The disclosure provides an industrial Internet of Things for identifying and processing manufacturing problems, a control method, and a storage medium. The method includes an industrial Internet of Things for identifying and processing manufacturing problems. The industrial Internet of Things includes an acquisition module, a problem type determination module and a problem solving module, the acquisition module is configured to obtain equipment information and data of product manufacturing problems; the problem type determination module is configured to determine a problem type at least based on the data of the product manufacturing problems; and the problem solving module is configured to determine problem processing data based on the problem type, and solve the problem based on the problem processing data.

The present disclosure provides an Industrial Internet of Things and a control method of an Industrial Internet of Things for handling failure of an assembly line equipment. The Industrial Internet of Things include a user platform, a service platform, a management platform, a sensor network platform, and an object platform interacting in sequence. The service platform, the management platform, and the sensor network platform all adopt an independent arrangement. The object platform is configured as a plurality of manufacturing equipment arranged in sequence according to a process sequence on the assembly line, and each of the manufacturing equipment separately corresponds to the service platform, the management platform, and the sensor network platform.

The present disclosure provides an Industrial Internet of Things system for intelligent repair of manufacturing equipment and a control method. The Industrial Internet of Things system includes a management platform, a sensor network platform, and an object platform interacting in sequence. The object platform is configured as a plurality of manufacturing equipment arranged in sequence according to a process sequence on the assembly line. The management platform is configured to issue self-repair instructions and failure handling instructions corresponding to the intelligent repair method to the corresponding manufacturing equipment through the sensor network platform, so as to realize the automatic repair of manufacturing equipment, reduce the cost of manual troubleshooting, and ensure the normal production and manufacturing of the assembly line.

According to one embodiment, an information extraction apparatus includes a processor including hardware. The processor extracts a description of a problematic event from text data. The processor extracts, from the text data, a description of a candidate action for taking an action against the problematic event. The processor discerns an effect of the candidate action against the problematic event.

Computer-implemented methods for fault diagnosis in an industrial environment generally includes processing the plurality of sensor data values to determine a recognized pattern therefrom; retrieving at least one industrial-environment digital twin corresponding to the industrial environment, the at least one industrial-environment digital twin comprising a plurality of component digital twins, with each of the plurality of component digital twins corresponding to one of the plurality of components in the industrial environment, and wherein the at least one industrial-environment digital twin and the plurality of component digital twins are visual digital twins that are configured to be rendered in a visual manner; and rendering the at least one industrial-environment digital twin and the at least one respective component digital twin corresponding to the particular component in the client application in response to the received request and based on the operational condition of the particular component.

A behavior recognition device for recognizing behaviors of a semiconductor manufacturing apparatus includes a storage device and a control unit. The storage device is configured to store log data of the semiconductor manufacturing apparatus. The control unit is cooperatively connected to the storage device, and configured to build a transition state model based on the log data to analyze behaviors related to wafer transfer sequences and manufacturing operations of the semiconductor manufacturing apparatus.

A building system for detecting faults in an operation of building equipment. The building system comprising one or more memory devices configured to store instructions thereon that cause one or more processors to perform a cumulative sum (CUSUM) analysis on actual building data and corresponding predicted building data to obtain cumulative sum values for a plurality of times within a first time period; determine a first time at which a first cumulative sum value is at a first maximum; identify a second cumulative sum value at a second maximum at a second time occurring after the first time; compare the identified second cumulative sum value to a threshold; and based on determining that the identified second cumulative sum value does not exceed the threshold, determine that a first fault ended at the first time.

A petroleum pipeline safety system for preventing contamination of an environmentally sensitive area close to a pipeline includes an upstream portion of the pipeline supplying a flow of fluid material, a crossing portion of the pipeline receiving the flow of fluid material from the upstream portion and conveying the flow of fluid material through the environmentally sensitive area to a downstream portion of the pipeline, the downstream portion, a pipeline pressure activated valve selectively capable of blocking the flow of fluid material from entering the crossing portion based upon a change in pressure within the crossing portion, and a fluid capacitor connected to the upstream portion configured to filter out a pressure spike in the upstream portion associated with the valve blocking the flow of fluid material.

A method for finding manufactured or to-be-manufactured products for defects includes obtaining basic information on processing history of products passed by each manufacturing machine at each processing workstation, and obtaining processing factor information of same, where each product is passed by a defect detection workstation after the product is passed by at least one processing workstation. The method includes obtaining quality information detected by each defect detection workstation. The method determines one or more problem manufacturing machines at one or more problem processing workstations according to the basic information on processing history and the quality information of the products. The method further determines one or more processing factors which influence the problem manufacturing machines according to the processing factor information of each manufacturing machine and the quality information of the products. A related electronic device and non-transitory storage medium are also provided.

A real-time control system includes a faulty variable identification technique to implement a data-driven fault detection function that provides an operator with information that enables a higher level of situational awareness of the current and likely future operating conditions of the process plant. The faulty variable identification technique enables an operator to recognize when a process plant component is behaving abnormally to potentially take action, in a current time step, to alleviate the underlying cause of the problem, thus reducing the likelihood of or preventing a stall of the process control system or a failure of the process plant component.