A computer implemented method includes receiving, by the computer, a request to display a process safety risk matrix associated with a process facility and displaying the process safety risk matrix. The process safety risk matrix includes a 2-dimensional representation of a plurality of risk matrix cells, each of the plurality of risk matrix cells associated with a combination of a likelihood level and a severity level. The computer implemented method includes displaying, by the computer, an indication of a hazardous process event scenario within a first cell within the process safety risk matrix, the cell location determined based on a Target Mitigated Event Likelihood (TMEL) and a Safety Severity. The computer implemented method includes displaying, by the computer, an indication of a second graphic indication on a second cell to identify a change in a hazardous scenario count associated with the second cell.

A self-diagnostic circuit includes an electrical conductor configured to multiplex, a first switch interposing the electrical conductor, and a first module crossing the first switch. The first module includes a first receptor antenna associated with the conductor on one side of the first switch, a first emitter antenna associated with the conductor on an opposite side of the first switch, and a first interfacing microprocessor. The first interfacing microprocessor is configured to receive no signal from the first receptor antenna when the first switch is open thus generating a first open signal and a first address signal indicative of the first module and outputting the first open signal and the first address signal to the conductor via the first emitter antenna. The first interfacing microprocessor is further configured to receive a first induced frequency signal from the first receptor antenna when the first switch is closed thus generating a first closed signal and the first address signal indicative of the first module and outputting the first closed signal and the first address signal to the conductor via the first emitter antenna.

An artificial intelligence (AI) system using a machine learning algorithm and an application thereof is provided. The method for controlling an electronic apparatus includes acquiring an output value by inputting an input value to a function module to perform a function corresponding to the function module included in the electronic apparatus, identifying a safety mechanism to be applied to the function module based on the input value and the output value, and detecting an error operation of the function module based on the identified safety mechanism.

An automated warehouse has a main path, secondary paths, a main vehicle movable along the main path, one or more auxiliary vehicles movable along the secondary paths, and an access point. On each vehicle a wireless device receiving and sending wireless signals and a control unit associated with safety modules including a safety-certified watchdog timer and a counter are installed. The wireless devices send check signals containing the value of the counter of the respective vehicle to the access point, which sends signals in response to received check signals When a response signal is received from a wireless device, the respective counter is incremented and the associated watchdog timer starts to measure time when the value of the counter differs from the value received via check signals. Each control unit de-energizes the respective vehicle when a time longer than a predetermined time is detected via the watchdog timer.

An automated warehouse has a main path, secondary paths, a main vehicle movable along the main path, one or more auxiliary vehicles movable along the secondary paths, and an access point. On each vehicle a wireless device receiving and sending wireless signals and a control unit associated with safety modules including a safety-certified watchdog timer and a counter are installed. The wireless devices send check signals containing the value of the counter of the respective vehicle to the access point, which sends signals in response to received check signals When a response signal is received from a wireless device, the respective counter is incremented and the associated watchdog timer starts to measure time when the value of the counter differs from the value received via check signals. Each control unit de-energizes the respective vehicle when a time longer than a predetermined time is detected via the watchdog timer.

Some implementations provides a system to implement a safety control at an oil and gas facility, the system comprising: one or more motor control centers, each comprising a network interface, and a programmable logic controller (PLC), wherein each motor control center is configured to monitor and control one or more field devices coupled thereto, and wherein a plurality of field devices are dispersed at the oil and gas facility; and a safety instrumented system (SIS) in communication with the one or more motor control centers through the network interface thereof, wherein each motor control center is configured to communicate with the SIS without an interposing relay, and wherein the SIS comprises control elements configured to implement the safety control at the oil and gas facility based on communication with each motor control center through the network interface thereof.

According to an aspect, there is provided a method for evaluating safety of a speed of a motor controlled by a frequency converter. The method includes, first, measuring first, second and third phase currents of three-phase electric power fed from the frequency converter to the motor and forming first, second and third current measurement pairs based thereon. Then, the speed of the motor is estimated separately based on each measurement pair to produce respective first, second and third estimates for the speed of the motor. A voting logic is applied to the first, second and third estimates for the speed of the motor. A voting logic is applied to the first, second and third estimates. An output of the voting logic is fed to a safety logic controlling at least one safety function of the frequency converter. The output of the voting logic includes an estimate for the speed of the motor and an indication whether or not said final estimate is valid according to the voting logic.

Soft error data describing soft errors predicted to affect at least a particular hardware component of a computing system are used to determine functional safety metric values. The computing system is to control at least a portion of physical functions of a machine using the particular hardware component. Respective soft error rates are determined for each of a set of classifications based on the soft errors described in the soft error data. Derating of the soft error rates are performed based on a set of one or more vulnerability factors to generate derated error rate values for each of the set of classifications. The functional safety metric value is determined from the derated error rate values to perform a functional safety analysis of the computing system.

Disclosed is a method for detecting an integrity index of a driving unit, including: an integrity value setting step of setting an integrity reference value on the basis of information on power consumed in a normal driving section of a driving unit; a defective value setting step of setting a defective reference value on the basis of information on power consumed in a driving section of the driving unit before a failure occurs; a measurement value extraction step of extracting a measurement value from information on power consumed in a driving section measured in a real-time driving state of the driving unit; a detection step of comparing the measurement value extracted in the measurement value extraction step with the integrity reference value and the defective reference value and detecting an integrity index value of the driving unit; and an output step of outputting the integrity index value detected in the detection step and providing same to an administrator.

A device for computing data models, in particular comprising the possibility to detect errors occurring during the computation, has at least two processing units, at least one of the at least two processing units being designed to compute a main data model as a function of at least one state of a system, at least one other of the at least two processing units being designed to compute, as a function of this at least one state of the system, an approximation data model associated with the main data model, the main data model comprising at least one property of the system as a first data model, the approximation data model comprising at least the same property of the system approximately as a second data model, a comparator unit being designed to compare a first result of a first computation of the main data model with a second result of a second computation of the approximation data model associated with the main data model, in order to determine information about a deviation between the first result and the second result, the comparator unit being designed to detect an error as a function of the information about the deviation if the deviation exceeds a maximum admissible deviation.