Manufacturing Workflow Modeling With Meta-Workflow Auto-Suggestions
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Solution Overview
Problem
Existing Manufacturing Operations Management (MOM) systems face challenges in efficiently modeling and executing complex manufacturing workflows, which can be time-consuming and error-prone.
Innovation Solution
A method and system that assist users in modeling manufacturing workflows by searching for similarities within workflows and using these similarities to automatically or semi-automatically create or complete workflow definitions, leveraging a meta-workflow library and machine learning techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If workflows are manually modeled using traditional methods, then customization and precision are improved, but time consumption and error rate increase
Solution Approach 1:
The system performs preliminary action by pre-defining workflow patterns and templates that capture common manufacturing processes. When a user needs to create a workflow, the system retrieves and adapts these pre-defined patterns rather than requiring manual creation from scratch, significantly reducing time while maintaining precision through the structured template design
Solution Approach 2:
The system uses copying by replicating proven workflow patterns from a library of pre-defined templates. Instead of manually designing each workflow, users can copy existing patterns and adapt them to specific needs, ensuring consistency and accuracy while dramatically reducing modeling time
2Ease of operation
If comprehensive workflow libraries are created to assist users, then workflow creation ease is improved, but system complexity increases
Solution Approach 1:
The system applies segmentation by dividing the workflow library into modular, hierarchical categories and templates. This structured segmentation allows the system to manage complexity through organized modules while providing users with simplified, targeted options rather than overwhelming comprehensive choices
Solution Approach 2:
The system introduces an intermediary layer between the user and the complex workflow library. This intermediary automatically matches user needs with appropriate templates, manages the complexity of the underlying library structure, and presents simplified options to users, thus easing operation without requiring the system to expose its full complexity
3Productivity
If automated workflow generation is implemented, then productivity is improved, but reliability may worsen due to potential automation errors
Solution Approach 1:
The system implements feedback mechanisms where automated workflow generation is followed by validation steps that check against predefined criteria and patterns. User feedback and system validation feedback are integrated to verify accuracy, allowing automated productivity gains while maintaining reliability through continuous verification and correction loops
Data Source
AI summary
A method and system automatically assist in a creation of a manufacturing workflow (WF) for manufacturing a product. The method includes receiving a graphical user input in an editing area configured for creating a manufacturing WF, the graphical user input includes a WF starting node and automatically selecting in a meta-workflow (MWF) library, in response to the received graphical user input and in function of the latter, a MWF. The selected MWF is a graphical pattern starting with the WF starting node and ending with a WF ending node, the latter being connected to each other through a sequence of interconnected decision and/or activity nodes. The selected MWF is displayed in a display box and then in the editing area. A manufacturing WF is created from the MWF displayed in the editing area. An auto-suggestion process is used for associating each node of the MWF to a manufacturing operation.