Implementing the ISO 15746 Standard for Chemical Process Optimization

Area of Science:

• Industrial Automation
• Process Engineering
• Data Modeling

Background:

• Current advanced process control (APC) and optimization (APC-O) solutions are often isolated, using diverse data formats and multiple modeling abstractions.
• This fragmentation makes integrating APC with optimization challenging, hindering efficient production processes.

Purpose of the Study:

• To propose and demonstrate a novel method for integrating APC and optimization (APC-O) solutions within factory settings.
• To leverage the International Organization for Standardization (ISO) 15746 data model to facilitate this integration.

Main Methods:

• Utilized the ISO 15746 data model to bridge the gap between APC and numerical optimization.
• Mapped inputs (goals from level 3, feedback from level 1) to a meta-model of a chemical process optimization problem (ISA-95 level 2).
• Serialized the meta-model population to provide input for numerical optimization code.

Main Results:

• Successfully demonstrated an automated, integrated process for solving a chemical process optimization problem.
• The ISO 15746 data model facilitated the unification of data from different levels (ISA-95 levels 1, 2, and 3).

Conclusions:

• The proposed integration method, utilizing ISO 15746, effectively overcomes the challenges of combining APC and optimization.
• This approach enables more efficient production processes through unified data modeling and automated optimization.