Quality prognostics system and method for manufacturing processes
First Claim
1. A quality prognostics system for manufacturing processes, comprising:
- conjecture modeling means for using a set of current input data of a production tool to conjecture a conjecture value for a product lot currently manufactured in said production tool, wherein said conjecture modeling means is built in accordance with a conjecture method, and said conjecture method is selected from the group consisting of a first neural network technique, a fuzzy logic technique and a stepwise regression technique; and
prediction modeling means for using said conjecture value of said product lot together with at least two actual measurement values of at least two previous product lots to predict a prediction value for a next product lot, wherein said at least two previous product lots are respectively produced in at least two production cycles, and said at least two actual measurement values are one-to-one corresponding to said at least two previous product lots respectively, and said prediction modeling means is built in accordance with a prediction method, and said prediction method is selected from the group consisting of a weighted moving average technique and a second neural network technique.
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Abstract
A quality prognostics system and a quality prognostics method for predicting the product quality during manufacturing processes are disclosed, wherein the current production tool parameters sensed during the manufacturing process and several previous quality data collected from the measurement tool are utilized to predict the future product quality, and a conjecture modeling step and prediction modeling step are performed respectively. The conjecture modeling step itself also can be applied for the purpose of virtual metrology. Further, a self-searching step and a self-adjusting step are performed for searching the best combination of various parameters/functions used by the conjecture algorithm or prediction algorithm; and meeting the requirements of new equipment parameters and conjecture/prediction accuracy.
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Citations
19 Claims
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1. A quality prognostics system for manufacturing processes, comprising:
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conjecture modeling means for using a set of current input data of a production tool to conjecture a conjecture value for a product lot currently manufactured in said production tool, wherein said conjecture modeling means is built in accordance with a conjecture method, and said conjecture method is selected from the group consisting of a first neural network technique, a fuzzy logic technique and a stepwise regression technique; and prediction modeling means for using said conjecture value of said product lot together with at least two actual measurement values of at least two previous product lots to predict a prediction value for a next product lot, wherein said at least two previous product lots are respectively produced in at least two production cycles, and said at least two actual measurement values are one-to-one corresponding to said at least two previous product lots respectively, and said prediction modeling means is built in accordance with a prediction method, and said prediction method is selected from the group consisting of a weighted moving average technique and a second neural network technique. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A quality prognostics method for manufacturing processes, comprising:
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providing a conjecture modeling step for using a set of current input data of a production tool to conjecture a current conjecture value for a product lot currently manufactured in said production tool, wherein said conjecture modeling step is based on a conjecture method, and said conjecture method is selected from the group consisting of a first neural network technique, a fuzzy logic technique and a stepwise regression technique; and providing a prediction modeling step for using said current conjecture value of said product lot together with at least two actual measurement values of at least two previous product lots to predict a prediction value for a next product lot, wherein said at least two previous product lots is respectively produced in at least two production cycles, and said at least one actual measurement value is one-to-one corresponding to said at least one previous product lot, and said prediction modeling step is based on a prediction method, and said prediction method is selected from the group consisting of a weighted moving average technique and a second neural network technique. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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Specification