Metrics independent and recipe independent fault classes

A non-transitory machine-accessible storage medium including data that, when accessed by a machine, cause the machine to perform a method comprising:

• analyzing process data using a first metric to identify a fault, wherein the process data was obtained from a manufacturing machine running a first recipe;
• identifying a fault signature that matches the fault, wherein the fault signature was generated using at least one of a second metric and a second recipe, wherein the fault signature ranks a plurality of process conditions representative of one or more faults in accordance with a contribution of each of the plurality of process conditions, wherein the fault signature does not include a process condition with a contribution that compares in a predetermined manner to a threshold;
• and
• identifying at least one fault class that is associated with the fault signature, wherein each fault class identifies a cause of the one or more faults represented by the fault signature.

A statistical process monitoring system, comprising:

• a fault detector coupled with a manufacturing machine, the fault detector to receive process data produced using a first recipe from the manufacturing machine, and to analyze the process data using a first metric to identify a fault;
• a database to store a plurality of fault signatures, each of the fault signatures being associated with at least one fault class;
• and
• a fault diagnoser coupled with the fault detector and coupled with the database, the fault diagnoser to identify a matching fault signature that matches the fault from the plurality of fault signatures, wherein the matching fault signature was generated using at least one of a second metric and a second recipe with the manufacturing machine, wherein the fault signature ranks a plurality of process conditions representative of one or more faults in accordance with a contribution of each of the plurality of process conditions, wherein the fault signature does not include a process condition with a contribution that compares in a predetermined manner to a threshold, and to identify at least one fault class that is associated with the fault signature, wherein the fault class identifies a cause of the one or more faults represented by the fault signature.

A computer-implemented method of diagnosing faults, comprising:

• analyzing, by a computer system hosting a statistical process monitoring apparatus, process data from at least one of historical data and training data to identify a plurality of faults;
• determining, by the computer system, one or more process variables that contributed to the plurality of faults;
• determining, by the computer system, a relative contribution of each of the one or more process variables to the plurality of faults;
• generating, by the computer system, a fault signature for each of the plurality of faults, the fault signature having relative contribution ranges that include the relative contributions of each of the one or more process variables, wherein the fault signature does not include a process variable with a relative contribution that compares in a predetermined manner to a threshold;
• dividing, by the computer system, the plurality of faults into groups based on similarities in fault signatures;
• and
• generating, by the computer system, a fault class for each of the groups of faults, wherein each fault class identifies a cause of a corresponding group of faults.

A non-transitory machine-accessible storage medium including data that, when accessed by a machine, cause the machine to perform a method comprising:

• analyzing process data from at least one of historical data and training data to identify a plurality of faults;
• determining one or more process variables that contributed to the plurality of faults;
• determining a relative contribution of each of the one or more process variables to the plurality of faults;
• generating a fault signature for each of the plurality of faults, the fault signature having relative contribution ranges that include the relative contributions of each of the one or more process variables, wherein the fault signature does not include a process variable with a relative contribution that compares in a predetermined manner to a threshold;
• dividing the plurality of faults into groups based on similarities in fault signatures;
• and
• generating a fault class for each of the groups of faults, wherein each fault class identifies a cause of a corresponding group of faults.

A statistical process monitoring system, comprising:

• a database to store a at least one of historical process data and training process data;
• a fault detector coupled with the database to analyze at least one of the historical process data and training process data to identify a plurality of faults;
• and
• a fault diagnoser coupled with the fault detector to determine one or more process variables that contributed to the plurality of faults, to determine a relative contribution of each of the one or more process variables to the plurality of faults, to generate a fault signature for each of the plurality of faults, the fault signature having relative contribution ranges that include the relative contributions of each of the one or more process variables, the fault signature not including a process variable with a relative contribution that compares in a predetermined manner to a threshold, to divide the plurality of faults into groups based on similarities in fault signatures, and to generate a fault class for each of the groups of faults, wherein each fault class identifies a cause of a corresponding group of faults.