Various systems and methods may be used to implement a software defined industrial system. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. The orchestrated system may include an orchestration server, a first node executing a first module, and a second node executing a second module. In response to the second node failing, the second module may be redeployed to a replacement node (e.g., the first node or a different node). The replacement mode may be determined by the first node or another node, for example based on connections to or from the second node.

Various systems and methods may be used to implement a software defined industrial system. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. The orchestrated system may include an orchestration server, a first node executing a first module, and a second node executing a second module. In response to the second node failing, the second module may be redeployed to a replacement node (e.g., the first node or a different node). The replacement mode may be determined by the first node or another node, for example based on connections to or from the second node.

Various systems and methods for implementing a software defined industrial system are described herein. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. In response to a node failing, a module may be redeployed to a replacement node. In an example, self-descriptive control applications and software modules are provided in the context of orchestratable distributed systems. The self-descriptive control applications may be executed by an orchestrator or like control device and use a module manifest to generate a control system application. For example, an edge control node of the industrial system may include a system on a chip including a microcontroller (MCU) to convert IO data. The system on a chip includes a central processing unit (CPU) in an initial inactive state, which may be changed to an activated state in response an activation signal.

In order to easily identify a specimen to be extracted because, for example, an item remains uninspected, from a rack 31 collected in a storage part 13 or the rack 31 taken out from the storage part, a camera of a smart device takes an image of the rack; and a calculation unit included in the smart device provides a mark, by AR technology, at the position of a specimen to be extracted. For example, the item that remains uninspected is identified on the basis of information about a combination of a rack ID and an identifier and information, which is received from an operation unit about specimens at respective positions. Thus, irrespective of a place or whether the specimen to be extracted is inside or outside of the device, the specimen to be extracted can be reliably specified from a plurality of specimen containers provided on a holder.

Various systems and methods may be used to implement a software defined industrial system. For example, an edge control node of the industrial system may include a system on a chip including a microcontroller (MCU) to convert IO data. The system on a chip includes a central processing unit (CPU) in an initial inactive state to receive an activation signal from, for example, an orchestration server, and change to an activated state in response to receiving the activation signal.

Various systems and methods for implementing a software defined industrial system are described herein. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. In response to a node failing, a module may be redeployed to a replacement node. In an example, self-descriptive control applications and software modules are provided in the context of orchestratable distributed systems. The self-descriptive control applications may be executed by an orchestrator or like control device and use a module manifest to generate a control system application. For example, an edge control node of the industrial system may include a system on a chip including a microcontroller (MCU) to convert IO data. The system on a chip includes a central processing unit (CPU) in an initial inactive state, which may be changed to an activated state in response an activation signal.

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.

An approach capable easily setting required connection settings even when multiple devices are connected to a network is provided. A support apparatus includes: a setting reception part, which receives a connection setting that is the setting of the connection established between the control apparatus and each remote device; and a transmission part, which transmit the connection setting received by the setting reception part to the control apparatus and the remote device which are involved in the connection setting. The setting reception part includes a part which displays the remote devices capable of establishing the connection from the control apparatus by a list and receives selection to the remote devices displayed by a list, and a part which temporarily allocates the input-output data predetermined for a remote device that is selected to the selected remote device.

An approach capable easily setting required connection settings even when multiple devices are connected to a network is provided. A support apparatus includes: a first setting reception part, which receives a setting of connection; a second setting reception part, which receives a setting of a variable name used for reference in a program executed in a control apparatus for each datum exchanged in the connection that is set; a generation part, which determines a tag name associated with each datum based on the variable name that is set for each datum, and generates a connection setting that contains each tag name that is determined; and a transmission part, which transmits the connection setting that is generated to the control apparatus and the device which are involved in the connection setting.

Disclosed are a network configuration method and an intelligent robot, falling within the technical field of intelligent devices. The method comprises: step S1, forming replacement information in a pre-set format according to configuration information of a network configuration for the intelligent robot, and outputting the replacement information by using an external device; step S2, the intelligent robot receiving and parsing the replacement information so as to obtain and output a corresponding parsing result; step S3, the intelligent robot obtaining the configuration information by means of restoration according to the parsing result; and step S4, the intelligent robot conducting network configuration according to the configuration information, and subsequently loging out. The beneficial effects of the technical solution are: being able to simplify a network configuration process for an intelligent robot, being able to achieve the purpose of network configuration with only a relatively low cost, and ensuring the accuracy of network configuration information.