Configurable Order Object Model for Data Management
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Solution Overview
Problem
Current order document management systems are inflexible and inefficient, as they model orders as hard-configured data objects that require individual programming for each type of order, leading to lengthy data access and processing times.
Innovation Solution
A highly configurable order document data management system that represents orders as objects with core components and extensions, allowing for a hierarchical structure and modular configuration, enabling standardized processing and efficient data storage across multiple tables based on semantic properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If orders are modeled as hard-configured data objects with individual programming for each type, then each order type can be precisely handled, but the system becomes inflexible and requires extensive programming effort
Solution Approach 1:
The patent implements a universal order object model that can handle multiple order types through configuration rather than separate programming. The core components (header, items, schedule lines) and extensions provide a multi-functional framework that adapts to different order types via configurable parameters and data areas, eliminating the need for individual programming for each order type.
Solution Approach 2:
The system introduces dynamic configurability where order objects can be adapted to specific needs through configurable core components and extensions. The data areas and their associated tables can be dynamically selected and configured based on the specific order type, providing flexibility without requiring static hard-coded structures for each order type.
2Productivity
If order data is stored independently in databases without structured organization, then storage is simple, but data access becomes lengthy and inefficient
Solution Approach 1:
The patent segments order data into structured components (header, items, schedule lines) and organizes them into configurable data areas with associated tables. This segmentation allows for efficient indexing and retrieval of specific order information, dramatically reducing data access time compared to unstructured storage while maintaining organized, searchable data structures.
3Productivity
If a general data storage model is implemented for all order types, then processing can be standardized and optimized, but adaptability to specific order needs may be reduced
Solution Approach 1:
The system achieves both standardization and customization through dynamic configuration. The core components provide a standardized processing framework that can be optimized once and applied universally, while the configurable extensions and data areas allow adaptation to specific order needs. This dynamic approach enables standardized efficient processing without sacrificing customization capability.
4Productivity
If large volumes of order data are stored in single database tables, then storage is simplified, but access performance deteriorates due to the volume of data
Solution Approach 1:
The patent divides large volumes of order data into multiple configurable data areas, each with its own associated tables. This segmentation distributes data across multiple tables rather than storing everything in a single large table, improving access performance by allowing queries to target specific data areas and reducing the amount of data scanned during operations.
Data Source
AI summary
Methods and systems for managing order document data are provided. The order document data may be represented as an object, the object being configurable so as to comprise a predetermined number of core components, the core components being configurable in their content, and being hierarchically ordered in a corresponding number of levels. The object may comprise a number of extensions. The core components may comprise a header, at least one item, and/or schedule line. The header may comprise central information about an order.