Systems and methods for controlling device performance variability during manufacturing of a device on wafers are disclosed. The system includes a process platform, on-board metrology (OBM) tools, and a first server that stores a machine-learning based process control model. The first server combines virtual metrology (VM) data and OBM data to predict a spatial distribution of one or more dimensions of interest on a wafer. The system further comprises an in-line metrology tool, such as SEM, to measure the one or more dimensions of interest on a subset of wafers sampled from each lot. A second server having a machine-learning engine receives from the first server the predicted spatial distribution of the one or more dimensions of interest based on VM and OBM, and also receives SEM metrology data, and updates the process control model periodically (e.g., to account for chamber-to-chamber variability) using machine learning techniques.

An expandable valved conduit for pediatric right ventricular outflow tract (RVOT) reconstruction is disclosed. The valved conduit may provide long-term patency and resistance to thrombosis and stenosis. The valved conduit may enlarge radially and/or longitudinally to accommodate the growing anatomy of the patient. Further, a method is disclosed for the manufacture of the valved conduit based in part on a plastically deformable biocompatible polymer and a computer-optimized valve design developed for such an expandable valved conduit.

A control system includes a drive-side control device and a host-side control device. The drive-side control device has a drive-side control structure including a drive-side feedback system and a drive-side control model part and configured so as to be capable of model tracking control in accordance with a control model which the drive-side control model part has. The host-side control device has a host-side control structure including a host-side control model part a host-side correcting signal based on a deviation between an output of the host-side control model part and the operation command signal is fed back to an input side of the host-side control model part, and a corrected command signal generated based on the host-side correcting signal that is fed back and the operation command signal is input to the host-side control model part. The corrected command signal is further input to the drive-side control structure.

A pick and place nozzle performance analytics system streams production data from pick and place machines used in electronic assembly to a cloud platform as torrential data streams, and performs analytics on the production data to track, visualize, and predict performance of individual nozzles in terms of rejects or miss-picks. The analytics system generates a performance vector for each nozzle based on the collected production data, the performance vector tracking both the accumulated rejects and the percentage of rejects as respective dimensions of an x-y plane. The system monitors and analyzes the trajectory of this vector in the x-y plane to predict when performance degradation of the nozzle will reach a critical threshold. In response to predicting that nozzle performance degradation will exceed a threshold at a future time, the system can generate and deliver notifications to appropriate client devices.

A simulation device includes: a simulation system including a predetermined feedback system having at least a predetermined control block structure corresponding to a predetermined device-side configuration; a holding unit holding impulse response information for calculation that is information on an impulse response relating to the predetermined device-side configuration; a first response calculation unit calculating a time response of the predetermined device-side configuration to a predetermined input value by convolution processing using the impulse response information for calculation and the predetermined input value; and a second response calculation unit calculating a response of the simulation system to a command value input to the simulation system by using the time response of the predetermined device-side configuration calculated by the first response calculation unit. According to this configuration, simulation accuracy of a control system is improved.

Techniques for comparing two or more sessions of a manufacturing process are described. In one example, a particular metric associated with execution of a manufacturing process is identified, the particular metric evaluated in a plurality of manufacturing process sessions for at least one manufacturing process. A particular session particular session from the plurality of manufacturing process sessions is selected as a baseline session, wherein at least a portion of the remaining plurality of manufacturing process sessions are to be compared to the baseline session. In a primary portion of a presentation area, a visualization of the values of the identified metric associated with the particular session are presented. In a secondary portion of the presentation area, visualizations of the values of the identified metric associated with at least a portion of the other manufacturing process sessions from the plurality of sessions is presented.

The invention concerns predominantly enclosed spaces, typically buildings, which are at least exposed to directionally and temporally varying levels of solar electromagnetic radiation as well as temporally varying levels of ambient air temperature and ambient air flow velocity and direction. Methods for at least approximating any one or any combination of system targets of a) reducing the average energy expenditure for keeping at least one primary compartment of a building within a desired temperature range by means of active air conditioning, or b) reducing temperature variations during a typical 24-hour cycle within said at least one primary compartment of said building, or c) reducing one or both of the average temperature or the peak temperature of said at least one primary compartment of said building. Methods for at least partially increasing the typical lifetime of some components of buildings and thus reducing resources associated with maintaining at least some buildings function.

Embodiments disclosed herein generally relate to methods, systems, and non-transitory computer readable medium for scheduling a substrate processing sequence in an integrated substrate processing system. A client device assigns a processing sequence to each substrate in a batch of substrates to be processed. The client device assigns a processing chamber to each process in the process sequence for each processing chamber in the integrate substrate processing system. The client device generates a processing model for the batch of substrates. The processing model defines a start time for each substrate in each processing chamber. The client device generates a timetable for the batch of semiconductor substrates based off the processing model. The client device processes the batch of substrates in accordance with the timetable.

An industrial data presentation system leverages structured data types defined on industrial devices to generate and deliver meaningful presentations of industrial data. Industrial devices are configured to support structured data types referred to as basic information data types (BIDTs) comprising a finite set of structured information data types, including a rate data type, a state data type, an odometer data type, and an event data type. The BIDTs can be referenced by both automation models of an industrial asset and non-automation models of the asset, allowing data points of both types of models to be easily linked using a common data source nomenclature.

A method and a corresponding system and computer program product are provided. A model of an object to be manufactured is obtained. Information about one or more available machine tools and one or more available cutting tools is obtained. A geometric feature to be machined as part of manufacturing the object is identified. A database including strategies for machining different geometric features is accessed. The database includes a plurality of strategies defining different ways of machining the identified geometric feature. One or more strategies are selected from the plurality of strategies based on the obtained information. A computer simulation is performed for the one or more selected strategies, and user instructions responsive to the computer simulation are received. Instructions for causing one or more machine tools to manufacture the object via subtractive manufacturing are provided based on the user instructions and a strategy of the one or more selected strategies.