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Cascade Analysis Technique for Targeting Property-Based Material Reuse/Recycle Network

Denny K. S. Ng1, Dominic Chwan Yee Foo1, Vasiliki Kazantzi2, and Mahmoud M. El-Halwagi3. (1) School of Chemical and Environmental Engineering, University of Nottingham Malaysia, Jalan Broga, Semenyih, Selangor, 43500, Malaysia, (2) Texas A&M University, Department of Chemical Engineering, College Station, TX 77843-3122, (3) Department of Chemical Engineering, Texas A&M University, Department of Chemical Engineering, College Station, TX 77843-3122

Efficient use of material resources is recognised as a key element of sustainable development and an effective strategy for cost reduction and environmental acceptability of the process industries. In the area of recycle/reuse, much work has been done to target minimum fresh usage and minimum waste discharge for particular material utilities (e.g., water, hydrogen, etc.). However, in many cases, recycle/reuse is dictated by sink constraints on properties of the recycled streams. In spite of the importance of the conventional mass integration techniques for material recycle/reuse, they are limited to problems that are governed by composition of chemical compounds. Composition is only one of the many chemical and physical properties that are essential in a chemical process. Other properties (or functionalities) that are commonly encountered include pH, density, viscosity, reflectivity, turbidity, colour and solubility, to name a few. Process network synthesis associated with these chemical properties is to be handled by the latest trend of process integration techniques, i.e. property integration.

In this work, a recently developed algebraic technique called the Property Cascade Analysis (PCA) technique is used to establish rigorous targets on the minimum usage of fresh resources and minimum waste discharge for property-based material reuse network. PCA eliminates the iterative steps typically associated with a graphical approach. Along with the minimum fresh and waste targets, the material allocation target is another key feature of the PCA. The procedures developed in this paper constitute a generalisation to the composition-based cascade analysis techniques developed for water and hydrogen networks. A water minimisation case study in a microelectronics manufacturing facility involving the property of reflectivity is solved to illustrate the applicability of the technique.