Integrating advanced process control solutions with optimization (APC-O) solutions, within any factory, enables more efficient production processes. Currently, vendors who provide the software applications that implement control solutions are isolated and relatively independent. Each such solution is designed to implement a specific task such as control, simulation, and optimization and only that task. It is not uncommon for vendors to use different mathematical formalisms and modeling tools that produce different data representations and formats. Moreover, instead of being modeled uniformly only once, the same knowledge is often modeled multiple times each time using a different, specialized abstraction. As a result, it is extremely difficult to integrate optimization with advanced process control. We believe that a recent standard, ISO 15746, describes a data model that can facilitate that integration. In this paper, we demonstrate a novel method of integrating numerical optimization with advanced process control using ISO 15746. The demonstration is based on a chemical-process-optimization problem, which resides at level 2 of the ISA95 architecture. The inputs to that optimization problem, which are captured in the ISO 15746 data model, come in two forms: goals from level 3 and feedback from level 1. We map these inputs, using this data model, to a population of a meta-model of the optimization problem for a chemical process. Serialization of the metamodel population provides input to a numerical optimization code of the optimization problem. The results of this integrated process, which is automated, provide the solution to the originally selected, level 2 optimization problem.
Proceedings of the ASME 2016 Manufacturing Science and Engineering Conference (MSEC2016)
June 27, 0016-July 1, 2016
The ASME 2016 Manufacturing Science and Engineering Conference (MSEC2016)
Standard, Integration, Optimization, Chemical Process