The present disclosure relates to a manufacturing system, method and control circuitry for quality assured manufacturing of at least two biopharmaceutical products. The manufacturing system comprises a warehouse facility, a hydration facility, and at least two biopharmaceutical manufacturing facilities, wherein the warehouse facility and hydration facility are comprised in the macro structure. Each biopharmaceutical manufacturing facility is comprised in a respective micro node, and a control facility in the macro structure is configured to control interoperability of the macro structure and the micro nodes by means of a network spine interconnecting the macro structure with each micro node.

The present disclosure relates to a manufacturing system, method and control circuitry for quality assured manufacturing of at least two biopharmaceutical products. The manufacturing system comprises a warehouse facility, a hydration facility, and at least two biopharmaceutical manufacturing facilities, wherein the warehouse facility and hydration facility are comprised in the macro structure. Each biopharmaceutical manufacturing facility is comprised in a respective micro node, and a control facility in the macro structure is configured to control interoperability of the macro structure and the micro nodes by means of a network spine interconnecting the macro structure with each micro node.

A production management system 100 includes an operating state acquisition apparatus 20a and a production management apparatus 10. The operating state acquisition apparatus 20a includes a detector 21a that is retrofitted to be mounted on a production equipment 31 disposed on a manufacturing line L1 or retrofitted to be disposed in a vicinity of the production equipment 31, and which outputs a detection signal indicating an operating state of the production equipment 31, and includes a transmitter 22a that transmits the detection signal. The production management apparatus 10 includes a generator for generating information on production state of the manufacturing line L1 by use of the detection signal received from the operating state acquisition apparatus 20a, and includes a display device for displaying the generated information on production state.

A production management system 100 includes an operating state acquisition apparatus 20a and a production management apparatus 10. The operating state acquisition apparatus 20a includes a detector 21a that is retrofitted to be mounted on a production equipment 31 disposed on a manufacturing line L1 or retrofitted to be disposed in a vicinity of the production equipment 31, and which outputs a detection signal indicating an operating state of the production equipment 31, and includes a transmitter 22a that transmits the detection signal. The production management apparatus 10 includes a generator for generating information on production state of the manufacturing line L1 by use of the detection signal received from the operating state acquisition apparatus 20a, and includes a display device for displaying the generated information on production state.

The invention relates to a method for configuring a monitoring system for monitoring industrial processes and industrial assets. The method comprising, the monitoring system: receiving data associated with operation of industrial plants in native data format, adapting a common predefined data model to organize the data to convert in a common structured data format for use by application functions, receiving a request for data processing, generating a graphical view of the industrial process; identifying specific industrial processes and assets relating to the request of data processing and generating the graphical view; processing of specific data according to data processing request and generating a first graphical view associated for the specific data and associated identifiers according to a preconfigured first view configuration, generating a second graphical view from the first graphical view by incorporating a new view configurations onto the first view configuration based on result of data processing.

The invention relates to a method for configuring a monitoring system for monitoring industrial processes and industrial assets. The method comprising, the monitoring system: receiving data associated with operation of industrial plants in native data format, adapting a common predefined data model to organize the data to convert in a common structured data format for use by application functions, receiving a request for data processing, generating a graphical view of the industrial process; identifying specific industrial processes and assets relating to the request of data processing and generating the graphical view; processing of specific data according to data processing request and generating a first graphical view associated for the specific data and associated identifiers according to a preconfigured first view configuration, generating a second graphical view from the first graphical view by incorporating a new view configurations onto the first view configuration based on result of data processing.

The present application provides a hotel management system and method. The system includes at least one control panel; the control panel includes a first sub-panel and a second sub-panel; the first sub-panel is used to verify a first authorization key; and the first authorization key is used for hotel identity verification; the second sub-panel works independently of the first sub-panel, and the second sub-panel includes at least one physical regulator. The physical regulator is used to control sensing module and room equipment; and the first sub-panel controls the physical regulator. The first sub-panel and the second sub-panel are detachably connected. The hotel management system and guests can interact with each other and a smarter, more convenient and more powerful hotel environment control system is integrated in the hotel management system.

The present application provides a hotel management system and method. The system includes at least one control panel; the control panel includes a first sub-panel and a second sub-panel; the first sub-panel is used to verify a first authorization key; and the first authorization key is used for hotel identity verification; the second sub-panel works independently of the first sub-panel, and the second sub-panel includes at least one physical regulator. The physical regulator is used to control sensing module and room equipment; and the first sub-panel controls the physical regulator. The first sub-panel and the second sub-panel are detachably connected. The hotel management system and guests can interact with each other and a smarter, more convenient and more powerful hotel environment control system is integrated in the hotel management system.

The disclosed embodiments relate to a system that facilitates development of machine-learning techniques to perform prognostic-surveillance operations on time-series data from a monitored system, such as a power plant and associated power-distribution system. During operation, the system receives original time-series signals comprising sequences of observations obtained from sensors in the monitored system. Next, the system decomposes the original time-series signals into deterministic and stochastic components. The system then uses the deterministic and stochastic components to produce synthetic time-series signals, which are statistically indistinguishable from the original time-series signals. Finally, the system enables a developer to use the synthetic time-series signals to develop machine-learning (ML) techniques to perform prognostic-surveillance operations on subsequently received time-series signals from the monitored system.

The disclosed embodiments relate to a system that facilitates development of machine-learning techniques to perform prognostic-surveillance operations on time-series data from a monitored system, such as a power plant and associated power-distribution system. During operation, the system receives original time-series signals comprising sequences of observations obtained from sensors in the monitored system. Next, the system decomposes the original time-series signals into deterministic and stochastic components. The system then uses the deterministic and stochastic components to produce synthetic time-series signals, which are statistically indistinguishable from the original time-series signals. Finally, the system enables a developer to use the synthetic time-series signals to develop machine-learning (ML) techniques to perform prognostic-surveillance operations on subsequently received time-series signals from the monitored system.