SKU to TMF Translation via Multi-Value Mapping Tables
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Solution Overview
Problem
Conventional ERP systems face challenges in translating customer orders' stock keeping unit (SKU) hierarchies to vendor-specific type-model-feature structures, especially for configurable products, due to the lack of a one-to-one correspondence between customer-defined and vendor-defined part numbers, and require cumbersome and inflexible methods to handle special manufacturing instructions.
Innovation Solution
A computer-based method that defines a multi-value characteristic and a table structure to translate SKU hierarchies into a type-model-feature structure, allowing for the translation of configurable products and special manufacturing instructions, using a SKU translation table to map customer orders to vendor-specific nomenclature, ensuring transparent and efficient processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional ERP systems use one-to-one relationship mapping between customer part numbers and vendor part numbers, then simple order processing is achieved, but configurable products cannot be properly handled
Solution Approach 1:
The patent segments the translation process into multiple hierarchical levels: customer SKU hierarchy (customer part number, customer options) is translated through intermediate mapping tables to vendor TMF structure (type, model, features). This segmentation allows complex configurable product translations to be broken down into manageable mapping steps, resolving the contradiction between handling versatility and system complexity.
Solution Approach 2:
The patent introduces intermediary mapping tables that serve as mediators between customer SKU hierarchies and vendor TMF structures. These intermediate tables store mapping relationships and enable flexible translation without requiring direct one-to-one correspondence, thus enabling configurable product handling while managing translation complexity.
2Adaptability or versatility
If flexible translation methods are implemented to handle configurable products, then adaptability improves, but processing efficiency decreases
Solution Approach 1:
The patent implements preliminary action by pre-establishing mapping tables that define relationships between customer SKUs and vendor TMF structures before actual order processing. During order translation, the system performs lookups in these pre-configured tables rather than computing translations in real-time, thus maintaining high processing efficiency while handling complex configurable products.
Solution Approach 2:
The patent uses copying by creating standardized template structures for different product types. Once a translation mapping is established for a particular configurable product configuration, it can be copied and reused for identical or similar configurations, significantly improving processing efficiency for repetitive orders while maintaining adaptability.
3Measurement precision
If detailed mapping tables are created to maintain translation accuracy, then data quality improves, but system complexity increases
Solution Approach 1:
The patent resolves the contradiction by organizing mapping tables in hierarchical dimensions rather than flat structures. The translation process moves through multiple dimensional layers: customer SKU → customer option → intermediate mapping → vendor type → vendor model → vendor features. This dimensional organization maintains translation accuracy through structured validation at each layer while managing complexity through hierarchical decomposition.
4Reliability
If customer-specific SKU hierarchies are translated to vendor TMF structure, then order fulfillment accuracy improves, but processing time increases
Solution Approach 1:
The patent implements continuity of useful action by establishing continuous mapping relationships in the translation tables between customer SKUs and vendor TMF structures. Once the mapping infrastructure is in place, translations proceed through continuous lookup operations rather than discrete computational steps, reducing processing time while maintaining fulfillment accuracy through validated mapping paths.
Data Source
AI summary
A method for translating a stock keeping unit (SKU) hierarchy in a customer order to a type-model-feature (TMF) structure in a vendor's order fulfillment system. A translation table relating the SKU hierarchy and TMF structure is defined. The SKU hierarchy includes SKU numbers that identify a configurable part and configurable options that specify a product. An initial order for the product includes the SKU hierarchy. Using the translation table, the SKU numbers are translated into an instance of the TMF structure. A multi-value characteristic is populated with values that include the SKU numbers and subline identifiers. A second order for the product is created that includes the instance of the TMF structure and subline values associated with the SKU number that identifies the configurable part.