Unified SCPM Data Model for Cross-Functional Workflow Analytics
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Solution Overview
Problem
The complexity of supply chain and production management (SCPM) activities in industrial processes is hindered by the lack of coordination across multiple functional domains, leading to decision-based problems with different time horizons and granularity, and the challenge of integrating various systems used by different functional users with their own models and proprietary tools.
Innovation Solution
A unified model is created to represent different source system models, enabling flexible integration through a common database schema and Service-Oriented Architecture (SOA)-based interfaces, with a scalable SCPM data store that archives transactions and allows for automatic and on-demand analytics calculations, providing a common infrastructure for workflow analytics and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple separate systems with proprietary tools are used by different functional users, then each functional domain can maintain its own models and tools, but integration and coordination across functional domains becomes complex and difficult
Solution Approach 1:
The patent introduces a unified data model and common infrastructure as an intermediary layer between multiple functional domain systems. This mediator enables data exchange and coordination without requiring direct integration between each pair of systems, thus maintaining functional independence while reducing overall integration complexity.
Solution Approach 2:
The patent creates a universal data model that can represent multiple functional domains (supply chain, production management, etc.) within a single framework. This multi-functional model allows different systems to interact through a common interface, reducing the need for separate proprietary integration solutions for each domain pair.
2Loss of information
If data from multiple sources is integrated into a unified model, then cross-functional analytics and visualization become possible, but data integration and model unification become complex
Solution Approach 1:
The patent segments the data integration process into manageable components: individual data sources are first processed and transformed according to their specific characteristics, then integrated into the unified model through standardized interfaces. This segmentation reduces the overall complexity by breaking down the monolithic integration task into smaller, manageable steps.
Solution Approach 2:
The patent applies parameter changes by transforming data from different sources into a common format and structure defined by the unified model. Data parameters are adjusted and standardized during the integration process, enabling seamless consolidation while managing complexity through systematic transformation rules.
3Measurement precision
If detailed analytics and multiple views are provided for different functional users, then decision-making capabilities improve, but system complexity and processing requirements increase
Solution Approach 1:
The patent implements dynamic analytics generation where the system adapts its complexity based on user needs. Different functional users receive customized views and metrics appropriate to their roles, with the system dynamically selecting and processing only the necessary data subsets. This dynamic approach maintains high measurement precision while managing system complexity through selective processing.
Data Source
AI summary
A method includes obtaining information identifying transactions from multiple sources. The transactions relate to multiple functional domains of a supply chain associated with an industrial process. The method also includes storing the information in a data store according to a unified model. The method further includes providing a common user interface for different functional users. The common user interface is configured to display multiple visualizations and reports associated with the transactions. The method also includes obtaining, according to a user input at the common user interface, one or more metrics and one or more analytics from the data store. The one or more metrics and the one or more analytics are associated with the obtained information. The method also includes configuring the common user interface to display, according to the user input, at least one visualization or report involving the one or more metrics and the one or more analytics.