Postal Data Modeling Framework for Legacy System Forecasting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Production management applications are unable to effectively process data for postal operations, such as forecasting future mail sortation states, despite the availability of abundant postal data and widespread use of legacy production management applications in mail sortation facilities.
Innovation Solution
An enhanced postal data modeling framework is introduced, which models postal operations as production management data capable of being processed by production management applications, allowing for predictive forecasting of future states by mapping postal data to production management data and vice versa, enabling insights into mail sortation processes, resource allocation, and customer delivery schedules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If production management applications are used for postal operations, then existing legacy applications can be utilized, but the applications cannot process postal data to forecast future mail sortation states
Solution Approach 1:
The patent introduces a data mapping framework that acts as an intermediary between postal operations data and production management applications. This framework translates postal data into production management data formats, enabling legacy applications to process and analyze postal operations for forecasting future states without requiring application redesign.
Solution Approach 2:
The patent transforms postal operational parameters into production management parameters through systematic data mapping. By changing the data representation and structure to match production management expectations, the system enables existing applications to accurately forecast future mail sortation states using historical postal data.
2Ease of manufacture
If postal data is mapped to production management data, then legacy applications can process the data, but data transformation complexity increases
Solution Approach 1:
The patent creates a universal data mapping framework that can handle multiple postal data types and transform them into a standardized production management data format. This multi-functional mapping approach consolidates complexity into a single reusable framework, simplifying the integration of various postal operations into existing applications.
Solution Approach 2:
The patent generates virtual copies of postal data in the format expected by production management applications. By creating transformed copies of the data rather than modifying the original postal systems, the solution maintains data integrity while enabling legacy applications to process and analyze the data without direct system integration complexity.
3Loss of information
If production management applications forecast future states, then planning insights are provided, but the applications lack postal operation specific capabilities
Solution Approach 1:
The data mapping framework serves as an intermediary that preserves postal operation specific information while translating it into production management terminology. This ensures that forecasting insights remain accurate and relevant to postal operations, as the mapping maintains the essential characteristics and relationships of the original postal data during transformation.
Data Source
AI summary
An enhanced postal data modeling framework, in which postal data which describes characteristics of a mail sortation process is accessed, and the postal data is mapped to production management data which describes characteristics of a model production management process in an initial state and which is capable of being processed by a production management application. The production management data is input for processing by the production management application to produce forecasted production management data which predicts characteristics of the model production management process in a subsequent state, the forecasted production management data is modeled to forecasted postal data which predicts characteristics of the mail sortation process, and at least a portion of the forecasted postal data is provided to a user.