Siemens Aktiengesellschaft

Siemens Corporate Research, Inc.

Siemens Industry, Inc.

Siemens Corporation

Siemens Enterprise Communications Gmbh & Co. Kg

Siemens Energy, Inc.

University System of Maryland

Siemens Corporation Research, Inc.

Other

Siemens Medical Solutions Usa, Inc.

Georgia Tech Research Corporation

Siemens Audiologische Technik Gmbh

Siemens Medical Instruments Pte. Ltd.

Siemens Enterprise Communications, Inc.

Justinian Rosca

Radu Victor Balan

Heiko Claussen

Lingyun Wang

Steffen Lamparter

Michael T Loiacono

George Lo

Nancy H Ulerich

Nazif Cihan Tas

Scott Rickard

Upul P DeSilva

Octavian Sarca

Michelle Xiaohong Yan

Amar H Patel

Dorin Comaniciu

Osman Ahmed

Juan L Aparicio Ojea

Thomas Gruenewald

Chellury R Sastry

Tong Fang

Eghart Fischer

Henning Puder

Arquimedes Martinez Canedo

Ti-chiun Chang

Edward David Thompson

Thomas Hubauer

Hartmut Ludwig

Dragan Obradovic

Sanjeev Srivastava

Livio Dalloro

Sandra Sudarsky

Mikhail Roshchin

Hans-Gerd Brummel

Volkmar Hamacher

Stephen Price Masticola

Sindhu Suresh

Juan Aparicio

Chih-Wei Huang

Alexander N Jourjine

Hasan Sinan Bank

Stephan Grimm

Raffaello Lepratti

Zainul Momin

Christian P Schultz

Kurt Dirk Bettenhausen

Tao Cui

Emmanuel Bisse

Thomas R Kurfess

Steven A Russell

Yenming Mark Lai

Jenq-Neng Hwang

Bernardo Hermont

Joseph &Oacute; Ruanaidh

Scott Thurston Rickard, Jr

Stephanie Locks

Aoyu Chen

Dongmin Han

Nuodi Huang

Roby Lynn

Carolyn Joiner

Thomas Wiese

Richard John LeBlanc

David Volk Beard

Peter Casazza

Dan Edidin

Liang Hong

Christophe Beaugeant

Bogdan Rosca

Ning Ping Fan

Thomas Kurfess

Richard John Leblanc

Eghard Fischer

Inga Holube

Christian Darken

Thomas Petsche

Michael Loiacono

A system for autonomously providing functionality to a computerized control system includes a logic controller running a first computer application relating to an operations system and an application manager that receives requests for functionality from the first computer application. A remote marketplace client is in communication with the application manager and a remote marketplace that offers computer applications for providing a plurality of functionalities relating to the operations system. A computer application repository stores computer applications providing functionality of the operations system and responsive to receiving the request for functionality the application manager forwards the request to the remote marketplace client. The remote marketplace client queries the remote marketplace for the requested functionality and provides results of the query to the application manager. The application manager performs logic operations on the query results to identify an application to provide the requested functionality. The identified application is downloaded from the marketplace.

Apparatus and method for autonomously adding and removing of functionality in programmable logic controllers (PLCs)

An embedded control system for a field device of an automation system includes: a diagnostic application interface to a backend server for signal analytics information, complex event pattern information, and diagnostic information; a physical process interface to a signal source for transferring signal data; a signal evaluation component for comparing received signal analytics information with received signal data to identify a first and a second event; an event processing component for applying received event pattern information to the first and second identified events to identify a first classified event; and a diagnostic reasoning component for deriving causal dependencies between the first classified event and a further classified event with regard to diagnostic information to identify a root cause for the first classified event or predict an impact of the first classified event.

Smart embedded control system for a field device of an automation system

A computer-implemented method for detecting cyber-attacks affecting a computing device includes retrieving a plurality of sensor datasets from a plurality of sensors, each sensor dataset corresponding to involuntary emissions from the computing device in a particular modality and extracting a plurality of features from the plurality of sensor datasets. One or more statistical models are applied to the plurality of features to identify one or more events related to the computing device. Additionally, a domain-specific ontology is applied to designate each of the one or more events as benign, failure, or a cyber-attack.

Critical infrastructure forensics

The controlling method uses a control specification. In the method, at least part of the progression of the controlling process is monitored, and at least one quality criterion characterizing the quality of the control method is determined, (e.g., ascertained), in accordance with the progression. The control specification is adjusted in accordance with the quality criterion.

Controlling methods, control systems, and plants using semantic models for quality criteria or adaptation of control rules

A method of operating an intelligent programmable logic controller (PLC) as part of a production process within an automation system includes the intelligent PLC receiving automation system data and a semantic context model comprising a plurality of ontologies providing formal specifications of conceptual entities associated with the automation system. The intelligent PLC creates one or more semantic annotations for the automation system data using the semantic context model. These semantic annotations are stored along with the automation system data in a non-volatile storage medium included in the intelligent PLC.

Rich contextualization of automation data

A computer-implemented method of identifying federations of manufacturing apps using House of Quality (HoQ) analysis includes receiving user request information comprising a plurality of desired functions and an importance value for each of the plurality of desired functions and generating a correlation matrix between the plurality of apps, wherein each element of the correlation matrix indicates a degree of correlation between a pair of apps. A relationship matrix is generated which comprises numerical values indicating relationships between a plurality of apps and the plurality of desired functions, wherein each column of relationship matrix is associated with an app and each row is associated with a desired function. Next, a weighted matrix is created by multiplying each row in the relationship matrix by the importance value corresponding to the desired function associated with the row. The numerical values in each column of the weighted matrix are aggregated to determine a total value for each of the plurality of apps. A federation of apps is identified based on the correlation matrix and the total values determined for the plurality of apps.

House of quality for federated manufacturing apps

A method of operating an intelligent programmable logic controller includes executing, by a processor included in the intelligent programmable logic controller, a control program. A non-volatile storage medium included in the intelligent programmable logic controller stores a control model comprising control knowledge related to the control program. The control model is used to perform a monitoring operation related to execution of the control program on the intelligent programmable logic controller.

Control contextualization and reasoning about control

A method of operating an intelligent programmable logic controller over a plurality of scan cycles includes the intelligent programmable logic controller selecting one or more soft-sensors available in a control program corresponding to a production unit, each soft-sensor comprising a local parameter or variable used by the control program. The intelligent programmable logic controller determines updated soft-sensor values corresponding to the one or more soft-sensors during each scan cycle and stores those values during each scan cycle on a non-volatile computer-readable storage medium operably coupled to the intelligent programmable logic controller. Additionally, the intelligent programmable logic controller annotates the updated soft-sensor values with automation system context information to generate contextualized data.

Using soft-sensors in a programmable logic controller

Systems, techniques, and computer-program products are provided for tracking and traceability of parts of a finished product. In some embodiments, the tracking and traceability generates streams of semantic data obtained from an imaging sensor system that records the execution of a manufacturing process in industrial equipment. The execution of the manufacturing process yields a finished product from initial materials and/or parts. The tracking and traceability also implements artificial reasoning about the execution of the manufacturing process to generate assertions that characterize the execution of the manufacturing process. Semantic data and assertions can be aggregated into a digital trace record that tracks a defined component of the finished product throughout the execution of the manufacturing process and permit tracing the component to a defined event within the manufacturing process.

Tracking and traceability of parts of a product

A computer-implemented method for detecting faults and events related to a system includes receiving sensor data from a plurality of sensors associated with the system. A hierarchical failure model of the system is constructed using (i) the sensor data, (ii) fault detector data, (iii) prior knowledge about system variables and states, and (iii) one or more statistical descriptions of the system. The failure model comprises a plurality of diagnostic variables related to the system and their relationships. Probabilistic reasoning is performed for diagnostic or prognostic purposes on the system using the failure model to derive knowledge related to potential or actual system failures.

Failure models for embedded analytics and diagnostic/prognostic reasoning

A system for storing data in an industrial production environment includes a distributed database stored on a plurality of intelligent programmable logic controller devices. Each respective intelligent programmable logic controller device includes a volatile computer-readable storage medium containing a process image area; a non-volatile computer-readable storage medium; a control application; an input/output component; a historian component; and a distributed data management component. The control application is configured to provide operating instructions to a production unit. The input/output component is configured to update the process image area during each scan cycle with data associated with the production unit. The historian component is configured to store automation system data including the operating instructions and contents of the process image area on the non-volatile computer-readable storage medium. The distributed data management component is configured to facilitate distributed operations involving the automation system data by the plurality of intelligent programmable logic controller devices.

Automation and control distributed data management systems

A method of operating an intelligent programmable logic controller over a plurality of scan cycles includes the intelligent programmable logic controller executing a control program and one or more reasoning algorithms for analyzing data received and transmitted by the intelligent programmable logic controller. The intelligent programmable logic controller receives one or more user-specified declarative knowledge models from an external source via a deployment interface included in the intelligent programmable logic controller. The intelligent programmable logic controller dynamically modifies the reasoning algorithms during runtime of the control program based on the user-specified declarative knowledge models.

Knowledge-based programmable logic controller with flexible in-field knowledge management and analytics

Systems and methods are provided for modeling and simulating a communication network operating under at least one communication protocol, which supports a Smart Grid electricity network. Communication performance data of the communication network are generated by a processor based on operating behavior of the Smart Grid with a plurality of assets under a first condition. Devices in the Smart grid are grouped in bins for rapid modeling. One or more different configurations of the communication network are entered into the processor and related performance data is also generated. Network configurations are compared based on the generated performance data which may include end-to-end delay and reception rate. Processor based systems to perform modeling methods are also provided.

Smart grid communication assessment and co-simulation tool

A method of compressing signal data in an intelligent programmable logic controller includes the controller creating a process image area in a volatile computer-readable storage medium operably coupled to the controller. The intelligent programmable logic controller updates the process image area with contents comprising signal data associated with a production unit and applies a compression algorithm to the contents to generate compressed signal data. The compressed signal data is stored on a non-volatile computer-readable storage medium operably coupled to the controller. The controller annotates the signal data with automation system context information to generate contextualized data. Next, the controller performs a statistical comparison of the signal data and the compressed signal data to generate statistical comparison results. Then, one or more compression parameters used by the compression algorithm may be automatically adjusted based on at least one of the statistical comparison and the contextualized data.

Automatic compression algorithm selection and parameter tuning based on contextual knowledge

A method of calibrating transceiver positions inside an acoustic pyrometry measuring vessel that contains a plurality of transceivers, includes determining () a speed of sound in the acoustic pyrometry measuring vessel from a temperature and gas composition of a gas inside the acoustic pyrometry measuring vessel, acquiring () time-of-flight (TOFs) &#x394;timeasurements from a plurality of pairs i,j of transceivers inside the acoustic pyrometry measuring vessel, estimating () a radius of the acoustic pyrometry measuring vessel from an average of the acquired TOF measurements, and using () an estimated radius of the acoustic pyrometry measuring vessel to estimate errors &#x394;&#x3b8;j of displacement angles of the transceivers.

Fully automated calibration for acoustic pyrometry

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West Windsor, NJ, United States of America

Justinian Rosca