Blanket Wash Solvent Blend Design Using Interval Analysis

Abstract

The search for new solvents is driven by the needs of new applications, new processing requirements, changing environmental regulations, and market demands. Many cleaning solvents used in the lithographic printing industry are on the environmental “hit list” and are to be phased out within the next few years. This paper discusses the systematic design of cleaning solvent blends for lithographic printing (commonly referred to as blanket washes). The design problem consists of a discrete problem involving selection of solvents from a set of pure-component solvents and a continuous problem of finding the blend composition. The simultaneous consideration of associated process constraints, property requirements, and environmental restrictions makes blanket wash design a rather difficult problem. To address this issue, we present a framework for designing cleaning solvent blends that meet thermophysical property requirements and environmental restrictions. The solvent design model is solved using interval analysis.

Review of Mixed‐Integer Nonlinear and Generalized Disjunctive Programming Methods

“…Some of them include design of solvents [275,277,[283][284][285][286][287][288][289], refrigerants [278,279,[290][291][292], polymers [293][294][295][296][297], and pharmaceutical products [298,299].…”

Global optimization in the 21st century: Advances and challenges

“…Ostrovsky, Achenie, and Sinha (2003) revisited their molecular design reduced dimension branch-and-bound algorithm by studying further the branching functions concept and the special tree function representation, proposed the sweep method for the construction of the linear underestimators, investigated the problem size dependency on the algorithmic performance, and showed that the computational effort increases almost linearly. Sinha, Achenie, and Gani (2003) studied the systematic design of cleaning solvent blends for lithographic printing, modelled it as a nonconvex MINLP problem, introduced an interval analysis based global optimization approach with modifications on the upper bounding calculation and the local feasibility test which are solved via SQP, and an interval-based domain reduction algorithm, and presented computational results for the design of aqueous blanket wash blends. Zhu and Kuno (2003) proposed a hybrid global optimization method for nonconvex MINLPs which combines convex quadratic underestimation techniques with a revised form of the generalized Benders decomposition, suggested its convergence properties, and illustrated it via a two variable problem.…”

The formulation of optimal mixtures with generalized disjunctive programming: A solvent design case study

“…An interval-analysis based optimization framework was developed by Sinha et al 38,39 to solve such problems. In their study, an eight-step interval-based domain reduction algorithm, LIBRA, was developed and used successfully to identify the globally optimal binary mixture in the design of environmentally acceptable blanket wash solvent blend.…”

“…Most existing methodologies are applicable to binary mixtures only, 1,2,4,10,11,33,[38][39][40] with the exception of the work of Klein et al 41 and Yunus et al 34 Furthermore, in many methods 1,2,10,34,38,41 the space of possible components is restricted. In some cases, all components that participate in a mixture are selected from a given set of molecules, while in others, one of the mixture ingredients is defined a priori, and the other compounds (usually one compound) are designed or selected from a set.…”

“…Most existing methodologies are applicable to binary mixtures only, 1,2,4,10,11,33,[38][39][40] with the exception of the work of Klein et al 41 and Yunus et al…”