Systems and techniques for determining sensing margins and/or diagnostic information associated with a sensor are presented. A statistics component generates statistical data based on sensor data associated with a sensing device. A margin component generates sensing margins for the sensing device based on the statistical data. An output component generates an indicator for a changing condition associated with the sensing device based on the sensing margins. In an aspect, a diagnostic component generates diagnostic data for the sensing device based on the statistical data.

Systems and techniques for determining sensing margins and/or diagnostic information associated with a sensor are presented. A statistics component generates statistical data based on sensor data associated with a sensing device. A margin component generates sensing margins for the sensing device based on the statistical data. An output component generates an indicator for a changing condition associated with the sensing device based on the sensing margins. In an aspect, a diagnostic component generates diagnostic data for the sensing device based on the statistical data.

A failure diagnosis device applicable to a mechanical device provided with a motor as a source to drive a motion axis, and configured to acquire a moving position of the motion axis and a disturbance torque value applied to the motion axis every predetermined period, and to diagnose that a failure is occurring when the disturbance torque value is larger than a failure determination threshold, includes a disturbance torque selector configured to calculate a change from a reference value of each of the acquired disturbance torque values, and to accumulate the disturbance torque values except each disturbance torque value having the change from the reference value equal to or larger than a predetermined threshold, and a failure diagnosis unit configured to diagnose a failure of the mechanical device by using the disturbance torque values accumulated by the disturbance torque selector.

A process control technique uses production data from multiple manufacturing tools and multiple inspection or metrology tools. Total measurement uncertainty (TMU) can be calculated on the production data, which can include measurements of one or more devices manufactured using the manufacturing tools. Manufacturing steps can be ranked or otherwise compared by TMU. All production modes and recipes can be continually monitored using production data.

A method for anomaly detection in a cutting machine with a spindle that is driven by an electric motor, wherein the method includes determining an electric power consumption of the motor during a working cycle of the machine, dividing the working cycle into time windows, determining, for each time window, whether the spindle was cutting and/or idling based on associated electric power values, determining median and expected deviation of electric power values for cutting and idling operation over the sequence of time windows, and determining an anomaly if electric power values during cutting or idling exceed a predetermined relationship to the corresponding median and expected deviation values.