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Autor: Florian Meierhofer

Autonomous Quality Inspection 4.0

Autonomous Quality Inspection 4.0

Reducing pseudo defects in PCB production by integrating machine learning (ML)
Florian Meierhofer, Jochen Deuse ORCID Icon, Lukas Schulte, Nils Killich
Customers are increasingly demanding electronic components with high quality, which forces companies to continuously fulfil these requirements. This leads to a high number of inspection gates with high inspection severity and a high number of pseudo defects. Double inspections by process experts reduce these defects but generate high inspection costs. Autonomously acting inspection systems meet this challenge. Within this article, a machine learning algorithm was integrated into the solder paste inspection process to form an autonomous quality inspection system.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 6 | Pages 52-56
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  • I4S+
  • Industry 4.0
    • Automation
    • Digital Twin
    • Factory Planning
    • Industry 4.0
    • Internet of Things
    • Lean Production
    • Sustainability
    • Manufacturing Systems
    • Adaptability
  • Artificial Intelligence
  • Functions
    • Start-up Management
    • Maintenance
    • Logistics
    • Assembly
    • Product Development
    • Production Planning
    • Production Control
    • Process Management
    • Quality Management
    • Risk Management
    • Safety
  • Tools
    • Additive Manufacturing
    • Analytics
    • Augmented Reality
    • Blockchain
    • Modularization
    • Training
    • Robotics
    • Sensors
    • Simulation
    • Software
  • Management
    • Services
    • Dynamics
    • Energy Efficiency
    • Leadership
    • Business Models
    • Innovation
    • SME
    • Management
    • Product Piracy
    • Resource Efficiency
    • Strategy
    • Profitability
  • Journal
    • Current Issue
    • Editorial Calendar
    • Editorial Board
    • Order in Print
    • All E-Journals
    • Annual Table of Contents
    • List of Reviewers
  • Information
    • Books
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    • Find ERP Consultants
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