Module Control Logic Reconstruction From Runtime State Transitions
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Solution Overview
Problem
Modular industrial plants face challenges in reverse engineering the control logic of modules, especially in older or third-party systems where control system descriptions are absent, necessitating a method to automatically generate engineering information for control system replacement.
Innovation Solution
A computer-implemented method for reverse engineering control logic involves obtaining module-related data, including runtime data, to infer equipment state transition conditions using a rule-based algorithm, enabling the reconstruction of control logic for modules like Process Equipment Assemblies (PEAs) in modular industrial plants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual reverse engineering of control logic is performed for older or third-party modules, then control system replacement can be achieved, but the process requires significant time and expert knowledge, reducing productivity
Solution Approach 1:
The patent replaces manual mechanical analysis methods with automated computational algorithms. The system uses machine learning models and automated data processing to analyze runtime data, tag databases, and process information, substituting human expert manual reverse engineering with automated electronic systems that can process information faster and more consistently.
Solution Approach 2:
The patent creates digital copies and representations of the control logic by analyzing runtime data and reconstructing the control system behavior. The system generates virtual models, state transition diagrams, and logic representations that replicate the original control system's functionality without requiring physical access to the original control hardware or source code.
2Measurement precision
If comprehensive runtime data collection is performed to accurately infer equipment state transitions, then control logic accuracy improves, but data processing complexity and computational resources increase
Solution Approach 1:
The patent segments the control logic reverse engineering process into distinct analytical components: equipment state identification, transition detection, condition inference, and model generation. Each segment processes specific aspects of the runtime data independently, allowing the system to manage complexity by breaking down the overall task into smaller, more manageable analysis modules that can be executed sequentially or in parallel.
3Loss of information
If detailed module-related data including tags and runtime information is collected, then complete control logic reconstruction is possible, but information management and processing burden increases
Solution Approach 1:
The patent creates a universal data processing framework that handles multiple types of module-related data (runtime data, tag databases, process information, configuration files) through a single integrated system. The automated analysis engine can process diverse data formats and sources using common processing routines, reducing the need for separate management systems for each data type and simplifying overall information management.
Data Source
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AI summary
There is provided a computer-implemented method for reverse engineering control logic of a module (110) for a modular industrial plant (100). The method comprises: obtaining module-related data including runtime data (210) relating to prior use of the module during a timeperiod in which at least one piece of equipment of the module transitions from a first equipment state to a second equipment state, the runtime data including tags indicating the equipment state of the equipment at a plurality of timepoints during the timeperiod; and inferring (203, 204) from the module-related data one or more equipment state transition conditions causing the equipment to transition from the first equipment state to the second equipment state.