(521a) Multiobjective Optimization of Multipurpose Batch Plants Using Superequipment Class Concept

Andrej Mošat`, Laurent Cavin, Ulrich Fischer,
Konrad Hungerbühler

Chemical batch plant processing is currently undergoing massive
changes in the aims, structure and systematics of production
design. As a consequence shorter time-to-market times and faster design planning
are required. Industry-driven project in multipurpose batch plant optimization
has been established to improve competitive advantages for a company.
In this paper we tackle the problems of selecting
one appropriate plant line out of many available, additional investment
into an existing plant and grassroot design.

We focus on the optimization of process design engineering. In
predesign stage, computer aided multiobjective optimization
tool, developed by our research group, helps in the
decision-making. An implementation of the Tabu Search
algorithm drives the set of software tools and provides a compilation of results.

Superequipment vessel has been defined
as an abstract model which is capable of performing any
chemicophysical batch operation. The model vessel is transformed
into a real equipment unit (for example a reactor) during or after
the optimization in order to evaluate performance parameters of a
design.

The application of superequipment concept in a single product
campaign solves variety of problems:

• Investment into an existing plant using
  our superequipment concept saves considerable efforts and time by
  applying optimal combination of equipment units for given
  recipe.
• Selection of a single plant line from
  many production facilities for one campaign by help of
  superequipment concept delivers time saving possibility of reducing
  multiple optimization runs to one. Sorted list of proposed
  Pareto-optimal designs according to productivity and additional
  multiple objective functions in each of the plants is presented to
  the decision maker.
• Grass-root designs using limited number
  of superequipment vessels outputs a number of Pareto-optimal and
  performing designs according to the multiple criteria selection of
  the user.

The designs obtained by optimization correspond to the requirements of industry experts according to productivity, GMP heuristics, reality checks and more.
The superequipment ``chameleon'' vessel algorithm offers the possibility
to solve various batch processing problems with one concept.