Accurate modeling can offer valuable insight into understanding the intricacies and trade-offs involved in a process plant. Using consistent models throughout the process plant's lifecycle from design and operation, through optimization and production planning, to training, revamp, and retrofit can result in improved decision making and enterprise operations management. The Open Object Model Framework (OOMF) has enabled users of our software solutions to make significant progress towards achieving this goal.

OOMF is a core component of design, simulation, and real time optimization solutions for the chemicals, petrochemicals, and refining industries. It serves as a crucial part of production planning, economic optimization and multi-blend optimization solutions for refineries. Furthermore, it facilitates data reconciliation and yield accounting solutions for process plants as well as comprehensive modeling and synthesis solutions for improved process water usage. Each of these software solutions has a specialized user interface and business logic that is specific to its domain. A common requirement of all of these domains is the need to analyze and make decisions via the use of process and plant models. In the past, completely separate model solution engines were used in these software solutions. Recently, the incorporation of OOMF as a common model solution framework into these engines has allowed re-use of the underlying models, thereby providing a level of consistency among the solutions.

This paper describes the state-of-the-art Open Object Model Framework that facilitates the representation, assembly, and solution of a range of large scale numerical optimization problems. OOMF provides a platform for development of open-form equation oriented steady state and dynamic models. Sophisticated model instantiation and restructuring algorithms enable the use of a model with fidelity appropriate for the current task. Advanced specification management tools allow the same model to be used for different applications such as process simulation, parameter estimation, reconciliation, and optimization. Custom designed connection managers facilitate the construction of process flowsheets that may include hierarchical networks of connected models. Replication tools facilitate the cloning of these hierarchical network models. These replication tools along with the ability to create complex objective functions enable data reconciliation and multi-period modeling. Structural and numerical analysis tools help in diagnosing problems with the model and the process. An interface to a library of math solvers enables the use of a solver that is appropriate for the current task. This library of math solvers includes proprietary and third party solvers. OOMF is a standalone software component that can be integrated into software applications. This component has reduced product development costs and project risks through the re-use of a proven solution technology.

The types of models that can be constructed and solved using OOMF include linear, non-linear and mixed integer programs that can include differential algebraic constraints. This versatility along with its range of available tools has resulted in OOMF being embedded and used in numerous software solutions. Effectively, OOMF is the basis of the unification of these different modeling domains through its common idiom of mathematical programming and abstract interfaces to models and solvers that are shared between these applications.

The paper provides details of how complex real time optimization and planning problems that arise in the process industries have been formulated and solved through the use of software solutions that embed OOMF.