Gm Global Technolgoy Operations, Inc.

Chalmers University of Technology

Stephan R Biller

Fangming Gu

Chengyin Yuan

Chieh-Yi Jerry Yen

Richard C Immers

Magnus Johansson

Pulak Bandyopadhyay

Mikael Kjellgren

Bengt Erik Lennartson

Roland J Menassa

Leandro G Barajas

Jorge F Arinez

Guoxian Xiao

Robert Bruce Tilove

Jeffrey Tew

Qing Chang

Peiling Wu

Jerome O Schroeder

Robert K Baird, Jr

Daniel B Aufderheide

James Benjamin D'Arcy

Martin Fabian

Knut Akesson

Jing Liu

Petter Falkman

Alaa Elwany

Demet C Wood

A method for managing heat energy in a metal casting plant includes executing a local control optimization model to control mass of solid metal charges to each modular melting furnace. The local control optimization model is configured to achieve a commanded total mass of molten material and coincidentally minimize waste heat for each of the modular melting furnaces. The method for managing heat energy in the metal casting plant further includes executing a system control optimization model to manage operation of a heat energy recovery system. The system control optimization model is configured to manage the operation of the heat energy recovery system including transferring the waste heat from the modular melting furnaces to a plurality of heat demand centers while minimizing total loss of the waste heat in the metal casting plant.

Method and apparatus for managing heat energy in a metal casting plant

A method for testing the safety automation logic used in a manufacturing cell includes recording control signals of a safety-related component such as an E-Stop, light curtain, gate lock, or a safety mat using a host machine, and then disconnecting the component from the host machine. The recorded test signals are transmitted to an automation controller in accordance with a test scenario from a test scenario generator module (TSGM) to emulate operation of the component. The automation logic may be certified using the playback of the recorded test signals. A system for testing the safety automation logic includes the controller, host machine, and TSGM. The host machine records the control signals and plays back the test signals on the controller to emulate operation of the component. The automation control logic may be certified using the test signals, e.g., by comparing these to the test specification or standard.

Method and system for testing safety automation logic of a manufacturing cell

A system and method for calibrating an inventory planning model in a parts supply chain. The inventory planning model is determined based on certain input. A performance monitor measures the parts supply chain and provides performance metrics. The movement of parts through the parts supply chain is also monitored by a supply chain visibility system that keeps track of actual supply chain conditions. Both information on the actual supply chain conditions and the performance metrics is sent to a feedback filter that formats the information into an appropriate form. The feedback from the feedback filter is sent to a feedback controller. Based on the feedback information and the input, the feedback controller adjusts the input of the inventory planning model while determining how frequently the inventory planning model is calibrated and how the inventory planning model is calibrated.

Feedback control theoretic parts inventory management model

A system for generating platform-specific control logic implementation code for execution on a programmable logic controller (PLC) platform includes a plurality of processing layers. A first layer models generic control requirements as a unitary mathematical model (UMM). A second layer translates the UMM into generic control code describing a platform-independent set of generic control functions following an open structured language. A third layer automatically transforms the generic control functions into the platform-specific implementation code executable on different PLC platforms. A method of generating the implementation code includes modeling control requirements as a mathematical model, transforming the model into platform-independent control code describing a predetermined set of generic control functions using Extensible Markup Language (XML) schema, and automatically transforming the generic control functions into the implementation code.

Platform-independent method and system for deploying control logic programming

Manufacturing facility process optimization includes monitoring communication signals within a facility device network, analyzing work station specific patterns in the communication signals, developing operational dependencies for work stations based upon the work station specific patterns, and predictively evaluating impacts to the work stations of the proposed configuration of the manufacturing facility process based upon the operational dependencies.

Method for distributed hybrid emulation of manufacturing systems

An integrated real and virtual manufacturing automation system that employs a programmable logic controller that controls part flow between a real machine in the real world part of the system and a virtual machine in the virtual world part of the system using virtually coupled sensors and actuators. A real world sensor senses the position of the real world machine and a real world actuator actuates the real world machine. Likewise, a virtual world sensor senses the position of the virtual world machine and a virtual world actuator actuates the virtual world machine. An interface device transfers signals between the virtual world part of the system and the real world part of the system, and an input/output device processes signals sent to the programmable logic controller and signals sent from the programmable logic controller.

Methods of integrating real and virtual world using virtual sensor/actuator

A method of testing a physical manufacturing automation system for manufactured work pieces is provided via a testing system and includes connecting a computer-simulated manufacturing automation system to a controller of the physical manufacturing automation system, wherein the computer-simulated manufacturing automation system is configured to represent a portion of the physical manufacturing automation system, including a simulated work piece. The method then includes concurrently running the physical manufacturing automation system and the computer-simulated manufacturing automation system via the controller, with the physical automation system running in the absence of the physical work pieces.

Integrated testing system and method for validation of a manufacturing automation system

A method for generation of a sequence of operations for a manufacturing process including modeling the manufacturing process through a finite state machine to create a sequence of operations generator operative to generate a list of sequences of operations for the manufacturing process and utilizing the sequence of operations generator to input process information and automatically generate a list of sequences of operations.

Framework for automatic generation of sequence of operations

A method, system, and computer program product for automated root cause identification of a failure of a logic controller have been provided. The method includes receiving logic controller failure information, receiving a logic model of logic code for the logic controller, and mapping the logic controller failure information to the logic model to identify a logic failure model state. The method further includes determining a potential trigger of the failure of the logic controller as a root cause via tracing through at least one path in the logic model to reach the logic failure model state. The method also includes identifying the root cause in the logic code via mapping the root cause from the logic model to the logic code, and outputting the logic code with the identified root cause of the failure of the logic controller.

Automated root cause identification of logic controller failure

A method for generation of a control code set for a manufacturing process includes generating a list of sequences of operations with an automatic sequence of operations generator, selecting an optimized sequence of operations from the list of sequences of operations, and utilizing the optimized sequence of operations to generate the control code set.

Process for generating control sequence of operations

Methods, systems, and computer program products for controlling production systems. Methods include monitoring actual performance of a production system that includes a plurality of machines. The actual performance of the production system is compared to a planned level of performance of the production system. One or more short-term production constraints in the production system are identified in response to the actual performance being more than a threshold value away from the planned level of performance. A corrective action for the production system is determined to mitigate one or more of the short-term production constraints. The corrective action is applied to the production system.

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Birmingham, MI, United States of America

Stephan R Biller