Abstract: One embodiment of the present disclosure provides a system for determining a hybrid-manufacturing plan for manufacturing an integrated circuit (IC). During operation, the system can obtain a set of hybrid-manufacturing constraints for manufacturing the IC. The set of hybrid-manufacturing constraints can include a set of primitives, a set of atoms, and an atom end-state vector. An atom can correspond to a unit of spatial volume of the IC. A primitive can represent an additive, subtractive, or a mixed manufacturing process corresponding to one or more atoms of the IC. Next, the system can determine a plurality of feasible hybrid-manufacturing plans based on the set of manufacturing constraints. Each feasible hybrid-manufacturing plan can represent an ordering of the set of primitives that satisfies the atom end-state vector. The system can then determine costs for manufacturing the IC using the plurality feasible hybrid-manufacturing plans.

Abstract: One embodiment can provide a method and a system for diagnosing faults in a physical system. During operation, the system obtains a time-domain model of the physical system and converts the time-domain model to the frequency domain to obtain a frequency-domain model of the physical system. The time-domain model can include one or more model parameters having known values. The system also obtains time-domain input and output signals and converts the time-domain input and output signals to the frequency domain to obtain frequency-domain input and output signals. The system identifies at least one model parameter having an expected value that is different from a known value of the at least one model parameter based on the frequency-domain model and the frequency-domain input and output signals, and generates a diagnostic output indicating at least one component within the physical system being faulty based on the identified at least one model parameter.

Abstract: A target system is coupled to a diagnosis engine that uses a lumped parameter model of the system for diagnosis. A proximity search in is performed in a computer-aided design model of the system to find groups of components that may be affected by resistive or parasitic interactions between the individual components in the groups. The lumped parameter model is augmented by adding elements that emulate the resistive or parasitic interactions between the individual components in the groups. The augmented lumped model is used by the diagnosis engine to perform diagnosis on the system.

Abstract: The system and method described allow for real-time control over positioning of a micro-object. A movement of at least one micro-object suspended in a medium can be induced by a generation of one or more forces by electrodes proximate to the micro-object. Prior to inducing the movement, a simulation is used to develop a model describing a parameter of an interaction between each of the electrodes and the micro-object. A function describing the forces generated by an electrode and an extent of the movement induced due to the forces is generated using the model. The function is used to design closed loop policy control scheme for moving the micro-object towards a desired position. The position of the micro-object is tracked and taken into account when generating control signals in the scheme.

Abstract: An analog circuit for solving optimization algorithms comprises three voltage controlled current sources and three capacitors, operatively coupled in parallel to the three voltage controlled current sources, respectively. The circuit further comprises a first inductor, operatively coupled in series between a first pair of the capacitors and the voltage controller current sources and a second pair of the capacitors and the voltage controller current sources. The circuit further comprises a second inductor, operatively coupled in series between the second pair of the capacitors and the voltage controller current sources and a third pair of the capacitors and the voltage controller current sources.

Abstract: An analog circuit for solving optimization algorithms comprises three voltage controlled current sources and three capacitors, operatively coupled in parallel to the three voltage controlled current sources, respectively. The circuit further comprises a first inductor, operatively coupled in series between a first pair of the capacitors and the voltage controller current sources and a second pair of the capacitors and the voltage controller current sources. The circuit further comprises a second inductor, operatively coupled in series between the second pair of the capacitors and the voltage controller current sources and a third pair of the capacitors and the voltage controller current sources.

Abstract: The following relates generally to analog circuit re-design. Some embodiments identify a candidate component of the circuit by determining that if the candidate component is adjusted or replaced, the circuit will satisfy a requirement metric. In some implementations, an optimization problem or Bayesian reasoning may be used to change parameters of the candidate component to create a replacement component. In some implementations, a replacement component of a different type than the candidate component may be selected by solving a mixed-integer optimization program or by using a non-linear program with continuous parameters.

Abstract: Embodiments described herein provide a system for facilitating a training system for a device. During operation, the system determines a system model for the device that can be based on empirical data of the device. The empirical data is obtained based on experiments performed on the device. The system then generates, from the system model, synthetic data that represents behavior of the device under a failure. The system determines uncertainty associated with the synthetic data and, from the uncertainty, determines a set of prediction parameters using an uncertainty quantification model. The system generates training data from the synthetic data based on the set of prediction parameters and learns a set of learned parameters associated with the device by using a machine-learning-based classifier on the training data.

Abstract: The disclosure following relates generally to complex simulations, and fault diagnosis. In some embodiments, a component that is causing a delayed simulation time of a system is determined. A component of reduced complexity is designed, and the component of reduced complexity is used to replace the original component in the system. Fault diagnosis may then be conducted using the updated system with the reduced complexity component, thus decreasing the time taken to diagnose the fault.

Abstract: A classification-based diagnosis for detecting and predicting faults in physical system (e.g. an electronic circuit or rail switch) is disclosed. Some embodiments make use of partial system model information (e.g., system topology, components behavior) to simplify the classifier complexity (e.g., reduce the number of parameters). Some embodiments of the method use a Bayesian approach to derive a classifier structure.

Abstract: The following relates generally to design and redesign of digital circuits. In one disclosed embodiment, a circuit is annotated by identifying at least one possible error location according to an error library; the at least one possible error location is localized; and the circuit is redesigned based on the localized at least one possible error location.

Abstract: One embodiment provides a method and a system for automated design of a computational system. During operation, the system obtains a component library comprising a plurality of computational components, receives design requirements of the computational system, and builds a plurality of universal component cells. A respective universal component cell is configurable, by a selection signal, to behave as one of the plurality of computational components. The system further constructs a candidate computational system using the plurality of universal component cells and encodes the received design requirements and the candidate computational system into a single logic formula. Variables within the single logic formula comprise at least inputs, outputs, and internal variables of the candidate computational system. The system solves the single logic formula to obtain at least one design solution for the computational system.

Abstract: One embodiment provides a method and a system for automated design of a computational system. During operation, the system obtains a component library comprising a plurality of computational components, receives design requirements of the computational system, and builds a plurality of universal component cells. A respective universal component cell is configurable, by a selection signal, to behave as one of the plurality of computational components. The system further constructs a candidate computational system using the plurality of universal component cells and encodes the received design requirements and the candidate computational system into a single logic formula. Variables within the single logic formula comprise at least inputs, outputs, and internal variables of the candidate computational system. The system solves the single logic formula to obtain at least one design solution for the computational system.

Abstract: A method and system for automated design of a physical system are provided. During operation, the system obtains a component library comprising a plurality of physical components, receives design requirements of the physical system, and constructs an initial system model based on physical components in the component library and the design requirements. The system topology associated with the initial system model can include a large number of links that are sufficiently coupled to one another, and a respective link comprises one or more physical components. The system further performs an optimization operation comprising a plurality of iterations, with the system topology being updated at each iteration. Updating the system topology includes removing links and components from the system topology. The system then generates a final system model based on an outcome of the optimization operation and outputs a design solution of the physical system according to the final system model.

Abstract: The system and method described allow for real-time control over positioning of a micro-object. A movement of at least one micro-object suspended in a medium can be induced by a generation of one or more forces by electrodes proximate to the micro-object. Prior to inducing the movement, a simulation is used to develop a model describing a parameter of an interaction between each of the electrodes and the micro-object. A function describing the forces generated by an electrode and an extent of the movement induced due to the forces is generated using the model. The function is used to design closed loop policy control scheme for moving the micro-object towards a desired position. The position of the micro-object is tracked and taken into account when generating control signals in the scheme.

Abstract: An analog circuit for solving optimization algorithms comprises three voltage controlled current sources and three capacitors, operatively coupled in parallel to the three voltage controlled current sources, respectively. The circuit further comprises a first inductor, operatively coupled in series between a first pair of the capacitors and the voltage controller current sources and a second pair of the capacitors and the voltage controller current sources. The circuit further comprises a second inductor, operatively coupled in series between the second pair of the capacitors and the voltage controller current sources and a third pair of the capacitors and the voltage controller current sources.

Abstract: The following relates generally to design and redesign of digital circuits. In one disclosed embodiment, a circuit is annotated by identifying at least one possible error location according to an error library; the at least one possible error location is localized; and the circuit is redesigned based on the localized at least one possible error location.

Abstract: The following relates generally to analog circuit re-design. Some embodiments identify a candidate component of the circuit by determining that if the candidate component is adjusted or replaced, the circuit will satisfy a requirement metric. In some implementations, an optimization problem or Bayesian reasoning may be used to change parameters of the candidate component to create a replacement component. In some implementations, a replacement component of a different type than the candidate component may be selected by solving a mixed-integer optimization program or by using a non-linear program with continuous parameters.

Abstract: A new and/or improved method, apparatus and/or system is disclosed which aids in extending correct behavioral models to include fault modes and in fault mode analysis of components and/or systems in simulated model environments, including, e.g., FMEA and FMECA and diagnostic fault tree generation.

Abstract: The system and method described below allow for real-time control over positioning of a micro-object. A movement of at least one micro-object suspended in a medium can be induced by a generation of one or more forces by electrodes proximate to the micro-object. Prior to inducing the movement, a simulation is used to develop a model describing a parameter of an interaction between each of the electrodes and the micro-object. A function describing the forces generated by an electrode and an extent of the movement induced due to the forces is generated using the model. The function is used to design closed loop policy control scheme for moving the micro-object towards a desired position. The position of the micro-object is tracked and taken into account when generating control signals in the scheme.