SEAM-Based CBM Workflow Reconfiguration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional condition-based health maintenance (CBM) systems are rigidly configured, leading to high costs and complexity, making it difficult to develop a flexible and cost-effective solution that can be easily customized for various complex systems without significant reprogramming efforts.
Innovation Solution
A computerized method using a data modeling tool to customize task workflow in a CBM system by populating computing nodes with standardized executable application modules (SEAMs) and configuring a workflow service state machine to generate events and associate unique responses, allowing for real-time reconfiguration without recompiling software.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional CBM systems are rigidly configured, then system stability is maintained, but adaptability and ease of customization deteriorate
Solution Approach 1:
The system is divided into standardized executable application modules (SEAMs) that can be independently selected, combined, and configured. Each SEAM represents a functional unit that can be reused across different CBM implementations, allowing adaptability without requiring custom development for each system.
Solution Approach 2:
A universal platform is provided with standardized interfaces and a common architecture that supports multiple CBM implementations. The same platform can serve different complex systems through configuration of SEAMs, eliminating the need for separate proprietary solutions for each application.
2Ease of manufacture
If conventional CBM systems are rigidly configured, then manufacturing precision is maintained, but ease of manufacture and reconfiguration cost deteriorate
Solution Approach 1:
SEAMs are pre-developed, pre-tested, and pre-validated as standardized modules. This preliminary action ensures that when SEAMs are combined to create new CBM systems, the reliability is maintained through reuse of proven components, while reconfiguration costs are reduced because only configuration rather than development is required.
Solution Approach 2:
Instead of creating custom software for each CBM system, the invention uses copies of standardized SEAMs that can be selectively instantiated and configured. This copying approach maintains reliability through consistent, tested code while dramatically reducing reconfiguration costs compared to custom development.
3Productivity
If conventional CBM systems are rigidly configured, then measurement precision is maintained, but productivity and reconfiguration speed deteriorate
Solution Approach 1:
The system transitions from static, rigid configuration to dynamic, runtime configuration. SEAMs can be selected, combined, and configured at runtime based on the specific CBM needs, allowing rapid reconfiguration without recompiling software. This dynamic approach increases productivity while managing complexity through standardized interfaces.
4Ease of operation
If conventional CBM systems are rigidly configured, then stability is maintained, but ease of operation and user customization capability deteriorate
Solution Approach 1:
The system enables users to perform their own customization by providing intuitive interfaces for selecting and configuring SEAMs. Users can define their own CBM workflows by combining standardized modules without requiring programming knowledge, making the system self-serviceable while maintaining operational ease.
Data Source
AI summary
Systems and methods are provided for customizing workflow in a condition based health maintenance (“CBM”) system computing node. The computerized method comprises identifying a first standardized executable application module (“SEAM”), wherein the first SEAM is configured to generate a first event associated with particular data being processed by the first SEAM and identifying a second SEAM, wherein the second SEAM is configured to generate a subsequent event associated with the particular data processed by the first SEAM. The computerized method further comprises creating a quasi-state machine associating a unique responses to the first event and associating a unique responses to the subsequent event, and installing the quasi-state machine into the SDS of the computing node from which the workflow service state machine retrieves the one or more unique responses from the quasi-state machine to the first event for processing by the second SEAM to produce the subsequent second event.