Abstract:
A method of monitoring a thermal processing system in real-time using a built-in self test (BIST) table to detect, diagnose and/or predict fault conditions and/or degraded performance. The method includes positioning a plurality of wafers in a processing chamber in the thermal processing system, performing a self test process, determining a real-time transient error from a measured transient response and a baseline transient response determined by a BIST rule stored in the BIST table, and comparing the transient error to operational limits and warning limits established by the BIST rule for the self test process.
Abstract:
A method of monitoring a single-wafer processing system in real-time using low-pressure based modeling techniques that include processing a wafer in a processing chamber; determining a measured dynamic process response for a rate of change for a process parameter; executing a real-time dynamic model to generate a predicted dynamic process response; determining a dynamic estimation error using a difference between the predicted dynamic process response and the expected process response; and comparing the dynamic estimation error to operational limits.
Abstract:
A method of determining wafer curvature in real-time is presented. The method includes establishing a first temperature profile for a hotplate surface, where the hotplate surface is divided into a plurality of temperature control zones. The method further includes positioning a wafer at a first height above the hotplate surface and determining a second temperature profile for the hotplate surface. The wafer curvature is then determined by using the second temperature profile. Also, a dynamic model of a processing system is presented and wafer curvature can be incorporated into the dynamic model.
Abstract:
An adaptive real time thermal processing system is presented that includes a multivariable controller. The method includes creating a dynamic model of the MLD processing system and incorporating virtual sensors in the dynamic model. The method includes using process recipes comprising intelligent set points, dynamic models, and/or virtual sensors.
Abstract:
A heat treatment apparatus for making a heat treatment while estimating temperatures of objects-to-be-processed that can estimate correct temperatures of the objects-to-be-processed. A reaction tube includes heaters and temperature sensors, and receives a wafer boat. A controller estimates temperatures of wafers and temperatures of the temperature sensors in zones in the reaction tube corresponding to the heaters by using the temperature sensors and electric powers of the heaters. Based on relationships between estimated temperatures of the temperature sensors and really metered temperatures, functions expressing the relationships between the estimated temperatures and the really metered temperatures are given for the respective zones. The functions are substituted by the estimated wafer temperatures to correct the estimated wafer temperatures. Electric powers to be fed to the respective heaters are respectively controlled so that the corrected wafer temperatures are converged to target temperature trajectories.
Abstract:
There is provided a batch type heat treatment system, control method and heat treatment method capable of appropriately coping with a multi-product small-lot production. A reaction tube 2 comprises a plurality of heaters 31 through 35 and a plurality of temperature sensors, and houses therein a wafer boat 23. A control part 100 stores therein many mathematical models for estimating (calculating) the temperature of wafers W in the reaction tube 2, in accordance with the number and arranged position of the wafers W mounted on the wafer boat 23, and many target temperature trajectories. If the wafer boat 23 is loaded in the reaction tube 2, a mathematical model and a target temperature trajectory corresponding to the number and arranged position of the mounted wafers W are read. If a deposition process is started, the output of a temperature sensor S and the model are used for estimating the temperature of the wafers W in the reaction tube 2, and the powers to be supplied to the heaters 31 through 35 are separately controlled so that the estimated temperature approaches the target temperature trajectory.
Abstract:
A system for controlling a thermal reactor is disclosed that characterizes the thermal reactor with a reactor model that indicates behavior of the thermal reactor and of a load contained in the thermal reactor and that accounts for interaction among a set of heating zones of the thermal reactor. An online reactor model is then determined that estimates the thermal behavior of the load based upon an online input power to the thermal reactor and upon an online temperature indication from the thermal reactor. A time varying temperature and reactant flow recipe is determined that minimizes end of run parameters on the load. A multi-variable controller is employed to minimize temperature deviations of the load from a predetermined temperature recipe or time varying trajectory.
Abstract:
A method of monitoring a processing system in real-time using low-pressure based modeling techniques that include processing one or more of wafers in a processing chamber; determining a measured dynamic process response for a rate of change for a process parameter; executing a real-time dynamic model to generate a predicted dynamic process response; determining a dynamic estimation error using a difference between the predicted dynamic process response and the expected process response; and comparing the dynamic estimation error to operational limits.
Abstract:
An adaptive real time thermal processing system is presented that includes a multivariable controller. The method includes creating a dynamic model of the MLD processing system and incorporating virtual sensors in the dynamic model. The method includes using process recipes comprising intelligent set points, dynamic models, and/or virtual sensors.
Abstract:
A method of monitoring a thermal processing system in real-time using a built-in self test (BIST) table to detect, diagnose and/or predict fault conditions and/or degraded performance. The method includes positioning a plurality of wafers in a processing chamber in the thermal processing system, performing a self test process, determining a real-time transient error from a measured transient response and a baseline transient response determined by a BIST rule stored in the BIST table, and comparing the transient error to operational limits and warning limits established by the BIST rule for the self test process.