Methods, systems, and computer-readable storage media for receiving a time-series of data values associated with a plurality of sensors, each sensor generating at least a portion of the time-series of a respective data value, providing a plurality of auto-regression models, each auto-regression model being provided based on a respective first sub-set of the time-series of data values used as input, and a respective second sub-set of the time-series of data values used as training data during a training process, receiving respective data values associated with a time from and generated by each of the plurality of sensors, determining respective predicted values for each of the auto-regression models, and selectively indicating that an anomaly is present in the system based on respective predicted values for each of the auto-regression models, and the respective data values associated with a time.

A method for generating a maintenance program for the operation of a maintenance system at a bioreactor, in particular a bioreactor of a vehicle for transporting persons, which method comprises at least the following steps, which are executed by an electronic data processing means associated with the maintenance system: acquiring system characteristics data of the maintenance system; acquiring reactor characteristics data of the bioreactor, the reactor characteristics data being received at least in part from a communication interface of the bioreactor; and generating the maintenance program at least on the basis of the system characteristics data and the reactor characteristics data.

A system and method for facilitating predictive maintenance of an equipment is disclosed. The system may include a data capturer, a plurality of edge computing nodes and a cloud computing device. Each edge computing node may include a first processor. The cloud computing device may include a second processor. The first processor may receive the raw input data from the data capturer and may process the raw input data to obtain a representative data. The representative data may include an insight pertaining to a deviation in the at least one variable and a corresponding remedial action to be taken to correct the deviation. The deviation may be related to a deterioration in the condition of the equipment. The respective edge computing node may facilitate a regulation of the deviation by performing an automated actuation based on the corresponding remedial action.

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 robotic electric arc welding system includes a welding torch, a welding robot configured to manipulate the welding torch during a welding operation, a robot controller operatively connected to the welding robot to control weaving movements of the welding torch along a weld seam and at a weave frequency and weave period, and a welding power supply operatively connected to the welding torch to control a welding waveform, and operatively connected to the robot controller for communication therewith. The welding power supply is configured to sample a plurality of weld parameters during a sampling period of the welding operation and form an analysis packet, and process the analysis packet to generate a weld quality score, wherein the welding power supply obtains the weave frequency or the weave period and automatically adjusts the sampling period for forming the analysis packet based on the weave frequency or the weave period.

A computer-implemented method of maintaining a transport system in a manufacturing facility including: measuring one or more pose-related properties of a plurality of transportation devices at a plurality of manufacturing stations in the manufacturing facility, at which manufacturing stations one or more workpieces are processed; determining a statistical characteristic for each of the plurality of transportation devices based on the pose-related properties; determining a sequence for maintaining one or more transportation devices based on the statistical characteristics; and optionally performing one or more maintenance procedures based on the sequence.

A method includes receiving, from one or more sensors associated with manufacturing equipment, current trace data associated with producing, by the manufacturing equipment, a plurality of products. The method further includes performing signal processing to break down the current trace data into a plurality of sets of current component data mapped to corresponding component identifiers. The method further includes providing the plurality of sets of current component data and the corresponding component identifiers as input to a trained machine learning model. The method further includes obtaining, from the trained machine learning model, one or more outputs indicative of predictive data and causing, based on the predictive data, performance of one or more corrective actions associated with the manufacturing equipment.

An assistance method for execution of a format change in an automatic machine can include dividing the format change into an orderly succession of operations for the removal of components designed for the old format and installation of components designed for the new format; communicating the orderly succession of removal and installation operations to an operator; electronically and automatically detecting the actual presence or absence of a component designed for the old or new format before communicating to the operator the operation for removal or installation of the component; electronically and automatically detecting the actual absence or presence of a component designed for the old or new format after having communicated to the operator; and communicating to the operator the operation following an operation for the removal or installation of a component only after having electronically and automatically checked for the actual absence or presence of the component.

A method includes receiving first metrology data associated with first substrates produced by manufacturing equipment. The method further includes training a first machine learning model with data input including the first metrology data to generate a first trained machine learning model. The first trained machine learning model is capable of reducing dimensionality of second metrology data associated with second substrates produced by second manufacturing equipment to perform corrective actions associated with the second manufacturing equipment.

A machine tool management system connects an external server and a large number of NC devices controlling the external server and respective machine tools through a network. The system collects several kinds of signal data from the NC device of each machine tool to the external server. In the system, the external server stores a maintenance period model and a refinement algorithm and obtains a next maintenance period from the maintenance period model.