Abstract: A method includes receiving, by a processing device, first trace data associated with a first processing chamber, wherein the first processing chamber satisfies one or more performance metrics. The method further includes generating target trace data based on the first trace data associated with the first processing chamber. The method further includes receiving second trace data associated with a second processing chamber, wherein the second processing chamber does not satisfy the one or more performance metrics. The method further includes generating, based on the target trace data and the second trace data, a first recommended corrective action associated with the second processing chamber, wherein the first recommended corrective action includes updating one or more equipment constants of the second processing chamber. The method further includes performing the first recommended corrective action.

Abstract: A method includes providing, as input to a first trained machine learning model, trace data associated with one or more substrate processing procedures. The input further includes equipment constants associated with the one or more substrate processing procedures. The input further includes trace data of a first processing chamber. The input further includes equipment constants of the first processing chamber. The method further includes obtaining, as output from the first trained machine learning model, a recommended update to a first equipment constant of the first processing chamber. The method further includes updated the first equipment constant of the first processing chamber responsive to obtaining the output from the first trained machine learning model.

Abstract: A method includes receiving, by a processing device, data indicative of performance of a plurality of process chambers. The method further includes providing the data indicative of performance of the plurality of process chambers to a model. The method further includes receiving as output from the model a first recommended equipment constant update associated with a first process chamber of the plurality of process chambers and a second recommended equipment constant update associated with a second process chamber of the plurality of process chambers. The method further includes updating a first equipment constant of the first process chamber and a second equipment constant of the second process chamber in view of the first recommended equipment constant update and the second recommended equipment constant update.

Abstract: An electronic device manufacturing system that includes a process tool, an evaluation system, and a communication node. The communication node is configured to obtain one or more attributes from the evaluation system and identify a data collection plan that is based on the one or more attributes. The communication node is further configured to register with the process tool to receive data according to the data collection plan and receive, from the process tool, data according to the data collection plan. The communication node is further configured to send the received data to the evaluation system.

Abstract: A method includes providing, as input to a first trained machine learning model, trace data associated with one or more substrate processing procedures. The input further includes equipment constants associated with the one or more substrate processing procedures. The input further includes trace data of a first processing chamber. The input further includes equipment constants of the first processing chamber. The method further includes obtaining, as output from the first trained machine learning model, a recommended update to a first equipment constant of the first processing chamber. The method further includes updated the first equipment constant of the first processing chamber responsive to obtaining the output from the first trained machine learning model.

Abstract: A method includes receiving, by a processing device, first trace data associated with a first processing chamber, wherein the first processing chamber satisfies one or more performance metrics. The method further includes generating target trace data based on the first trace data associated with the first processing chamber. The method further includes receiving second trace data associated with a second processing chamber, wherein the second processing chamber does not satisfy the one or more performance metrics. The method further includes generating, based on the target trace data and the second trace data, a first recommended corrective action associated with the second processing chamber, wherein the first recommended corrective action includes updating one or more equipment constants of the second processing chamber. The method further includes performing the first recommended corrective action.

Abstract: An electronic device manufacturing system that includes a process tool and a tool server coupled to the process tool and comprising a communication node and an evaluation system. The communication node is configured to receive, from a monitoring device registered on the process tool, data based on a data collection plan and send the received data to the evaluation system. The communication node is further configured to receive, from the evaluation system, feedback data based on the received data and cause the process tool to perform a corrective action based on the feedback data.

Abstract: A method includes receiving, by a processing device, data indicative of performance of a plurality of process chambers. The method further includes providing the data indicative of performance of the plurality of process chambers to a model. The method further includes receiving as output from the model a first recommended equipment constant update associated with a first process chamber of the plurality of process chambers and a second recommended equipment constant update associated with a second process chamber of the plurality of process chambers. The method further includes updating a first equipment constant of the first process chamber and a second equipment constant of the second process chamber in view of the first recommended equipment constant update and the second recommended equipment constant update.

Abstract: An electronic device manufacturing system that includes a process tool and a tool server coupled to the process tool and comprising a communication node and an evaluation system. The communication node is configured to obtain one or more attributes from an evaluation system and provide a monitoring device comprising a data collection plan that is based on the one or more attributes. The communication node is further configured to register the monitoring device with a process tool. The communication node is further configured to receive, from the process tool, data based on the data collection plan and send the received data to the evaluation system.

Abstract: An electronic device manufacturing system that includes a process tool and a tool server coupled to the process tool and comprising a communication node and an evaluation system. The communication node is configured to obtain one or more attributes from an evaluation system and provide a monitoring device comprising a data collection plan that is based on the one or more attributes. The communication node is further configured to register the monitoring device with a process tool. The communication node is further configured to receive, from the process tool, data based on the data collection plan and send the received data to the evaluation system.

Abstract: Systems and methods with variable and customized functionality for pumping milk from a breast, wherein the milk is expressed from the breast under suction and milk is expulsed from the pumping mechanism to a collection container under positive pressure.

Abstract: A wireless networking method includes placing a master device and at least one peripheral device within proximity of each other. A radio frequency request for proximity pairing is transmitted from the peripheral device to the master device. Radio frequency proximity pairing signals implementing the proximity pairing are transmitted from the master device to the peripheral device. The proximity pairing signals are transmitted with a first level of transmission power. After the proximity pairing is complete, operational signals are transmitted from the master device to the peripheral device. The operational signals are transmitted with a second level of transmission power greater than the first level of transmission power.

Abstract: In one embodiment, a quality compliance system for a medical device includes at least one medical device configured to diagnose, monitor, or treat a medical condition, the at least one medical device configured to lockout operation of the at least one medical device, a refurbishment device configured to establish a communication link with the at least one medical device, generate electronic documentation of a maintenance or service procedure on the at least one medical device, provide for associating a digital signature of an operator with the generated electronic documentation, transmit the digital signature and generated electronic documentation, and unlock the medical device with a received key, and a service application configured to receive the transmitted digital signature and generated electronic documentation, verify the transmitted digital signature and generated electronic documentation, and transmit the key to the refurbishment device upon verification of the transmitted digital signature and gener