The objective of this research is to identify optimal temperature sensor locations in a laminated die system for the purpose of predicting the temperature distribution throughout the die to control heating and cooling rates. Potential locations (referred to as target nodes) are grouped based on the similarity of their thermal response using both K-means and a proposed temperature ratio clustering method. A sensitivity analysis of the temperature distribution for these groups of target nodes identifies the sensor location for each cluster that exhibits the highest sensitivity to variable inputs. A comparison of sensor locations identified by each clustering method with the sensitivity analysis is presented and is used to evaluate the optimal sensor location in terms of consistency in generating these sensor locations, the degree of sensitivity, the mutual interaction through principal component analysis, limiting the number of sensors, and the accuracy in estimating the temperature distribution.

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