Service Operation Modeling Using Predicate-Action Pairs
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Solution Overview
Problem
In service industries, there is a lack of effective methods to make tacit knowledge and knowledge in documents, scripts, and software implementations reusable and maintainable, leading to non-uniformity and duplication of knowledge, which hinders knowledge sharing and utilization.
Innovation Solution
A method and system for modeling and executing service operations by representing factual and actionable knowledge in executable form using standard operators and predicate-action pairs, allowing for the selection and execution of appropriate operators based on conditions, thereby standardizing and structuring knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If knowledge is captured in various forms (documents, scripts, software implementations) without standardization, then knowledge can be stored and accessed, but knowledge becomes non-uniform and duplicated across the organization
Solution Approach 1:
The patent applies homogeneity by standardizing knowledge representation through a unified metadata schema and controlled vocabulary. All knowledge assets (documents, scripts, software implementations) are modeled using the same ontological framework with standardized properties, data types, and relationships. This ensures consistent structure and format across diverse knowledge sources, eliminating non-uniformity while maintaining manageable complexity through automation.
Solution Approach 2:
The patent implements universality by creating a platform-independent knowledge model that can represent various types of knowledge assets (documents, scripts, software implementations, tacit knowledge) using a single unified framework. The metadata schema and ontological model are designed to be technology-agnostic, allowing the same knowledge representation structure to handle diverse knowledge sources without requiring separate management systems for each type.
2Adaptability or versatility
If knowledge is duplicated across different technologies and implementations, then specific technology requirements are met, but memory space is wasted and maintenance becomes difficult
Solution Approach 1:
The patent applies copying by creating virtual representations of knowledge through standardized metadata models rather than storing multiple physical copies of the same knowledge in different formats. The ontological framework enables knowledge to be instantiated multiple times across different technology contexts while maintaining a single source of truth, reducing redundant storage while preserving technology-specific adaptations through parameterized metadata.
Solution Approach 2:
The patent implements parameter changes by using a configurable metadata schema where knowledge representations can be adapted to different technology contexts through parameter adjustment rather than duplication. The controlled vocabulary and standardized properties allow the same knowledge model to be parameterized for different technologies (e.g., Oracle on Windows vs. Oracle on Linux) by changing specific metadata values rather than creating separate knowledge artifacts.
3Productivity
If tacit knowledge in human resources is made explicit and reusable, then knowledge sharing improves, but the process of extracting and structuring tacit knowledge becomes complex
Solution Approach 1:
The patent applies self-service by enabling automated knowledge extraction and structuring through the standardized metadata model and ontological framework. The system can automatically capture tacit knowledge from various sources (documents, scripts, software implementations) and transform it into structured, reusable knowledge artifacts without requiring complex manual intervention. The standardized schema guides the extraction process, making it systematic rather than ad-hoc.
Solution Approach 2:
The patent implements preliminary action by pre-defining the metadata schema, ontological model, and controlled vocabulary before knowledge extraction begins. This preparatory work establishes the structure and rules for knowledge representation in advance, simplifying the subsequent extraction and structuring process. The predetermined framework provides clear guidelines for transforming tacit knowledge into explicit, reusable forms without requiring complex decision-making during extraction.
4Adaptability or versatility
If knowledge is standardized using uniform rules and formats, then knowledge reusability increases, but the initial effort to define and implement standardization rules increases
Solution Approach 1:
The patent applies preliminary action by establishing the metadata schema, ontological model, and controlled vocabulary in advance of knowledge capture and storage. This upfront standardization effort creates a reusable framework that accelerates subsequent knowledge management activities. The preliminary work defines the rules and structures once, enabling rapid and consistent knowledge standardization across the organization without repeating the standardization process for each knowledge asset.
Solution Approach 2:
The patent implements universality by designing a metadata schema and ontological model that can handle multiple types of knowledge assets and technology contexts through a single unified framework. This universal approach increases knowledge reusability across different departments, technologies, and use cases, as the same standardized model can represent diverse knowledge without requiring separate standardization efforts for each domain.
Data Source
AI summary
Disclosed is method and system for modeling and executing service operation associated with technical service. Method comprises modeling of knowledge required for execution of service operation by representing factual knowledge and actionable knowledge in executable form. Modeling comprises representing standard operators and service operation. Service operation comprises parameters and rules presented in form of list of predicate-action pairs. Predicate-action pair comprises predicate and action. Predicate defines condition to be verified to comply with rule, and action specifies standard operator to be executed based on verification of condition. Method further comprises execution of service operation. Execution of service operation comprises selecting each predicate-action pair from list of predicate-action pairs and supplying subset of parameters to predicate of each predicate-action pair, verifying condition using subset of parameters, selecting standard operator based on verification of condition, supplying subset of parameters to standard operator, executing the standard operator by using subset of parameters.