Systems Engineering Approaches for Scalable Plastic Waste Management


Wednesday, November 29, 2023 - 9:00am


Engr II 1519


Associate Professor Victor M. Zavala - University of Wisconsin-Madison

Abstract: Plastics are essential materials in modern life, but it is no secret that they generate a wide range of environmental problems. In this talk, we discuss how systems engineering tools can help identify scalable recycling/upcycling strategies for handling plastic waste. Specifically, we show how systems engineering can help integrate molecular simulations, computational catalysis, techno-economic analysis, lifecycle assessment, and supply chain optimization to identify processes (and entire infrastructures) that can convert vast, distributed, and complex plastic waste streams (e.g., post-consumer mixtures and multi-layer films) into value-added products. We also discuss how such integrative frameworks can help design plastic materials/products that are inherently more sustainable and can help design incentives/policies that aim to change consumer and industry behavior. Our discussion will aim to emphasize how "systems thinking” is essential for addressing pressing sustainability problems, as such problems integrate products, technologies, supply chains, and stakeholders at a global scale. 

Bio: Victor M. Zavala is the Baldovin-DaPra Professor in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison and a senior computational mathematician in the Mathematics and Computer Science Division at Argonne National Laboratory. He holds a B.Sc. degree from Universidad Iberoamericana and a Ph.D. degree from Carnegie Mellon University, both in chemical engineering. He is on the editorial board of the Journal of Process Control, Mathematical Programming Computation, and Computers and Chemical Engineering. He is a recipient of NSF and DOE Early Career awards and of the Presidential Early Career Award for Scientists and Engineers. His research interests include computational modeling, statistics, control, and optimization. 

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