Quality Engineering in Industry 4.0: Impacts, Roles, and Tools

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This presentation delves into the realm of Quality 4.0, exploring its impacts on operational performance, the roles of quality researchers in Industry 4.0 and IIOT, data analysis through Google Trends, and a spectrum of quality tools. It covers the evolution of industry from mechanization to the Industrial Internet of Things, emphasizing the significance of quality engineering in the digital age.

  • Quality Engineering
  • Industry 4.0
  • Operational Performance
  • Data Analysis
  • Quality Tools

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Presentation Transcript


  1. Quality 4.0: Quality engineering in Industry 4.0 Presenter: Tu Feng Research Advisor: Dr. Theodore Allen

  2. Background Industry 1.0 Mechanization, Steam Power 1760-1820 Industry 2.0 Electrification, Mass production 1871-1914 Industry 3.0 Computer, Automation, Mass customization Traditional Quality Engineering 1990s Industry 4.0 Industrial Internet of Things, Cyber physical systems Big Data Today Quality 4.0? 3

  3. Review Methods Methods Searched articles based on a list of related keywords Selected 66 articles from over 2000 search results Classified based on 12 criteria 4

  4. Research Questions: What is Quality 4.0? What are its impacts on operational performance? What roles can quality researchers usefully play in relationship to Industry 4.0 and IIOT? 5

  5. Data Analysis Google trends: 6

  6. Data Analysis a) Number of articles over time. b) Number of articles by source c) The yearly number of articles and their authorship d) Number of articles by research approach 7

  7. Data Analysis a) Number of articles in IOT manufacturing applications over time. b) Frequency of most mentioned keywords 8

  8. Conclusion (a) (b) Quality Tools Quality 4.0 Tools Cause-and-effect diagram Artificial intelligence Check sheet Big data Control chart Blockchain Histogram Deep learning Pareto chart Enabling technologies Scatter diagram Machine learning Stratification Data science Design of Experiments Virtual & Augmented Reality Spatial Analyses & RFIDs Dashboarding & Human Factors Digital Twins 9

  9. Conclusion Reinforcement Learning Self-Induced System Corrections Data driven decision-making Shift from Process Operators to Process Designers Quality 4.0 Big Data Self-Management Machines Internet of People and Thing Human Performance and Integration with Business Objectives 10

  10. Thanks! SP21 Spring Undergraduate Research Festival Tu Feng (feng.1039@osu.edu) 11

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