| About this Abstract |
| Meeting |
2022 TMS Annual Meeting & Exhibition
|
| Symposium
|
REWAS 2022: Automation and Digitalization for Advanced Manufacturing
|
| Presentation Title |
AI/Data Mining in Materials Manufacturing |
| Author(s) |
Elsa Olivetti |
| On-Site Speaker (Planned) |
Elsa Olivetti |
| Abstract Scope |
Presently commercialized technologies, silicon photovoltaics and lithium-ion batteries, have required decades to reach even modest levels of global adoption. One among many factors contributing to this protracted transition to large scale manufacturing is that the processes and equipment used in lab diverge from those which are available or required at production scales. When novel materials or devices proceed from the laboratory to manufacturing, unforeseen and unfamiliar processing challenges can easily arise. Fundamental scientific and design problems that could be solved during early-stage research with comparatively little time and expense must instead be addressed during scale up, compelling the use of significantly more capital at a time when such delays are ill-afforded and in an industry in which low-cost incumbents drive perilously thin margins for new entrants. This presentation will focus on data-driven insight and tools for early research to design new technologies explicitly for manufacturing and scale up from inception. |
| Proceedings Inclusion? |
Planned: |