Secure Model Integration for Confidential Predictive Maintenance
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Solution Overview
Problem
Existing predictive maintenance models for semiconductor manufacturing devices lack accuracy due to limitations in sharing confidential parameters across multiple manufacturers, preventing the creation of more accurate models through collective analysis.
Innovation Solution
A secure computing system that receives and integrates concealed parameters from multiple semiconductor manufacturers using secure computation, outputting the results in a concealed form to maintain confidentiality while enhancing predictive maintenance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If models from multiple semiconductor manufacturers are integrated to improve predictive maintenance accuracy, then the accuracy of the predicted data is improved, but the confidentiality of the manufacturers' parameters is compromised
Solution Approach 1:
A secure computing system acts as an intermediary between multiple semiconductor manufacturers, enabling the integration of their predictive maintenance models without exposing their confidential parameters. The secure computing system processes and integrates the models while maintaining parameter confidentiality, thus resolving the contradiction between improving prediction accuracy through model integration and protecting manufacturers' proprietary information.
2Loss of information
If a single prediction model is used for predictive maintenance, then the confidentiality of manufacturer parameters is maintained, but the accuracy of the predicted data is limited
Solution Approach 1:
The secure computing system serves as a trusted intermediary that enables multiple manufacturers to contribute their models to a collective predictive maintenance system without directly sharing confidential parameters. This intermediary approach allows accuracy improvement through model integration while maintaining parameter confidentiality.
Solution Approach 2:
Instead of sharing original confidential model parameters, the system uses copies or representations of the models that can be integrated for prediction purposes without revealing the underlying proprietary information. This allows multiple models to be combined while protecting the source confidentiality.
Data Source
AI summary
A secure computing system according to the present disclosure is used in an analysis pertaining to predictive maintenance of a semiconductor manufacturing device, and comprises: a parameter reception means that receives concealed parameters of a plurality of models generated by each of a plurality of semiconductor manufacturers; a secure computing means that integrates the plurality of concealed parameters by secure computing; and an output means that outputs, in a concealed format, the parameters integrated by the secure computing means.


