Sensor auditing is an important component of statistical process monitoring (SPM). The sensors generate a wealth of information. This information is used for monitoring and controlling the process. Misleading information can be generated if there is a bias change, drift or high levels of noise in some of the sensors. Erroneous information often causes control actions that are unnecessary, resulting in the deterioration of product quality, safety and profitability [224]. Identifying failures such as a broken thermocouple is relatively easy since the signal received from the sensor has a fixed and unique value. Incipient sensor failures that cause drift, bias change or additional noise are more difficult to identify and may remain unnoticed for extended periods of time. Consequently, early detection and diagnosis of such faults followed by timely reporting of the analysis can assist plant operators in improving product quality, process safety and profitability.