Plant Builder System Iterative P&ID Simulation
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Solution Overview
Problem
The existing plant design process is redundant, time-consuming, and error-prone, often resulting in flawed designs due to the lack of iterative testing of physical layouts and control strategies before construction, making redesigns costly and inefficient.
Innovation Solution
A plant builder system that enables the design and simulation of process and instrumentation diagrams (P&IDs) and control strategies before construction, allowing for the creation of equipment objects with simulation functionality, facilitating iterative design and optimization of plant layouts and control systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual plant design procedures are used, then the design process is straightforward and simple to execute, but the process becomes redundant, time-consuming, and error-prone due to lack of iterative testing
Solution Approach 1:
The system performs preliminary design actions by automatically generating equipment objects, I/O elements, and control configurations from P&ID diagrams before actual plant construction. This preliminary configuration allows designers to test and validate designs virtually, eliminating redundant manual steps while maintaining accuracy through automated rule-based generation.
Solution Approach 2:
The system creates virtual copies of physical equipment through equipment objects that replicate the behavior and characteristics of actual plant components. These digital twins allow iterative testing and validation of control strategies without physical prototypes, significantly reducing design time while improving reliability through comprehensive virtual testing.
2Reliability
If iterative testing of design scenarios is implemented, then design accuracy and optimization improve, but the complexity of the design process increases
Solution Approach 1:
The system performs self-service by automatically generating equipment objects, I/O elements, and control configurations from P&ID diagrams using rule-based logic. This automation eliminates the need for manual configuration of each component, allowing iterative testing to proceed without proportionally increasing design process complexity. The system serves itself by validating designs against predefined rules and standards.
Solution Approach 2:
The system enables parameter changes by allowing designers to modify equipment specifications, control strategies, and operational parameters within the virtual model. These parameter changes can be tested iteratively without physical reconfiguration, improving design accuracy while the automated system manages the complexity of tracking and validating multiple parameter variations.
3Adaptability or versatility
If comprehensive equipment objects with simulation functionality are created, then control strategy optimization improves, but the time required for design configuration increases
Solution Approach 1:
The system performs preliminary configuration by automatically generating comprehensive equipment objects with embedded simulation functionality before control strategy development. This preliminary setup includes defining I/O elements, communication protocols, and equipment characteristics, which reduces the time required for subsequent control strategy optimization while maintaining full adaptability.
Solution Approach 2:
The equipment objects are designed with multi-functionality, serving as both design documentation artifacts and simulation models. Each equipment object encapsulates physical characteristics, control interfaces, and simulation behavior, allowing the same object to be used for design review, control strategy development, and performance simulation, thereby reducing overall configuration time.
Data Source
AI summary
The described methods and systems enable iterative plant design. These methods and systems may be utilized to test multiple P&ID designs and control strategies before a plant is constructed, enabling engineers to test physical layouts and control strategies for the particular unit, facilitating optimal design of the plant and control scheme for controlling the process. The described methods and system thus facilitate optimal design of optimal physical layouts and control strategies.