Data Science in Metal Forming provides readers with a framework to collect, visualize, analyze, and characterize metal forming metadata, thus enabling improved design, more efficient production, and more effective application of a range of metals. Chapters introduce concepts and discuss industry 4.0, digital manufacturing, and more. Other sections feature case studies of metal forming data collection spanning several essential procedures and outline methods for data processing when lacking essential information.
The book also includes data visualization techniques, insights into how to analyze data from various metal forming processes (stamping, hydroforming, incremental, extrusion, and more) and details on how readers can setup, manage, and most effectively apply their own data repositories.
1. 1. Introduction to data science in metal forming - p. 1 2. 2. Review of advanced metal forming technologies - p. 11 3. 3. Metal forming data - p. 87 4. 4. Data processing framework of information absent metal forming data - p. 133 5. 5. Digital characteristics of data science in metal forming - p. 185 6. 6. Developing and analyzing digital characteristics of metal forming processes - p. 207 7. 7. Digital characteristics space of manufacturing processes - p. 265 8. 8. Applications of data science in metal forming - p. 275 9. Index - p. 345
Data Science in Metal Forming provides readers with a framework to collect, visualize, analyze, and characterize metal forming metadata, thus enabling improved design, more efficient production, and more effective application of a range of metals. Chapters introduce concepts and discuss industry 4.0, digital manufacturing, and more. Other sections feature case studies of metal forming data collection spanning several essential procedures and outline methods for data processing when lacking essential information.
The book also includes data visualization techniques, insights into how to analyze data from various metal forming processes (stamping, hydroforming, incremental, extrusion, and more) and details on how readers can setup, manage, and most effectively apply their own data repositories.
1. 1. Introduction to data science in metal forming - p. 1 2. 2. Review of advanced metal forming technologies - p. 11 3. 3. Metal forming data - p. 87 4. 4. Data processing framework of information absent metal forming data - p. 133 5. 5. Digital characteristics of data science in metal forming - p. 185 6. 6. Developing and analyzing digital characteristics of metal forming processes - p. 207 7. 7. Digital characteristics space of manufacturing processes - p. 265 8. 8. Applications of data science in metal forming - p. 275 9. Index - p. 345
