Automated Configure-to-Order Platform for Real-Time Supply Chain Visibility
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional ERP systems face inefficiencies due to data fragmentation, lack of integration capabilities, data inconsistency, security concerns, and inability to handle large volumes of data, leading to operational delays and poor customer experiences in distribution and supply chain management.
Innovation Solution
An integrated platform with a Real-Time Data Mesh (RTDM) and Single Pane of Glass (SPoG) UI, employing AI and ML algorithms for automated Configure to Order (CTO) and Quote to Order (QTO) processes, optimizing inventory management, pricing, and ensuring data security and compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional ERP systems are used for managing distribution and supply chain processes, then comprehensive data storage and departmental access are provided, but data fragmentation and lack of real-time visibility occur
Solution Approach 1:
The patent merges multiple ERP systems and data sources into a single unified platform that consolidates all distribution and supply chain data. This integration eliminates data silos and provides centralized real-time visibility across all departments and systems, directly resolving the contradiction between data accessibility and real-time visibility.
Solution Approach 2:
The patent introduces an intermediary layer (the unified platform) that sits between traditional ERP systems and users. This intermediary aggregates, standardizes, and presents data from multiple sources in real-time, enabling comprehensive visibility without requiring changes to underlying legacy systems.
2Reliability
If traditional ERP systems are used, then centralized data storage is achieved, but data integration capabilities with external systems remain ineffective
Solution Approach 1:
The unified platform is designed with universal integration capabilities that can connect with multiple external systems and vendors simultaneously. It provides standardized data exchange protocols and interfaces that work across different systems, making the platform adaptable and versatile while maintaining centralized data storage.
3Manufacturing precision
If manual processes are used for data transformation and validation, then data standardization is achieved, but operational delays occur
Solution Approach 1:
The unified platform implements automated data transformation and validation processes that operate without manual intervention. The system automatically standardizes data formats, validates information accuracy, and transforms data between systems, eliminating the need for time-consuming manual processes while maintaining high data quality standards.
Solution Approach 2:
The patent replaces manual mechanical processes (human operators performing data transformation) with automated electronic systems. The unified platform uses software-based data transformation engines that instantly process and standardize data, replacing the slow manual workflow with high-speed automated processing.
4Stability of the object's composition
If traditional ERP systems are used, then existing system stability is maintained, but ability to handle large volumes of data effectively is limited
Solution Approach 1:
The unified platform segments and distributes data processing across multiple components and servers, enabling it to handle large volumes of data efficiently. By dividing the data processing workload into manageable segments handled by different system components, the platform maintains stability while scaling to accommodate massive data volumes.
5Adaptability or versatility
If traditional ordering processes are used, then multiple systems can independently perform activities, but inefficiencies and errors increase
Solution Approach 1:
The patent merges independent ordering activities into a single streamlined workflow within the unified platform. Instead of multiple systems performing activities independently with manual handoffs, the platform consolidates the entire order process from bill of materials creation to order submission into one automated flow, eliminating redundancies and errors while maintaining the ability to perform all necessary functions.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Computerized systems and methods are disclosed for automating Configure to Order (CTO) and Quote to Order (QTO) processes. Methods include receiving user inputs for desired product configurations, retrieving corresponding data from a bill of materials database, and calculating optimized pricing through intelligent rules based on real-time market data. Automated quotes are generated and transferred to orders in a vendor system, selected based on pre-set criteria like vendor reputation and delivery time. Validation steps reduce errors, and real-time reports are generated. The system integrates a Real-Time Data Mesh for data aggregation, a Single Pane of Glass User Interface for user interactions, and Advanced Analytics and Machine Learning Modules for implementing rule-based and learning algorithms. The system is accessible across various devices and standardizes data for uniform consumption, while also employing machine learning models to continually optimize processes. Notifications are sent to users upon successful execution of orders or completion of quotes.