Modeling and control of thermocouples for reduced measurement uncertainty in diffusion furnaces

Mark E. Yelverton; Michael J. McBride

doi:10.1117/12.410063

23 August 2000 Modeling and control of thermocouples for reduced measurement uncertainty in diffusion furnaces

Mark E. Yelverton, Michael J. McBride

Proceedings Volume 4182, Process Control and Diagnostics; (2000) https://doi.org/10.1117/12.410063
Event: Microelectronic Manufacturing, 2000, Santa Clara, CA, United States

Abstract

Thermocouples are a widely used sensor in Semiconductor manufacturing because of their relatively low cost and ease of use. Most users in an attempt to improve measurement accuracy, purchase pre-calibrated thermocouples and establish replacement or re-calibration schedules. Unfortunately, these processes are often not based on actual thermocouple drift data, but most likely base don historical practice, opinion, or misinformation. This paper addresses the simple, but often misunderstood physics behind how thermocouples 'feel' temperature, and models the various sources of error that can occur with this sensor. Using this information, this paper outlines a procedure for ensuring accurate measurement in a production environment. The electronics used to convert the thermocouple signal to a temperature is discussed, along with how thermocouples are calibrated and why in-situ calibration in the field is not practical. Sources of measurement error are modeled including incoming calibration error, manual data-entry error of calibration data, tool or electronically induced error, and drift over time. These sources of error are described and modeled for 'type R' thermocouples, the most widely used thermocoupled for high temperature diffusion applications, using over five years of manufacturing data from over 70 horizontal and vertical diffusion furnaces.

Citation Download Citation

Mark E. Yelverton and Michael J. McBride "Modeling and control of thermocouples for reduced measurement uncertainty in diffusion furnaces", Proc. SPIE 4182, Process Control and Diagnostics, (23 August 2000); https://doi.org/10.1117/12.410063

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