Examples described herein provide a computer-implemented method that includes calculating, by a processing device, a motor acceleration error based at least in part on a motor torque and a motor speed. The method further includes calculating, by the processing device, a regression fit line based at least in part on the motor acceleration error. The method further includes identifying, by the processing device, a zero point using the regression fit line. The method further includes comparing, by the processing device, the zero point to a datum reference to determine a difference. The method further includes integrating, by the processing device, the difference to determine the lash angle. The method further includes controlling, by the processing device, the motor based at least in part on the lash angle.

Examples described herein provide a computer-implemented method that includes calculating, by a processing device, a motor acceleration error based at least in part on a motor torque and a motor speed. The method further includes calculating, by the processing device, a regression fit line based at least in part on the motor acceleration error. The method further includes identifying, by the processing device, a zero point using the regression fit line. The method further includes comparing, by the processing device, the zero point to a datum reference to determine a difference. The method further includes integrating, by the processing device, the difference to determine the lash angle. The method further includes controlling, by the processing device, the motor based at least in part on the lash angle.

A modular automation support system for modular plants includes an engineering support system comprising a control and execution engine configured to: receive data from a monitoring infrastructure of a modular plant and convert that data into semantic data which conforms to a semantic data model; use one or more semantic rules or mechanisms relating the semantic data received from the monitoring infrastructure to services provided by modules of a pipeline of the modular plant to control the pipeline in executing a process.

A manufacturing system for a biopharmaceutical product includes first and second sets of biopharmaceutical manufacturing equipment located at a first and second enterprise sites, and memory configured to store an enterprise configuration and a process specification. The enterprise configuration includes records of one or more equipment parameters of the multiple pieces of equipment of the first and second sets of biopharmaceutical manufacturing equipment. At least one processor is configured to execute instructions determine whether at least one of the first enterprise site and the second enterprise site is capable of manufacturing the biopharmaceutical product, transmit a generated set of instructions to the determined at least one of the first enterprise site and the second enterprise site, and operate the multiple pieces of equipment at the determined at least one of the first enterprise site and the second enterprise site to manufacture the biopharmaceutical product.

A wireless emergency stop system includes a machine safety device connected to a machine stop circuit for stopping operation of a machine when the machine stop circuit is activated. The machine safety device includes a wireless communication interface. The system also includes a mobile device controller configured to control operation of the machine, and a safety stop device. The safety stop device includes a wireless communication interface for wireless communication with the machine safety device, and an emergency stop switch configured to, when activated, transmit an emergency stop signal to the machine safety device to trigger an emergency stop of the machine. The mobile device controller is configured to link with the safety stop device via short-range wireless communication.

A fieldbus solenoid valve system has a solenoid operated control valve mounted and operated by a solenoid pilot. A direct current power source is connected to a coil of the solenoid pilot and a driver for actuating the coil. A resistive element is in series with the power source, the driver, the solenoid and a ground. A frequency generator is connected to the circuit for creating a frequency pulse train to the coil having a characterization so as not to cause the solenoid pilot to actuate. The voltage is measured between the coil and resistive element and the measured voltage is compared to a base voltage value measured from the same circuit location. An indicator signal is displayed on the fieldbus solenoid valve system or externally when the measured voltage increases to a predetermined amount from said base voltage over time.

A method for generating a process model modeling a manual mode procedure instance of a plant process includes providing log events of operational actions; selecting related sequences of manual mode operational actions from the log events; filtering the related sequences according to an individual plant section; identifying a sequential order from the filtered related sequences; determining statistical properties of values of related process variables and/or statistical properties of values of related set point changes to each sequential ordered manual mode operational action from the filtered related sequences; generating the process model of the manual mode procedure instance by arranging related manual mode operational actions with the sequential order of each operational action assigned with the statistical properties of the values of related process variables and/or assigned with the statistical properties of the values of the related set point changes.

A method and apparatus for predicting power consumption, a device, and a readable storage medium. The method includes: acquiring a reference variable generated in a history time period; and acquiring predicted power consumption in a target time period by inputting a variable characteristic into a power consumption prediction model, the target time period and the history time period having a corresponding relationship, and the power consumption prediction model being obtained by training a sample reference variable marked with sample power consumption. In the method, the reference variable including a discrete reference variable and a continuous reference variable in the history time period is acquired, and a characteristic of the acquired reference variable is acquired; and an extracted variable characteristic is input into a variable prediction model to output the predicted power consumption in the target time period.

A method and apparatus for predicting power consumption, a device, and a readable storage medium. The method includes: acquiring a reference variable generated in a history time period; and acquiring predicted power consumption in a target time period by inputting a variable characteristic into a power consumption prediction model, the target time period and the history time period having a corresponding relationship, and the power consumption prediction model being obtained by training a sample reference variable marked with sample power consumption. In the method, the reference variable including a discrete reference variable and a continuous reference variable in the history time period is acquired, and a characteristic of the acquired reference variable is acquired; and an extracted variable characteristic is input into a variable prediction model to output the predicted power consumption in the target time period.

An interactive control method, an apparatus, and a system for an intelligent kitchen, a computer readable storage medium, and an electronic device, capable of improving the degree of intelligence of kitchen work, and improving the kitchen operation efficiency. The method includes: obtaining dish information of a dish to be cooked, and determining a cooking task according to the dish information; controlling, according to the cooking task, a target cooking station to cook the dish; determining a dish container corresponding to the dish information according to the dish information, and controlling the dish container to be transported to a dish receiving position of the target cooking station; and after the target cooking station finishes cooking and fills a cooked dish into the dish container, sending a delivery instruction to control a delivery terminal to perform a dish delivery task.