Aircraft Assembly System Using Description Logics
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Solution Overview
Problem
The aircraft assembly process is complex and inefficient, requiring flexible management of customer-specific design and configuration data, time constraints, resource availability, and unexpected events, which existing systems struggle to optimize effectively.
Innovation Solution
An aircraft assembly system comprising an input module, database, and processing unit that generates manufacturing plans using description logics and ontologies, allowing for automatic variation of input parameters and design data to optimize assembly time and costs, while prioritizing rules and performing error checks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual aircraft assembly planning is used to accommodate customer-specific design data, then flexibility in meeting customer requirements is improved, but assembly time and costs increase due to complex manual optimization
Solution Approach 1:
The patent replaces manual mechanical planning processes with an automated computer-based system that uses description logics and ontologies to generate optimized manufacturing plans. The processing unit automatically processes customer-specific design data and generates assembly plans without manual intervention, eliminating the time-consuming nature of manual planning while maintaining flexibility through programmable rule-based optimization.
Solution Approach 2:
The system enables self-service by allowing the automated processing unit to independently optimize manufacturing plans based on input parameters and pre-defined rules. The system automatically adjusts assembly sequences, resource allocation, and scheduling without requiring continuous human intervention, thereby reducing assembly time while adapting to customer requirements through automated rule-based decision-making.
2Adaptability or versatility
If manual aircraft assembly planning is used to handle complex design data, then adaptability to design changes is improved, but manufacturing costs increase due to intensive manual optimization processes
Solution Approach 1:
The patent replaces costly manual optimization processes with an automated computer-based system that uses description logics and ontologies. The processing unit automatically generates optimized manufacturing plans based on customer-specific design data, eliminating the need for expensive manual intervention while maintaining full adaptability to design changes through programmable rule-based optimization.
Solution Approach 2:
The system uses ontologies and description logics to create reusable knowledge models that can be copied and applied across different manufacturing scenarios. These standardized knowledge representations allow the system to rapidly adapt to design changes by reusing existing optimization patterns and rules, reducing the need for costly custom manual optimization for each new design configuration.
3Productivity
If automated systems are used to reduce assembly time, then productivity is improved, but flexibility in handling customer-specific configurations decreases
Solution Approach 1:
The patent implements a dynamic system where the processing unit automatically adjusts manufacturing plans based on input parameters and pre-defined optimization rules. The system dynamically processes customer-specific design data and generates customized assembly sequences, maintaining both high productivity through automation and full flexibility in handling various configurations through programmable adaptability.
Solution Approach 2:
The system handles customer-specific configurations by changing parameters within the automated optimization process. The processing unit accepts input parameters representing customer requirements and automatically adjusts assembly plans by varying sequencing, resource allocation, and scheduling parameters while maintaining optimized productivity through rule-based decision-making.
4Manufacturing precision
If comprehensive rule sets are used to optimize manufacturing plans, then manufacturing precision is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex optimization problem into manageable components using description logics and ontologies. The system divides the manufacturing plan generation into distinct logical layers: ontology-based knowledge representation, rule-based optimization constraints, and sequential planning algorithms. This segmentation maintains high optimization accuracy while reducing perceived system complexity through modular, hierarchical organization.
Solution Approach 2:
The patent introduces ontologies and description logics as intermediary layers between raw customer data and the optimization engine. These intermediaries structure and standardize input information, enabling the processing unit to apply comprehensive optimization rules systematically. The intermediaries simplify the interface between complex rule sets and user inputs, maintaining precision while managing system complexity through standardized knowledge representation.
Data Source
AI summary
An aircraft assembly system as described herein includes an input module, a database, and a processing unit. The input module is adapted for inputting customer-specific data and, in particular, parameters which relate to the expected time of delivery, the number of personnel working in the aircraft assembly system or an apparatus of the system which cannot be used. By applying description logics, the processing unit generates a manufacturing plan in accordance with a set of rules and the input parameters. In order to improve the manufacturing plan, input parameters may be changed by the system in an iterative process. This may provide for an efficient use of resources available.