Adaptive Visual Quality Inspection Based on Defect Prediction From Production Parameters
Author:
Affiliation:
1. Department of Automatics, Biocybernetics and Robotics, Jožef Stefan Institute, Ljubljana, Slovenia
2. SICK d.o.o, Ljubljana, Slovenia
Funder
DIGITOP Project funded by the Ministry of Higher Education, Science and Innovation of Slovenia, Slovenian Research and Innovation Agency and European Union—NextGenerationEU
Slovenian Research Agency through the program group “Automation, Robotics and Biocybernetics”
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/6287639/10380310/10587254.pdf?arnumber=10587254
Reference45 articles.
1. Research Challenges of Industry 4.0 for Quality Management
2. Zero defect manufacturing: state-of-the-art review, shortcomings and future directions in research
3. Analysis of relevant standards for industrial systems to support zero defects manufacturing process
4. Zero Defect Manufacturing Strategies for Reduction of Scrap and Inspection Effort in Multi-stage Production Systems
5. Quality monitoring in multistage manufacturing systems by using machine learning techniques
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