TITLE:
Robust Multi-Objective Optimization of Chromatographic Rare Earth Element Separation
AUTHORS:
Hans-Kristian Knutson, Anders Holmqvist, Niklas Andersson, Bernt Nilsson
KEYWORDS:
Rare Earth Elements, Chromatography, Multi-Objective Optimization, Robust Optimization
JOURNAL NAME:
Advances in Chemical Engineering and Science,
Vol.7 No.4,
October
31,
2017
ABSTRACT: Rare earth elements are strategic commodities in many countries, and an important
resource for the growing modern technology industry. As such, there is
an increasing interest for development of rare earth element processing, and
this work is a part of further development of chromatography as a rare earth
element separation process method. Process optimization is pivotal for process
development, and it is common that several competing objectives must be regarded.
Chromatographic separation processes often consider competing objectives,
such as productivity, yield, pool concentration and modifier consumption,
which leads to Pareto optimal solutions. Adding robustness to a process is of
great importance to account for process disturbances and uncertainties but
generally comes with reduced performance of the other process objectives as a
trade off. In this study, a model-based robust multi-objective optimization was
carried out for batch-wise chromatographic separation of the rare earth elements
samarium, europium and gadolinium, which was considered highly
un-robust due to the neighbouring peaks proximity to the product pooling
horizon. The results from the robust optimization were used to chart the required
operation point changes for keeping the amount of failed batches at an
acceptable level when a certain level of process disturbance was introduced. The
loss of process performance due to the gained robustness was found to be in the
range of 10% - 20% reduced productivity when comparing the robust and
un-robust Pareto solutions at Pareto points with identical yield. The methodology
presented shows how to increase robustness to a highly un-robust system
while still keeping multiple objectives at their optima.