A method for a substrate measurement subsystem is provided. An indication is received that a substrate being processed at a manufacturing system has been loaded into a substrate measurement subsystem. First positional data of the substrate within the substrate measurement subsystem is determined. One or more portions of the substrate to be measured by one or more sensing components of the substrate measurement subsystem are determined based on the first positional data of the substrate and a process recipe for the substrate. Measurements of each of the determined portions of the substrate are obtained by one or more sensing components of the substrate measurement subsystem. The obtained measurements of each of the determined portions of the substrate are transmitted to a system controller.

A travel path of an article transport facility provided with a plurality of article transport vehicles that travel along the travel path and transport articles, and a control device that controls operation of the article transport vehicles includes a path set in an inspection area for causing a target transport vehicle designated as an inspection target from among the plurality of article transport vehicles to travel along. The target transport vehicle includes a sensor that detects behavior of the target transport vehicle during travel. The control device controls the plurality of article transport vehicles such that only the one target transport vehicle is present in the inspection area, and causes the target transport vehicle to travel in the inspection area in an inspection travel pattern prescribed in advance.

Disclosed herein is technology for performing a simulation based optimization to identify a schedule for a manufacturing tool. An example method may include determining, by a processing device, resources of a manufacturing tool, wherein the resources comprise a first chamber and a second chamber; accessing task data indicating a first manufacturing task and a second manufacturing task; determining a duration to perform the first manufacturing task using the first chamber and a duration to perform the second manufacturing task using the second chamber; updating a machine learning model based on the duration to perform the first manufacturing task and the duration to perform the second manufacturing task; performing a set of computer simulations that uses the machine learning model and the task data to produce a set of simulation results; storing, by the processing device, a simulation result of the set of simulation results in a data store.

A system, method and software for generating and receiving information about the AC, DC, RF, voltage, and other characteristics and information provided by components in a system. The information can provide insight into the operational characteristics and functionality of the components, as well as the process and system the components are being used within. This information may be used for preventative maintenance of the components, and to detect changes, issues, failures, events, problems, etc. in the process and system.

A substrate treatment apparatus includes a plurality of treatment chambers performing different treatment types on a substrate; a transfer device; and a controller that controls the transfer of the substrate and the substrate treatment. The controller enables fixation of a time for pulling up the substrate for each treatment chambers/treatment type and creation of a transfer schedule for transferring the substrate among the plurality of treatment chambers/treatment types and treating the substrate so as to maximize throughput, and enables correction of the transfer schedule to extend, based on a waiting time of the transfer device after storage of the substrate into a treatment chamber of one treatment type and a waiting time of the treatment chamber after treatment of the substrate, a time required for pulling up the substrate from a treatment chamber of an immediately previous treatment type in transfer order of the substrate.

A method includes transferring a wafer into a first process chamber of a cluster tool; performing a first process to the wafer in the first process chamber; transferring the wafer from the first process chamber to a second process chamber of the cluster tool after performing the first process; cleaning the first process chamber; performing a second process to the wafer in the second process chamber during cleaning the first process chamber.

A device used for semiconductor metrology includes a substrate and a plurality of pieces from one or more semiconductor wafers. Each piece of the plurality of pieces is bonded to the substrate at a respective position on the substrate. Each piece of the plurality of pieces includes a respective instance of a measurement test structure and an alignment mark. Each piece of the plurality of pieces has a known location from the one or more semiconductor wafers.

There is provided a technique that includes: displaying a recipe editing screen including at least a selection screen area that displays a parameter list for selection of parameters included in a recipe of a substrate processing apparatus, and a parameter editing screen area that edits the parameters; receiving a selection operation that selects an editing target parameter from the parameter list; displaying, on the parameter editing screen area, in an editable manner, a timing chart that is changeable at a time of each process in a series of processes included in a substrate processing process; and editing the editing target parameter by receiving an operation instruction to edit the timing chart displayed on the parameter editing screen area and changing the timing chart according to the operation instruction.

A method for process control in the manufacture of semiconductor devices including performing metrology on at least one Design of Experiment (DOE) semiconductor wafer included in a lot of semiconductor wafers, the lot forming part of a batch of semiconductor wafer lots, generating, based on the metrology, one or more correctables to a process used to manufacture the lot of semiconductor wafers and adjusting, based on the correctables, the process performed on at least one of; other semiconductor wafers included in the lot of semi-conductor wafers, and other lots of semiconductor wafers included in the batch.

An automatic detecting device and an automatic detecting method of a manufacturing equipment are provided. The automatic detecting method of the manufacturing equipment includes the following steps. A detection curve of the manufacturing equipment executing several recipe steps is obtained. The detection curve is aligned to the recipe steps, such that the detection curve is divided into several process segments. At least one peak or at least one valley in each of the process segments is searched to obtain several sub-step segments. According to the sub-step segments, a Fault Detection Classification analysis (FDC) is performed to obtain an analysis result. Based on the analysis result, a predict health information of the manufacturing equipment is outputted.