Multi-valued Decision Diagram for Vehicle Configuration Space
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Solution Overview
Problem
The challenge lies in efficiently managing the complex configuration spaces of customizable products, such as vehicles, which often feature numerous optional categories, leading to a vast number of possible configurations that traditional systems struggle to handle effectively.
Innovation Solution
A method and system utilizing a multi-valued decision diagram (MDD) to represent the Boolean function specifying all possible configurations of a vehicle's features, allowing for efficient determination of feature states and availability mapping without violating constraints, implemented with a processor and memory to store and process this data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional systems are used to manage product configurations, then the system is simple to implement, but the system cannot efficiently handle complex configuration spaces with numerous optional categories
Solution Approach 1:
The patent segments the complex configuration space into hierarchical levels, where each level represents a feature category with multiple mutually exclusive options. This segmentation allows the system to manage complexity by breaking down the overall configuration problem into smaller, manageable sub-problems at each level, enabling efficient handling of products with numerous optional categories while maintaining system tractability
Solution Approach 2:
The patent introduces a new dimensional framework by organizing configurations across multiple hierarchical levels rather than treating all features as a flat space. This dimensional transformation from a single-level feature space to a multi-level hierarchical structure enables the system to efficiently navigate and constrain complex configuration spaces that would be intractable in traditional flat representations
2Loss of information
If all possible configurations are enumerated and stored, then complete configuration information is available, but memory usage becomes prohibitive with thousands of valid configurations
Solution Approach 1:
The patent merges multiple configuration paths that share common sub-configurations into a single shared representation. By combining common prefixes and suffixes across different configuration paths, the system stores each unique configuration segment only once, dramatically reducing memory requirements while preserving complete configuration information. This merging approach allows efficient representation of thousands of valid configurations without prohibitive memory usage
Solution Approach 2:
The patent implements a nested structure where configuration levels are organized hierically, with each level containing configurations that are nested within parent level configurations. This nesting allows the system to store configuration information in a compressed manner, where common parent configurations are stored once and child configurations reference them, reducing overall storage requirements while maintaining complete configuration data
3Reliability
If constraint validation is performed for each configuration, then configuration validity is ensured, but computational effort increases significantly in complex spaces
Solution Approach 1:
The patent performs preliminary constraint validation by pre-processing and storing constraint information in the hierarchical configuration structure. Constraints are incorporated during the construction of the configuration space representation, allowing the system to efficiently check validity during configuration exploration without performing computationally intensive validation for each possible configuration. This preliminary action ensures configuration validity while minimizing computational effort during runtime
Data Source
AI summary
A system is provided with memory and a processor. The memory is configured to store data representative of a multi-valued decision diagram (MDD). The processor is in communication with the memory and is programmed to receive a current selection of one or more of the features, and to determine a feature state for each of the one or more features, based on the current selection and the possible configurations defined by the MDD. The processor is further programmed to calculate an availability bitset indicative of which features as available for further selection, consistent with the valid configurations and without violating existing constraints of the current selection.