About this Research Topic
Manufacturing is currently undergoing a revolution driven by a confluence of forces including automation, the democratization of AI/ML technologies, and the ubiquity of Big Data technologies for handling the volume, velocity, and variety of data generated and used throughout modern manufacturing processes. Both additive and subtractive manufacturing have benefited greatly from this confluence of technological innovation. The focus of this Research Topic is on the modern data stack, and in particular, the development and application of Big Data technologies, applied to both forms of manufacturing.
According to recent studies, multiple market studies forecast the additive manufacturing market to grow from roughly $10B today to $50B to $75B by 2030 as the technology becomes more robust, especially in the metal additive space across modalities such as laser powder bed fusion, directed energy deposition, and binder jetting. This growth is largely being driven by the desire to reduce manufacturing waste, increase product efficiency, and improve product customizability, especially in the biomedical/healthcare and aerospace industries, to name a few driving forces.
While additive manufacturing is experiencing substantial growth, subtractive manufacturing continues to be a major contributor to manufacturing across most industries, as well. The modernization of subtractive manufacturing is equally important and therefore, in parallel, there have been similar efforts over the last few decades to optimize subtractive manufacturing processes through the application of Big Data technologies as well.
This Research Topic welcomes new submissions that present novel and interesting experiences, learnings, and applications in the areas of Big Data for additive and subtractive manufacturing.
Principal topics of interest include:
• Managing data velocity, volume, and/or variety in a manufacturing context
• Federated data management for manufacturing
• Digital Twins of manufacturing processes
• Data fusion - integrating pre-processing, processing, post-processing, and/or inspection data
• Real-time processing of manufacturing high-throughput data streams
• Data platforms in support of AI/ML for manufacturing
• Data exchange and interoperability for FAIR data in manufacturing
Industrial applications in:
• Autonomous manufacturing process design & development
• Data-driven manufacturing process modeling and simulation
• Manufacturing process optimization, e.g.,
o Real-time process monitoring
o Postprocessing
o Inspection
o Quality control
According to recent studies, multiple market studies forecast the additive manufacturing market to grow from roughly $10B today to $50B to $75B by 2030 as the technology becomes more robust, especially in the metal additive space across modalities such as laser powder bed fusion, directed energy deposition, and binder jetting. This growth is largely being driven by the desire to reduce manufacturing waste, increase product efficiency, and improve product customizability, especially in the biomedical/healthcare and aerospace industries, to name a few driving forces.
While additive manufacturing is experiencing substantial growth, subtractive manufacturing continues to be a major contributor to manufacturing across most industries, as well. The modernization of subtractive manufacturing is equally important and therefore, in parallel, there have been similar efforts over the last few decades to optimize subtractive manufacturing processes through the application of Big Data technologies as well.
This Research Topic welcomes new submissions that present novel and interesting experiences, learnings, and applications in the areas of Big Data for additive and subtractive manufacturing.
Principal topics of interest include:
• Managing data velocity, volume, and/or variety in a manufacturing context
• Federated data management for manufacturing
• Digital Twins of manufacturing processes
• Data fusion - integrating pre-processing, processing, post-processing, and/or inspection data
• Real-time processing of manufacturing high-throughput data streams
• Data platforms in support of AI/ML for manufacturing
• Data exchange and interoperability for FAIR data in manufacturing
Industrial applications in:
• Autonomous manufacturing process design & development
• Data-driven manufacturing process modeling and simulation
• Manufacturing process optimization, e.g.,
o Real-time process monitoring
o Postprocessing
o Inspection
o Quality control
Keywords: Big data, additive manufacturing, autonomous materials, data-drive materials
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
