Patent application number | Description | Published |
20150109223 | HAPTIC ELECTROMAGNETIC ACTUATOR - A haptic electromagnetic actuator for track pad is provided. The actuator includes an array of electromagnets with alternating South and North poles on a first end, each magnet comprising a metal core and an electrical wire around the metal core. The array of magnets is coupled to a base plate on a second end opposite to the first end. The actuator also includes an attraction plate at a distance from the first end of the array of the magnets such that the attraction plate moves toward the magnets when an electrical current flows through the electrical wire around the metal core and moves away from the magnets when the current becomes zero. The array of magnets is configured to form a uniform gap from the attraction plate. | 04-23-2015 |
20150130730 | FEEDBACK SYSTEMS FOR INPUT DEVICES - An electronic device including a processor, a display screen in communication with the processor, a track pad in communication with the processor including a movable surface that is selectively movable in at least one direction to provide feedback to a user, and a feedback system in communication with the processor including a feedback sensor. The feedback sensor determines a movement characteristic of the movable surface and the processor selectively adjusts at least one setting of the track pad based on the movement characteristic. | 05-14-2015 |
20160091972 | HAPTIC FEEDBACK ASSEMBLY - A haptic feedback assembly includes interconnections for mechanically and electrically securing a haptic actuator in a track pad assembly so as to securely and efficiently provide haptic feedback to a user. | 03-31-2016 |
20160103545 | Temperature Compensating Transparent Force Sensor Having a Complliant Layer - An optically transparent force sensor that may compensate for environmental effects, including, for example, variations in temperature of the device or the surroundings. In some examples, two force-sensitive layers are separated by a compliant layer. The relative electrical response of the two force-sensitive layers may be used to compute an estimate of the force of a touch that reduces the effect of variations in temperature. In some examples, piezoelectric films having anisotropic strain properties are used to reduce the effects of temperature. | 04-14-2016 |
Patent application number | Description | Published |
20150081966 | DENSE TREE VOLUME METADATA ORGANIZATION - In one embodiment, a node coupled to one or more storage devices executes a storage input/output (I/O) stack having a volume layer. The volume layer manages volume metadata embodied as mappings from offsets of a logical unit (LUN) to extent keys associated with storage locations for extents on the one or more storage devices. Volume metadata is maintained as a dense tree metadata structure representing successive points in time. The dense tree metadata structure has multiple levels, wherein a top level of the dense tree metadata structure represents newer volume metadata changes and descending levels of the dense tree metadata structure represent older volume metadata changes. The node accesses a latest version of changes to the volume metadata by searching from the top level to the descending levels in the dense tree metadata structure. | 03-19-2015 |
20150134616 | SNAPSHOTS AND CLONES OF VOLUMES IN A STORAGE SYSTEM - In one embodiment, snapshots and/or clones of storage objects are created and managed by a volume layer of a storage input/output (I/O) stack executing on one or more nodes of a cluster. Illustratively, the snapshots and clones may be represented as independent volumes, and embodied as respective read-only copies (snapshots) and read-write copies (clones) of a parent volume. Volume metadata is illustratively organized as one or more multi-level dense tree metadata structures, wherein each level of the dense tree metadata structure (dense tree) includes volume metadata entries for storing the metadata. Each snapshot/clone may be derived from a dense tree of the parent volume (parent dense tree). Portions of the parent dense tree may be shared with the snapshot/clone. | 05-14-2015 |
20150134879 | SNAPSHOTS AND CLONES OF VOLUMES IN A STORAGE SYSTEM - In one embodiment, a node coupled to one or more storage devices executes a storage input/output (I/O) stack having a volume layer that manages volume metadata. The volume metadata is organized as one or more dense tree metadata structures having a top level residing in memory and lower levels residing on the one or more storage devices. The dense tree metadata structures include a first dense tree metadata structure associated with a parent volume and a second dense tree metadata structure associated with a copy of the parent volume. The top level of the first dense tree metadata structure may be copied to the second dense tree metadata structure. The lower levels of the first dense tree metadata structure are initially shared with the second dense tree metadata structure. The shared lower levels may eventually be split as the parent volume diverges from the copy of the parent volume. | 05-14-2015 |
20150193156 | NVRAM DATA ORGANIZATION USING SELF-DESCRIBING ENTITIES FOR PREDICTABLE RECOVERY AFTER POWER-LOSS - In one embodiment, a node coupled to a plurality of solid state drives (SSDs) executes a storage input/output (I/O) stack having a plurality of layers. Write data associated with one or more write requests to the SSDs is stored in a volatile log. The write data is organized into one or more extents that are copied to the SSDs. The volatile log has a front-end and a set of records with metadata. The metadata includes a head offset referencing an initial record and a tail offset referencing a final record. A portion of the one or more write requests including the write data is copied to a non-volatile log maintained in a non-volatile random access memory (NVRAM). The front-end and the set of records from the volatile log are copied, but the head offset and the tail offset are not, to reduce an amount of metadata copied to the NVRAM. | 07-09-2015 |
20150370485 | SNAPSHOTS AND CLONES OF VOLUMES IN A STORAGE SYSTEM - In one embodiment, a node coupled to one or more storage devices executes a storage input/output (I/O) stack having a volume layer, a persistence layer and an administration layer that interact to create a copy of a parent volume associated with a storage container on the one or more storage devices. A copy create start message is received at the persistence layer from the administration layer. The persistence layer ensures that dirty data for the parent volume is incorporated into the copy of the parent volume. New data for the parent volume received at the persistence layer during creation of the copy of the parent volume is prevented from incorporation into the copy of the parent volume. A reply to the copy create start message is sent from the persistence layer to the administration layer to initiate the creation of the copy of the parent volume at the volume layer. | 12-24-2015 |
20150370498 | NVRAM DATA ORGANIZATION USING SELF-DESCRIBING ENTITIES FOR PREDICTABLE RECOVERY AFTER POWER-LOSS - In one embodiment, a node coupled to a plurality of storage devices executes a storage input/output (I/O) stack having a plurality of layers including a persistence layer. A portion of non-volatile random access memory (NVRAM) is configured as one or more logs. The persistence layer cooperates with the NVRAM to employ the log to record write requests received from a host and to acknowledge successful receipt of the write requests to the host. The log has a set of entries, each entry including (i) write data of a write request and (ii) a previous offset referencing a previous entry of the log. After a power loss, the acknowledged write requests are recovered by replay of the log in reverse sequential order using the previous record offset in each entry to traverse the log. | 12-24-2015 |
Patent application number | Description | Published |
20090240366 | METHOD AND SYSTEM FOR DETECTION OF TOOL PERFORMANCE DEGRADATION AND MISMATCH - Autonomous biologically based learning tool system(s) and method(s) that the tool system(s) employs for learning and analysis of performance degradation and mismatch are provided. The autonomous biologically based learning tool system includes (a) one or more tool systems that perform a set of specific tasks or processes and generate assets and data related to the assets that characterize the various processes and associated tool performance; (b) an interaction manager that receives and formats the data, and (c) an autonomous learning system based on biological principles of learning. Objectively generated knowledge gleaned from synthetic or production data can be utilized to determine a mathematical relationship among a specific output variable and a set of associated influencing variables. The generated relationship facilitates assessment of performance degradation of a set of tools, and performance mismatch among tools therein. | 09-24-2009 |
20100138026 | METHOD AND APPARATUS FOR SELF-LEARNING AND SELF-IMPROVING A SEMICONDUCTOR MANUFACTURING TOOL - System(s) and method(s) for optimizing performance of a manufacturing tool are provided. Optimization relies on recipe drifting and generation of knowledge that capture relationships among product output metrics and input material measurement(s) and recipe parameters. Optimized recipe parameters are extracted from a basis of learned functions that predict output metrics for a current state of the manufacturing tool and measurements of input material(s). Drifting and learning are related and lead to dynamic optimization of tool performance, which enables optimized output from the manufacturing tool as the operation conditions of the tool changes. Features of recipe drifting and associated learning can be autonomously or externally configured through suitable user interfaces, which also can be drifted to optimize end-user interaction. | 06-03-2010 |
20110131162 | AUTONOMOUS BIOLOGICALLY BASED LEARNING TOOL - An autonomous biologically based learning tool system and a method that the tool system employs for learning and analysis are provided. The autonomous biologically based learning tool system includes (a) one or more tool systems that perform a set of specific tasks or processes and generate assets and data related to the assets that characterize the various processes and associated tool performance; (b) an interaction manager that receives and formats the data, and (c) an autonomous learning system based on biological principles of learning. The autonomous learning system comprises a memory platform and a processing platform that communicate through a network. The network receives data from the tool system and from an external actor through the interaction manager. Both the memory platform and the processing platform include functional components and memories that can be defined recursively. Similarly, the one or more tools can be deployed recursively, in a bottom-up manner in which an individual autonomous tools is assembled in conjunction with other (disparate or alike) autonomous tools to form an autonomous group tool, which in turn can be assembled with other group tools to form a conglomerated autonomous tool system. Knowledge generated and accumulated in the autonomous learning system(s) associated with individual, group and conglomerated tools can be cast into semantic networks that can be employed for learning and driving tool goals based on context. | 06-02-2011 |
20120185813 | TOOL PERFORMANCE BY LINKING SPECTROSCOPIC INFORMATION WITH TOOL OPERATIONAL PARAMETERS AND MATERIAL MEASUREMENT INFORMATION - System(s) and method(s) are provided for adjustment and analysis of performance of a tool through integration of tool operational data and spectroscopic data related to the tool. Such integration results in consolidated data that enable, in part, learning at least one relationship amongst selected portions of the consolidated data. Learning is performed autonomously without human intervention. Adjustment of performance of the tool relies at least in part on a learned relationship and includes generation of process recipe parameter(s) that can adjust a manufacturing process in order to produce a satisfactory tool performance in response to implementation of the manufacturing process. A process recipe parameter can be generated by solving an inverse problem based on the learned relationship. Analysis of performance of the tool can include assessment of synthetic performance scenarios, identification of spectroscopic condition(s) that affect performance, and extraction of endpoints based at least on time dependence spectroscopic data. | 07-19-2012 |
20120209798 | AUTONOMOUS BIOLOGICALLY BASED LEARNING TOOL - An autonomous biologically based learning tool system and a method that the tool system employs for learning and analysis are provided. The autonomous biologically based learning tool system includes (a) one or more tool systems that perform a set of specific tasks or processes and generate assets and data related to the assets that characterize the various processes and associated tool performance; (b) an interaction manager that receives and formats the data, and (c) an autonomous learning system based on biological principles of learning. The autonomous learning system comprises a memory platform and a processing platform that communicate through a network. Both the memory platform and the processing platform include functional components and memories that can be defined recursively. Knowledge generated and accumulated in the autonomous learning system(s) can be cast into semantic networks that can be employed for learning and driving tool goals based on context. | 08-16-2012 |
20120242667 | BIOLOGICALLY BASED CHAMBER MATCHING - The subject disclosure relates to automatically learning relationships among a plurality of manufacturing tool parameters as applied to arbitrary semiconductor manufacturing tools and a graphical user interface that is supported, at least in part, by an autonomous learning system. The graphical user interface can create one or more matrixes based on received data and can further generate additional matrices by transforming the one or more matrixes. A series of windows can be output, wherein the series of windows, provide performance analysis that comprises a matching between a focus chamber and a reference chamber. In an aspect, the focus chamber and the reference chamber can be different chambers. In another aspect, the focus chamber and the reference chamber can be the same chamber, which provides analysis of the deterioration in performance of the same chamber over time. | 09-27-2012 |
20130151447 | METHOD AND APPARATUS FOR SELF-LEARNING AND SELF-IMPROVING A SEMICONDUCTOR MANUFACTURING TOOL - Performance of a manufacturing tool is optimized. Optimization relies on recipe drifting and generation of knowledge that capture relationships among product output metrics and input material measurement(s) and recipe parameters. Optimized recipe parameters are extracted from a basis of learned functions that predict output metrics for a current state of the manufacturing tool and measurements of input material(s). Drifting and learning are related and lead to dynamic optimization of tool performance, which enables optimized output from the manufacturing tool as the operation conditions of the tool changes. Features of recipe drifting and associated learning can be autonomously or externally configured through suitable user interfaces, which also can be drifted to optimize end-user interaction. | 06-13-2013 |
20140135970 | METHOD AND APPARATUS FOR AUTONOMOUS TOOL PARAMETER IMPACT IDENTIFICATION SYSTEM FOR SEMICONDUCTOR MANUFACTURING - A system and method for autonomously determining the impact of respective tool parameters on tool performance in a semiconductor manufacturing system is provided. A parameter impact identification system receives tool parameter and tool performance data for one or more process runs of the semiconductor fabrication system and generates a separate function for each tool parameter characterizing the behavior of a tool performance indicator in terms of a single one of the tool parameters. Each function is then scored according to how well the function predicts the actual behavior of the tool performance indicator, or based on a determined sensitivity of the tool performance indicator to changes in the single tool parameter. The tool parameters are then ranked based on these scores, and a reduced set of critical tool parameters is derived based on the ranking. The tool performance indicator can then be modeled based on this reduced set of tool parameters. | 05-15-2014 |
20140163712 | METHOD AND APPARATUS FOR AUTONOMOUS IDENTIFICATION OF PARTICLE CONTAMINATION DUE TO ISOLATED PROCESS EVENTS AND SYSTEMATIC TRENDS - A system and method for autonomously tracing a cause of particle contamination during semiconductor manufacture is provided. A contamination analysis system analyzes tool process logs together with particle contamination data for multiple process runs to determine a relationship between systematic particle contamination levels and one or more tool parameters. This relationship is used to predict expected contamination levels associated with regular usage of the tool, and to identify which tool parameters have the largest impact on expected levels of particle contamination. The contamination analysis system also identifies process logs showing unexpected deviant particle contamination levels that exceed expected contamination levels, and traces the cause of the deviant particle contamination to particular process log parameter events. | 06-12-2014 |
20140304196 | BIOLOGICALLY BASED CHAMBER MATCHING - The subject disclosure relates to automatically learning relationships among a plurality of manufacturing tool parameters as applied to arbitrary semiconductor manufacturing tools and a graphical user interface that is supported, at least in part, by an autonomous learning system. The graphical user interface can create one or more matrixes based on received data and can further generate additional matrices by transforming the one or more matrixes. A series of windows can be output, wherein the series of windows, provide performance analysis that comprises a matching between a focus chamber and a reference chamber. In an aspect, the focus chamber and the reference chamber can be different chambers. In another aspect, the focus chamber and the reference chamber can be the same chamber, which provides analysis of the deterioration in performance of the same chamber over time. | 10-09-2014 |
20150161520 | SYSTEM AND METHOD FOR LEARNING AND/OR OPTIMIZING MANUFACTURING PROCESSES - A system and method for learning and/or optimizing processes related to semiconductor manufacturing is provided. A learning component generates a set of candidate process models based on process data associated with one or more fabrication tools. The learning component also selects a particular process model from the set of candidate process models that is associated with lowest error. An optimization component generates a set of candidate solutions associated with the particular process model. The optimization component also selects a particular solution from the set of candidate solutions based on a target output value and an output value associated with the particular solution. | 06-11-2015 |
20150332167 | SYSTEM AND METHOD FOR MODELING AND/OR ANALYZING MANUFACTURING PROCESSES - Systems and techniques for modeling and/or analyzing manufacturing processes are presented. A dataset component generates a plurality of binary classification datasets based on process data associated with one or more fabrication tools. A learning component generates a plurality of learned models based on the plurality of binary classification datasets and applies a weight to the plurality of learned models based on a number of data samples associated with the plurality of binary classification datasets to generate a weighted plurality of learned models. A merging component merges the weighted plurality of learned models to generate a process model for the process data. | 11-19-2015 |