An architecture for monitoring at least one aircraft. The architecture comprises an avionics system configured to generate avionics data during use of the aircraft; a mobile electronic device including an analysis unit configured to convert at least one maintenance operation into operational data; and an alerter configured to display at least one item of monitoring information; and a cloud computing infrastructure. The analysis unit and the alerter are configured to implement a local operating mode and an operating mode connected to the cloud computing infrastructure.

A server rack predictive maintenance method comprises: an information collecting step of measuring and collecting the value of power consumed by a main wire for supplying power to a fan and pieces of equipment in a normal operating state of a server rack in which the internal temperature and humidity are maintained to be constant through the fan; an alarm setting step of setting the average current value of the server rack on the basis of the value of power collected in the information collecting step, and setting the alarm current value to be smaller than the set average current value; and a detecting step of detecting the server rack as an abnormal state when the value of power consumed by the main wire, having been measured in a real-time operating state of the server rack, is formed less than the alarm current value.

A method for automatic diagnosis of a mechanical system of a group of mechanical systems sharing mechanical characteristics includes obtaining data relating to a vibration. The vibration-related data is acquired by a portable communications device configured to communicate with a remote processor. The processor automatically diagnoses the mechanical system by applying a relationship to the obtained vibration-related data. The relationship is based on sets of vibration-related data previously obtained from the mechanical systems. Each set of vibration-related data relates to vibrations of a mechanical system. The relationship is further based on sets of operation data previously obtained for mechanical systems of the group. Each set of operation data indicates a previous state of operation of a mechanical system. Each of the previous states of operation is associated with at least one of the previously obtained sets of vibration-related data.

A maintenance planning system for a production plant comprises: a production planning system for determining a production sequence for the production plant; an automation system for controlling production in the production plant; a state monitoring system for acquiring states of the production plant and its components; and a business planning system for the economic management of production and maintenance in the production plant. The maintenance planning system is designed for determining maintenance measures for the production plant. When determining the maintenance measures, the maintenance planning system takes into account the information of the production planning system, the automation system, the state monitoring system and the business planning system and performs optimization with regard to an economic utilization of the production plant. The disclosure further relates to a method for determining maintenance measures for a production plant and corresponding computer programs.

A life consumption estimation device for estimating life consumption of at least one part of a gas turbine includes: a predicted air temperature information acquisition unit configured to acquire predicted air temperature information regarding a future air temperature; a predicted load information acquisition unit configured to acquire predicted load information regarding a future load of the gas turbine; a gas turbine state quantity estimation unit configured to estimate at least one gas turbine state quantity regarding a future state quantity of the gas turbine, on the basis of predicted air temperature information acquired by the predicted air temperature information acquisition unit and the predicted load information acquired by the predicted load information acquisition unit; and a life consumption estimation unit configured to estimate the life consumption of the at least one part, on the basis of the gas turbine state quantity estimated by the gas turbine state quantity estimation unit.

There is provided an equipment element maintenance analysis system including: a history information acquirer that is attached with at least one equipment element and acquires, at a predetermined timing, operation history information on a piece of manufacturing equipment for manufacturing a product; an error rate calculator that calculates an error rate based on the number of errors related to each of the at least one equipment element, included in the operation history information; a maintenance determiner that determines maintenance necessity of each of the at least one equipment element; and a notifier that notifies an information item on an equipment element determined to require maintenance among the at least one equipment. The error rate calculator calculates, as a latest error rate, an error rate in a latest predetermined period from the acquired operation history information, the maintenance determiner determines an equipment element with the latest error rate greater than or equal to a predetermined value among one or more equipment elements with a large number of errors as the equipment element that requires maintenance, the one or more equipment elements being included in the at least one equipment element, and the notifier lists the information on the equipment elements with a large number of errors in order, and notifies the number of errors and requirement of maintenance.

Systems and methods for fault prediction through a Bayesian framework are provided. Fault prediction for a valve system may be provided by generating a Bayesian framework by collecting a plurality of historical parameters related to opening and closing of a valve across a plurality of operational legs; generating a plurality of historical feature metrics based on the plurality of historical parameters; in response to detecting a fault, defining a prefault state corresponding to the historical feature metrics; monitoring a plurality of operational parameters related to opening and closing of the valve during a given operational phase of an operational leg; generating a plurality of operational feature metrics based on the plurality of operational parameters monitored during the given operational phase; and in response to determining, using the generated Bayesian framework, that the operational feature metrics indicate the prefault state of the subsystem, generating a notification.

A data processing system enables a user to select performance indicators in terms of which a plant operation is to be optimized. The system receives data from instruments monitoring plant operation and a user selection of a performance indicators to optimize in accordance with one or more set-points for assets at the plant. The system generates a plurality of values for the performance indicator via the model and based on the data and a plurality of test values for the set-point. The system determines one or more settings for one or more set-points of at least one of the plurality of assets at the plant based on the plurality of values for the performance indicator and the plurality of test values for the set-point and provides the one or more settings for the one or more set-points to adjust the performance of the plant.

A material life predicting method is to perform X-ray diffraction on a target to obtain a composition state curve diagram of the target, and then compare the composition state curve diagram of the target according to a built-in data in a database to obtain a composition of the target and content of the composition, and then the content of the identical composition of the target and the control is compared to obtain the change in the content of the identical composition between the target and the control, and then quantify a consumption degree of the material life of the target, where the control is a new furnace tube and the target is a used furnace tube.

An approach for providing solutions to ad in the process recovery in manufacturing systems to resume manufacturing activity is disclosed. The outcome of the approach can include the following advantages, minimizing waste, reducing cost of recovery, and increasing efficiency in a manufacturing process. The approach includes collecting initial factory data; identifying and categorizing one or more shop floor activities; determining initial recovery process; creating a digital twin copy of the factory; performing one or more initial simulation scenarios; generating factory improvement plan; and executing factory improvement plan.