Webinar
on
Identifying
robust operational spaces for flexible process flow diagram design and
optimisation
Sam
Kay, University of Manchester
27th
March 2025 at 3pm (UK time)
Process optimisation and quality control are crucial
in process industries for minimising product waste and improving plant
economics. Identifying robust operational regions that ensure both product
quality and performance is particularly valued in industries. However, this
task is complicated by operational uncertainties, which can lead to violations
of product quality constraints and significant batch discards. Addressing these
uncertainties is essential for maintaining process stability and maximising profitability,
as uncontrolled variability introduces stochastic elements into product quality
that can result in large-scale wastage. We propose a novel robust optimisation
strategy that integrates advanced machine learning and process systems
engineering to systematically identify optimal operational regions under
uncertainty.
Our approach begins by using a process model to screen
a broad operational space across various uncertainty scenarios, pinpointing
promising control trajectories to satisfy process constraints and product
quality. Machine learning is then employed to cluster these trajectories into
sub-regions. Finally, a two-layer dynamic optimisation framework is employed to
determine the optimal control trajectory and corresponding operable space
within each promising sub-region. To demonstrate the efficiency of our approach,
we used a case study focusing on the quality control of a dynamic batch process
for formulation product manufacturing, accounting for generic industrial
uncertainties such as feedstock variation, control disturbances, and operator
human errors. The resulting operational regions were shown to meet product
quality demands and offer a significant improvement in optimality over the
current operation, highlighting the advantage and industrial potential of our
strategy.
This webinar will take no longer than one hour.
Please register
at: https://universityofstrathclyde.webex.com/weblink/register/r96ec633238c6c6c5d11d82c1a8026d9a
