Intention Modeling for Process Plant Engineering Decisions
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Solution Overview
Problem
Current methods in process plant engineering lack transparent and structured representation of goals, intentions, and requirements, leading to conflicts between stakeholders and inefficient decision-making, especially during the early phases of engineering where multiple disciplines are involved.
Innovation Solution
A method using an assistance system to formulate and model intentions in a controlled natural language, transforming them into a graphical representation that hierarchically structures goals, implementations, and requirements, allowing for discipline-independent understanding and validation across different phases of engineering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If current means of description (flowsheets or textual description) are used, then the solution (how) is provided, but the underlying goals and intentions (what and why) are not clearly represented
Solution Approach 1:
The patent segments the description of engineering decisions into distinct components: goals, intentions, requirements, and solutions. This segmentation allows each element to be explicitly represented and linked, preventing the loss of goals and intentions information while maintaining clarity through structured organization rather than complex unstructured text.
Solution Approach 2:
The patent introduces a new dimensional structure by adding hierarchical levels (goals → intentions → requirements → solutions) to the traditional linear description. This dimensional expansion enables simultaneous representation of both the solution and the underlying goals/intentions, resolving the contradiction between information completeness and description complexity.
2Adaptability or versatility
If decisions are made by different people in the engineering workflow, then various requirements and objectives can be addressed, but it becomes difficult to review requirements and objectives across all levels
Solution Approach 1:
The patent implements feedback mechanisms where each decision is traced back to its underlying goals and intentions, and where changes in lower levels (solutions, requirements) automatically trigger reviews of higher levels (intentions, goals). This feedback loop ensures that causal dependencies are maintained and visible across all decision-making levels, preventing information loss despite multiple stakeholders involved.
3Reliability
If solution validation and quality checking are made by hand, then informal requirements can be checked against solutions, but the process is inefficient and error-prone
Solution Approach 1:
The patent enables the system to validate requirements against solutions automatically through the structured intention model. The formal relationships defined in the model allow the system to self-validate consistency, completeness, and achievability of intentions, eliminating the need for manual checking while maintaining high reliability. This self-service capability dramatically improves productivity without sacrificing validation quality.
Data Source
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AI summary
The invention relates to a method for formulation and modelling of intentions in process plant engineering, comprising the steps: formulating (S10), by an assistance system (100), intentions of an actor (A1, A2) by guiding the actor (A1, A2) to provide the intentions (I) to the assistance system (100) in a controlled natural language using semi-formal phrases (P), wherein the intentions (I) are hierarchically structured and comprises at least a goal (IG), describing a goal to be achieved, at least an implementation (II), describing how the goal can be achieved, and at least an requirement (IR), describing requirements for the at least one implementation (II); translating (S20), by the assistance system (100), the intentions (I) into an intention model (MI) wherein the intention model (MI) describes a relationship between the intentions (I); transforming (S30), by the assistance system (100), the intention model (MI) into a graphical representation (RG) of the intention model (MI) and providing the graphical representation (RG) to the actor (A1, A2); modeling (S40), by the assistance system (100), the intention model (MI) using modelling data (DM) provided by the actor (A1, A2), wherein the graphical representation (RG) allows the actor (A1, A2) to provide the modelling data (DM) to the assistance system (100).