Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method is provided for certifying safety logic code in a manufacturing automation system. A plurality of safety related test scenarios is provided for testing the safety logic code in the manufacturing automation system. A processing unit is configured for communication with the logic controller. The processing unit generates logic input signals in response to the plurality of safety related test scenarios and provides the logic input signals to the logic controller. Execution of the plurality of safety related test scenarios via the safety logic code is triggered in response to the processing unit providing the logic input signals to the logic controller. Response output signals are generated by the logic controller in response to the safety related test scenarios being executed by the safety logic code. Compliancy of the safety logic code is determined by evaluating response output signals and associated logic input signals to a predetermined standard.

Abstract: A method for coding an event history is disclosed. Information relating to a real time state of an event is received. For a defined interval of time, it is determined whether the state of the event is in one of two states. In response to the event being in a first state, a data stream is appended with a first characteristic representative of the first state, and in response to the event being in a second different state, the data stream is appended with a second characteristic representative of the second state. The appended data stream is saved, and the process repeated for the next sequential defined interval of time.

Abstract: 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.

Abstract: 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 said list of sequences of operations, and utilizing said optimized sequence of operations to generate said control code set.

Abstract: A system and method for integrating a real and virtual manufacturing automation system that provides a part flow between a virtual world part of the system including virtual world components and a real world part of the system including real world components. The system includes an interface device for transferring signals between the virtual world part of the system and the real world part of the system, a programmable logic controller for controlling the operation of the system and an input/output device that processes signals sent to the programmable logic controller and signals sent from the programmable logic controller. The programmable logic controller controls the operation of the system where sensors and actuators coupled between the virtual world part of the system and the real world part of the system are physically coupled.

Abstract: 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.

Abstract: A system and method for providing an integrated virtual and real emulation environment for a manufacturing process to provide component compatibility testing and system performance prediction. In one embodiment, a real manufacturing system includes one or more real components that are controlled by a programmable logic controller. The real component can be replaced with a virtual component to determine whether it is compatible in the process, where the programmable controller sends signals to and receive signals from the virtual component as if it were the real component. For system performance prediction, a virtual manufacturing process is provided that includes virtual components where the virtual process is controlled by a programmable logic control as if it were a real process to determine the performance of a real system using the virtual process.

Abstract: 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.

Abstract: A method for coding an event history is disclosed. Information relating to a real time state of an event is received. For a defined interval of time, it is determined whether the state of the event is in one of two states. In response to the event being in a first state, a data stream is appended with a first characteristic representative of the first state, and in response to the event being in a second different state, the data stream is appended with a second characteristic representative of the second state. The appended data stream is saved, and the process repeated for the next sequential defined interval of time.

Abstract: A multistage machining process includes a plurality of stations. Workpiece feature quality is predicted based on decomposition of the machining process into sources of variation, reticulation of the machining process into machining stations and error models that account for significant contributions to feature quality including from categorical sources of variation.