Intelligent Failure Prediction of PCR Thermal Cyclers Using Sensor Data Abstraction Techniques
Chan-Young Park
Department of Convergence Software, Hallym University, Korea , Korea
Mi-So Lee
Department of Convergence Software, Hallym University, Korea , Korea
Yu-Seop Kim
Department of Convergence Software, Hallym University, Korea , Korea
Hye-Jeong Song
Department of Convergence Software, Hallym University, Korea , Korea
Jong-Dae Kim
Department of Convergence Software, Hallym University, Korea , Korea
Received 18 July 2023; received in revised form 20 November 2023; accepted 26 November 2023
Keywords: PCR thermal cycler, maintenance, aging, failure
Abstract
In this paper, the heating and cooling rates of polymerase chain reaction thermal cyclers was analysed over time, to predict their aging. Two kinds of methods were applied to calculate the rise times of the heating and cooling protocol sections, which were inversely related to the heating or cooling rates. The temporal changes of the rise times were investigated over several months. For three thermal cyclers with different structures, the increases of the rise times were fairly linear; therefore, the aging prediction is feasible.
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References
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