFECT MANUFACTURING APPROACH FOR A MORE SUSTAINABLE AND COMPETITIVE SMEs ECOSYSTEMS
Overview of the Overview of the problem problem Manufacturing companies are required to deliver: Higher quality products Lower costs Limiting the use of resources
Main topic Zero Intelligence, IoT and Big Data for reaching the new quality paradigm in Industry 4.0 era of Cyber-Physical Production Systems. Defects Manufacturing (ZDM): Artificial Human operators' integration in the industry 4.0 digital factory framework to strengthen the concept of Operator 4.0 Project main topics: Quality control technologies for Zero Defect Manufacturing Data Analysis and AI for improvement of Manufacturing efficiency and reduction of waste IIoT devices for Operator 4.0
Current partnership Current partnership composition composition NEW Region More Developed Region (MDR) Friuli Venezia Giulia Region Marche Region Less Developed Region (LDR) Terras de Tr s-os- Montes Region NEW Region
Actual Actual Partnership Partnership MORE Laborat rio Colaborativo Montanhas de Investiga o Associa o Mirazeite is a Portuguese company dedicated, since 1977, to the production and packaging of Olive Oils and Edible Oils. NEED: They have problems of quality in their packaging. U-Sense.IT is a Start up that developed a smart inspection tool for inline measurement of Gap and Flush, capable of autonomous computing, running AI algorithms, for an improved process quality. Zannini SpA is a SME that produces precision turned small metal parts. The problem addressed concerns the limited efficiency of the current production quality control processes and its implications on the overall efficiency of the company's production processes.
Possible Possible interactions interactions Cluster 1 LDR Cluster 2 MDR SME SME Technology Provider 1 MDR manufacturer1 LDR SME Technology Provider 2 LDR OEM 1 MDR Laboratory 2 LDR Demand Supply Side Integration of Knowledge Testing Facilities Exchange of Competences Best Practices SME Laboratory 1 MDR manufacturer2 LDR Laboratory 1 LDR
WE ARE LOOKING FOR WE ARE LOOKING FOR Clusters SMEs Technology providers Producers RTOs/Universities
Thank you! Michela Pivetta Project Manager michela.pivetta@clustercomet.it COMET Mechanical Engineering Cluster Friuli Venezia Giulia (Italy)
