Digital Twin Control Plan for Continuous Manufacturing Verification
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Solution Overview
Problem
Existing control plans in manufacturing processes are limited by their human-readable format, hindering automation and reducing their effectiveness in ensuring quality assurance and process conformity.
Innovation Solution
A digital system model (DSM) and digital twin (DTw) of the manufacturing process, particularly the control plan, are developed to represent, analyze, and optimize quality assurance, integrating real-world data for continuous verification and validation, reducing disruptions and improving first-time quality and production rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If control plan is described in human-readable format, then ease of operation is improved, but extent of automation deteriorates
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the control plan that mirrors the human-readable format while enabling automated processing. The digital twin maintains the same structure and information as the original control plan but exists in a machine-executable digital format, allowing automation systems to access and process control requirements without requiring human interpretation.
Solution Approach 2:
The patent transforms the control plan from static human-readable text into a dynamic digital model with machine-executable parameters. By changing the format parameters from natural language descriptions to structured digital data with defined schemas and validation rules, the system enables automated verification and validation while preserving the operational clarity needed for human understanding.
2Productivity
If verification and validation are performed at set stages, then device complexity is reduced, but productivity deteriorates
Solution Approach 1:
The patent implements continuous verification and validation throughout the manufacturing process rather than at discrete stages. The digital twin enables ongoing comparison between actual process data and control plan requirements, allowing quality assurance to occur continuously during production. This eliminates stop/resume cycles and maintains steady-state operation, improving productivity while the digital automation manages the increased verification complexity.
Solution Approach 2:
The patent replaces manual, stage-based verification processes with automated digital validation systems. The digital twin automatically validates process data against control requirements using computational algorithms, substituting human-operated mechanical inspection processes with software-based continuous verification. This automation handles the increased complexity of continuous monitoring without proportionally increasing operational burden.
3Ease of operation
If control plan is used traditionally for human operators, then ease of operation is improved, but extent of automation deteriorates
Solution Approach 1:
The patent creates a universal control plan system that serves multiple functions simultaneously. The digital twin of the control plan can be accessed and executed by both human operators (maintaining ease of operation) and automated systems (enabling extent of automation). The same digital model supports human decision-making while providing machine-executable instructions for automated verification, validation, and process control, making the system universally applicable to both operational modes.
Data Source
AI summary
A method of developing a product is provided that includes generating a digital system model (DSM) that describes the product and a manufacturing process for the product, and generating a digital twin (DTw) of an instance of a component of the manufacturing process, the DTw including a digital replica of the instance. The method includes receiving attribute data for attributes of process/process characteristics subject to sources of variation that affect product quality. The digital replica is executed with input of the attribute data, and thereby updating the DTw to replicate the instance of the component of the manufacturing process as performed. A data analysis of the manufacturing process is performed based on the DTw as updated, and the manufacturing process is modified based on the data analysis to reduce variability in one or more product characteristics. The DTws of multiple instances may be used to generate further improvement.