Abstract: In order to provide a method for analysing quality deficiencies of workpieces, preferably vehicle bodies and/or vehicle attachment parts, in particular after and/or whilst passing through a production process in industrial-method plants, preferably after and/or whilst passing through a painting process in painting plants, by means of which method quality deficiencies can be avoided and/or by means of which method quality deficiency causes in the production process can be determined, avoided and/or remedied, it is proposed in accordance with the invention that the method comprises the following steps: creating a workpiece-specific data set, uniquely assigned to a workpiece, at the start of a production process, in particular at the start of a painting process and/or creating a workpiece-carrier-specific data set, uniquely assigned to a workpiece carrier, at the start of a production process, in particular at the start of a painting process; supplementing the workpiece-specific data set while a workpiece is

Abstract: In order to provide a method for anomaly and/or fault recognition in an industrial-method plant, for example a painting plant, wherein anomalies and/or fault situations are recognisable simply and reliably by means of the method, it is proposed according to the invention that the method should comprise the following: automatic generation of an anomaly and/or fault model of the industrial-method plant that comprises information on the occurrence probability of process values; automatic input of process values of the industrial-method plant during operation thereof; automatic recognition of an anomaly and/or fault situation by determining an occurrence probability by means of the anomaly and/or fault model on the basis of the process values of the industrial-method plant that have been input and by checking the occurrence probability for a limit value,

Abstract: In order to provide a method for anomaly and/or fault recognition in an industrial-method plant, for example a painting plant, wherein anomalies and/or fault situations are recognisable simply and reliably by means of the method, it is proposed according to the invention that the method should comprise the following: automatic generation of an anomaly and/or fault model of the industrial-method plant that comprises information on the occurrence probability of process values; automatic input of process values of the industrial-method plant during operation thereof; automatic recognition of an anomaly and/or fault situation by determining an occurrence probability by means of the anomaly and/or fault model on the basis of the process values of the industrial-method plant that have been input and by checking the occurrence probability for a limit value,

Abstract: In order to provide a method for predicting process deviations in an industrial-method plant, for example a painting plant, by means of which process deviations are predictable simply and reliably, it is proposed according to the invention that the method should comprise the following: automatic generation of a prediction model; prediction of process deviations during operation of the industrial-method plant, using the prediction model.

Abstract: In order to provide a method for fault analysis in an industrial-method plant, for example a painting plant, by means of which fault situations are analysable simply and reliably, it is proposed according to the invention that the method should comprise the following: in particular automatic recognition of a fault situation in the industrial-method plant (101); storage of a fault situation data set for the respective recognised fault situation, in a fault database (136); automatic determination of a cause of the fault for the fault situation and/or automatic determination of process values that are relevant to the fault situation, on the basis of the fault data set of a respective recognised fault situation.

Abstract: In order to provide a method for analysing quality deficiencies of workpieces, preferably vehicle bodies and/or vehicle attachment parts, in particular after and/or whilst passing through a production process in industrial-method plants, preferably after and/or whilst passing through a painting process in painting plants, by means of which method quality deficiencies can be avoided and/or by means of which method quality deficiency causes in the production process can be determined, avoided and/or remedied, it is proposed in accordance with the invention that the method comprises the following steps: creating a workpiece-specific data set, uniquely assigned to a workpiece, at the start of a production process, in particular at the start of a painting process and/or creating a workpiece-carrier-specific data set, uniquely assigned to a workpiece carrier, at the start of a production process, in particular at the start of a painting process; supplementing the workpiece-specific data set while a workpiece is

Abstract: In order to provide a method for anomaly and/or fault recognition in an industrial-method plant, for example a painting plant, wherein anomalies and/or fault situations are recognisable simply and reliably by means of the method, it is proposed according to the invention that the method should comprise the following: automatic generation of an anomaly and/or fault model of the industrial-method plant that comprises information on the occurrence probability of process values; automatic input of process values of the industrial-method plant during operation thereof; automatic recognition of an anomaly and/or fault situation by determining an occurrence probability by means of the anomaly and/or fault model on the basis of the process values of the industrial-method plant that have been input and by checking the occurrence probability for a limit value,

Abstract: In order to provide a method for predicting process deviations in an industrial-method plant, for example a painting plant, by means of which process deviations are predictable simply and reliably, it is proposed according to the invention that the method should comprise the following: automatic generation of a prediction model; prediction of process deviations during operation of the industrial-method plant, using the prediction model.

Abstract: A network connectivity mode is activated at a vehicle during which an on-board wireless LAN interface and an on-board wireless WAN interface are collectively operated in a higher-power consumption state with respect to a set of on-board batteries to collectively support communications between one or more LAN-side client devices and one or more WAN-side network resources. Operation of the vehicle entering a predefined operating state is detected, and in response thereto, the network connectivity mode is deactivated after a period of time during which the on-board wireless LAN interface and the on-board wireless WAN interface are collectively operated in a lower-power consumption state with respect to the set of on-board batteries and communications are discontinued between the one or more LAN-side client devices and the one or more WAN-side network resources via the on-board wireless LAN interface and the on-board wireless WAN interface.

Abstract: A network connectivity mode is activated at a vehicle during which an on-board wireless LAN interface and an on-board wireless WAN interface are collectively operated in a higher-power consumption state with respect to a set of on-board batteries to collectively support communications between one or more LAN-side client devices and one or more WAN-side network resources. Operation of the vehicle entering a predefined operating state is detected, and in response thereto, the network connectivity mode is deactivated after a period of time during which the on-board wireless LAN interface and the on-board wireless WAN interface are collectively operated in a lower-power consumption state with respect to the set of on-board batteries and communications are discontinued between the one or more LAN-side client devices and the one or more WAN-side network resources via the on-board wireless LAN interface and the on-board wireless WAN interface.