Predictive multi-stage modelling for complex semiconductor device manufacturing process control is provided. In one aspect, a method of predictive multi-stage modelling for controlling a complex semiconductor device manufacturing process includes: collecting geometrical data from metrology measurements made at select stages of the manufacturing process; and making an outcome probability prediction at each of the select stages using a multiplicative kernel Gaussian process, wherein the outcome probability prediction is a function of a current stage and all prior stages. Machine-learning models can be trained for each of the select stages of the manufacturing process using the multiplicative kernel Gaussian process. The machine-learning models can be used to provide probabilistic predictions for a final outcome in real-time for production wafers. The probabilistic predictions can then be used to select production wafers for rework, sort, scrap or disposition.

A design support system for permitting a design that easily meets desired conditions regarding an entire item group is provided. An automatic estimation system acting as the design support system comprises: an item recognition section that recognizes each of the items included in the item group by individually recognizing elements making up the item; a designated condition recognition section that recognizes a designated condition from the manufacturing conditions; and a recommended-to-be-examined element recognition section that recognizes, with respect to the designated condition recognized, the element corresponding to any of the manufacturing conditions that is recommended to be examined for changes. The recommended-to-be-examined element recognition section displays a model of the item group by highlighting the element for which the manufacturing condition is recommended to be examined for changes.

A partial bespoke protective sports equipment to be worn by a player engaged in a sporting activity is provided. The partial bespoke sports equipment system includes methods for acquiring, storing and processing a player's unique data, namely the anatomical features of the body part against which the partial bespoke equipment is worn. The systems also includes methods of using the player's unique data to manufacture the partial bespoke protective equipment with a partially custom formed internal padding. The system and method allows for the design and manufacture of partial bespoke protective sports equipment that is purposely designed and manufactured to substantially match the anatomical specifications of the player's body part.

A method includes: identifying attributes that are associated with cell edges of abutted cells in a layout of a semiconductor device, wherein the attributes include at least one of terminal types of the cell edges; determining at least one minimal boundary leakage of the abutted cells based on the attributes, for adjustment of the layout of the semiconductor device. A system is also disclosed herein.

A method of manufacturing an integrated circuit includes adjusting a first spacing between an adjacent pair of routing tracks in a first set of routing tracks to be equal to a second spacing, adjusting a third spacing between an adjacent pair of routing tracks in a second set of routing tracks to be equal to a fourth spacing, placing a first and second pair of conductive patterns on the corresponding first and second set of routing tracks, forming a first set of conductive structures based on the first pair of conductive patterns, and a second set of conductive structures based on the second pair of conductive patterns. A first and second cell have a same cell height that is a non-integer multiple of a minimum pitch. One spacing of a first set of spacings is different from another spacing of the first set of spacings.

In an aspect an apparatus for analyzing machinability of a part for manufacture, wherein the apparatus comprises a processor. The processor is configured to receive a representative part model of a part for manufacture. The processor may also be configured to extract a semantic datum from the print of the part for manufacture. A machinability datum is determined as a function of the semantic datum. A manufacturing quote is generated as a function of the machinability datum.

In an example, a method includes obtaining a compensation model characterising a relationship between a location of an object within a fabrication chamber of an additive manufacturing apparatus and a geometrical compensation to be applied to a model of said object, wherein different geometrical compensation values are associated with different locations. In some examples the method further includes determining a magnitude of a dimension parameter of each object of a set of objects to be generated in a build operation. The method may include determining a spatial arrangement of objects to be generated within the build volume, based on the magnitude of the dimension parameters and the geometrical compensation values for an intended location of object generation in the spatial arrangement.

Example embodiments describe a computer-implemented method for balancing an electrochemical deposition of metal on a PCB substrate; the method including i) obtaining a layout of the metal on the PCB substrate comprising at least one active area having a circuit layout and a balancing area available for the balancing; ii) dividing the substrate area in a plurality of finite elements; iii) determining active metal fractions from the layout for the respective finite elements; iv) determining metal balancing fractions covering respective finite elements in the balancing area based on the active metal fractions in finite elements in the at least one active area surrounding the respective finite element.

Disclosed is an operating method of an electronic device which includes receiving a design layout for manufacturing the semiconductor device, generating a first layout by performing machine learning-based process proximity correction (PPC), generating a second layout by performing optical proximity correction (OPC), and outputting the second layout for a semiconductor process. The generating of the first layout includes generating a first after cleaning inspection (ACI) layout by executing a machine learning-based process proximity correction module on the design layout, generating a second after cleaning inspection layout by adjusting the design layout based on a difference of the first after cleaning inspection layout and the design layout and executing the process proximity correction module on the adjusted layout, and outputting the adjusted layout as the first layout, when a difference between the second after cleaning inspection layout and the design layout is smaller than or equal to a threshold value.

A system for operating a configuration platform. The system comprising a conversion pipeline, the conversion pipeline allowing converting a first set of data associated with a computer-aided design (CAD) system into polygon meshes suitable for rendering of the portion of a monument and configuration data. The system also comprising a content management system, the content management system storing the polygon meshes and the configuration data; and a 3D real-time engine, the 3D real-time engine allowing to determine, based on the configuration data, at least one of the positioning of the monument, the material surface associated with the monument, the material grain direction associated with the monument, the lighting associated with the monument, the annotations associated with the monument, the alternate states associated with the monument and the kinematic sequence associated with the monument; and to render the portion of the monument by the 3D real-time engine.