Applied Artificial Intelligence, Big Data, and Data Analytics Methods for Next-Gen Manufacturing Efficiency II | AIChE

Applied Artificial Intelligence, Big Data, and Data Analytics Methods for Next-Gen Manufacturing Efficiency II

Chair(s)

Paulson, J., The Ohio State University

Co-chair(s)

Bavarian, M., University of Nebraska-Lincoln
Arabi Shamsabadi, A., Drexel University

With increasing competition and technologies that can be needed worldwide in a short timeframe in areas such as pharmaceuticals, techniques for decreasing the time in taking a concept through development all the way to manufacturing and market are required. This session will focus on methods for moving toward shorter timeframes between concept development and manufacturing, including discussion of automation and artificial intelligence or data analytics in facilitating such approaches. Rapid acquisition, optimization of design and processing, and distribution of products are also topics within scope. Submissions from industry and national labs are welcome to facilitate discussion at the industry/national lab/academic interface. Discussion of challenges posed by policy and other practical considerations in ultra-rapid concept-to-manufacturing strategies, as well as methods for overcoming barriers, are also of interest.

Presentations

Topics 

Checkout

Paper abstracts are public but to access Extended Abstracts, you must first purchase the conference proceedings.

Checkout

Do you already own this?

Pricing

Individuals

AIChE Pro Members $150.00
AIChE Emeritus Members $105.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
AIChE Explorer Members $225.00
Non-Members $225.00