AI Design Platform with Regulation Assistant for Compliance
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Solution Overview
Problem
Current design processes are inefficient and resource-intensive, requiring numerous iterations and lacking tools to reduce the number of iterations and increase efficiency, particularly in capturing appealing designs for products like aircraft interiors, which must comply with regulatory requirements.
Innovation Solution
An AI-based design platform that includes a suite of AI-driven design assistants such as a design generation assistant, trendspotting assistant, design optimization assistant, design visualization assistant, digital twin management assistant, and regulation assistant, utilizing deep learning models and natural language processing to streamline the design process, generate designs, and ensure compliance with regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional iterative design process is used to capture appealing designs, then design quality can be improved, but resource consumption and time required increase significantly
Solution Approach 1:
The system performs preliminary actions by automatically generating multiple design variations and evaluating them against regulatory requirements before the designer commits to a final design. The design generation assistant creates candidate designs in advance, and the regulation assistant pre-evaluates compliance, reducing the need for repeated iterative cycles later in the process.
Solution Approach 2:
The system implements continuous feedback loops where the regulation assistant automatically evaluates design candidates against regulatory requirements and provides immediate feedback to the design generation assistant. This allows real-time adjustment of design parameters to ensure compliance, eliminating the need for time-consuming post-design regulatory checks.
2Manufacturing precision
If multiple design iterations are performed to achieve appealing designs, then design quality improves, but processor and memory resources are significantly consumed
Solution Approach 1:
The system applies partial action by generating and evaluating only the most promising design candidates rather than exhaustively exploring all possible designs. The design generation assistant uses regulatory constraints to prune the search space, focusing computational resources on viable options and avoiding wasted processing on non-compliant designs.
Solution Approach 2:
The system changes parameters by automatically adjusting design variables based on regulatory requirements and evaluation feedback. The design generation assistant modifies design parameters programmatically rather than requiring manual redesign iterations, reducing the computational overhead associated with repeated full-design regenerations.
3Reliability
If manual regulatory compliance checking is performed during design iterations, then regulatory compliance can be ensured, but design productivity decreases
Solution Approach 1:
The system implements self-service by enabling the regulation assistant to automatically check compliance without human intervention. The regulation assistant independently evaluates design candidates against regulatory requirements, extracts relevant information from regulatory documents, and provides compliance assessments, freeing the designer from manual compliance checking tasks.
Solution Approach 2:
The system replaces manual mechanical processes with automated computational processes. Instead of designers manually reviewing regulatory documents and checking compliance (a mechanical human process), the regulation assistant uses natural language processing and automated reasoning to perform compliance checking, significantly increasing speed and consistency.
4Reliability
If comprehensive regulatory documents are processed to ensure compliance, then regulatory compliance improves, but system complexity increases
Solution Approach 1:
The system extracts only the relevant regulatory information needed for compliance checking rather than processing entire regulatory documents. The regulation assistant uses natural language processing to identify and extract specific clauses, requirements, and parameters applicable to the current design, filtering out unnecessary information and reducing processing complexity.
Solution Approach 2:
The system applies local quality by tailoring the regulatory checking process to the specific design domain and requirements. Different design types receive customized compliance checks based on their specific regulatory contexts, rather than applying a uniform complex checking process to all designs. The system adapts its analysis depth and scope to match the local needs of each design scenario.
Data Source
AI summary
Implementations of the present disclosure include generating, by a design generation assistant, a design image representing a design subject, the design subject having one or more regulations applicable thereto, querying, by a regulation assistant, an answer extractor to provide a query result based on a query, the answer extractor including at least one deep learning model that processes the query to provide the query result, the query being descriptive of at least a portion of the design subject, the query result being representative of at least one regulation applicable to the design subject, and displaying, within a graphical user interface (GUI), the query result.