Industrial Plant Reference Model Using Unit-Operation Hyperstructure
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Solution Overview
Problem
Conventional data models are inadequate in efficiently representing and managing the complex relationships between physical and procedural domains in industrial plants, hindering effective planning and management in manufacturing execution systems (MESs).
Innovation Solution
A reference model and system that project a cross-product of physical and procedural models into a unit-operation association set using a projection matrix, establishing internal and external adjacency sets to generate a hyperstructure representing the industrial plant, thereby combining structural and behavioral aspects for optimized production planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional data models are used to represent physical and procedural domains, then the model structure is simple and easy to implement, but the model cannot efficiently represent or handle the complex relationships between multiple variables and process elements
Solution Approach 1:
The patent segments the industrial plant model into distinct physical domain elements (equipment, units) and procedural domain elements (operations, processes), allowing each to be represented independently while maintaining their relationships through structured data models. This segmentation enables efficient handling of complex relationships without requiring a monolithic complex structure.
Solution Approach 2:
The patent introduces a dual-domain dimensional structure by creating separate physical and procedural domain spaces, then establishing relationships between them through association matrices. This dimensional approach allows the model to represent complex cross-domain relationships efficiently without increasing intra-domain complexity.
2Loss of information
If multiple variables and process elements are integrated in both physical and procedural domains, then the model comprehensiveness improves, but the efficiency of representing and handling relationships deteriorates
Solution Approach 1:
The patent extracts relationships between physical and procedural elements into separate association structures (unit-operation association sets, adjacency sets). This extraction allows comprehensive representation of all relationships without embedding them directly in the core domain models, thereby maintaining modeling efficiency while preserving information completeness.
Solution Approach 2:
The patent introduces intermediate data structures (projection matrices, association sets) that mediate between the physical and procedural domains. These intermediaries efficiently manage the complex relationships between multiple variables and process elements without requiring direct integration of all elements, thus maintaining both comprehensiveness and efficiency.
3Ease of operation
If a unified model structure is used for both physical and procedural domains, then implementation is simpler, but the model cannot effectively distinguish and manage domain-specific characteristics
Solution Approach 1:
The patent creates a universal framework with common data structures (units, operations, associations) that can represent both physical and procedural domains. This universal structure maintains ease of implementation through consistent syntax and semantics while accommodating domain-specific characteristics through specialized attributes and relationships for each domain type.
Data Source
AI summary
Systems and methods that include selecting a physical model and a procedural model associated with an industrial plant, projecting a cross-product of the physical model and the procedural model into a unit-operation association set using a projection matrix, the unit-operation association set associating units representing equipment in the industrial plant and operations representing processes performed in the industrial plant, and establishing internal and external adjacency sets within structures, the internal adjacency set identifying connections between inputs and outputs of individual units and operations, the external adjacency set identifying connections between outputs of some units and operation and inputs of other units and operations. These systems and methods may also include generating a hyperstructure representing the industrial plant using the association and adjacency sets.