Siemens Aktiengesellschaft

Jens Schnittger

Hans-Henning Klos

Wolfgang Riedl

Benjamin Kohler

Ralf Gross

Giovanni Venturi

Stephan Grimm

Christoph Paulitsch

Ernesto Montaldo

Vladimir Lavrik

Felix Baer

Niklas Buerger

Alois Haselböck

Richard Taupe

A method and an automation component for identifying a process-disrupting automation component in an industrial automation assembly, wherein a process disruption is determined in a first automation component and examined by a first local analysis device, where an automation component arranged upstream and/or an automation component arranged downstream is first determined by each automation component, an interrogation message is sent from a first automation component to a second automation component and the same interrogation message or a further interrogation message is recursively sent by the second automation component to a third automation component arranged upstream or downstream of the second automation component and processed, where in the event of a locally determined disruption, the relevant automation component sends a response message, which is back-propagated to the origin and signaled such that a decentralized error analysis becomes possible, even with a changing system topology, without the need for any redesign work.

Method for identifying a process-disrupting automation component in a concatenated automation assembly

A method provides predictions of key performance indicators of a product variant of a product family manufactured by a complex manufacturing system in a manufacturing process. The method provides a manufacturing operation model for each manufacturing operation type used to manufacture a product variant of the product family. Via the complex manufacturing system measured contributions to key performance indicators, process context data and process execution data of manufacturing operations, are provided. The model parameters of the provided manufacturing operation models are learned automatically based on collected process context data, collected process execution data, and measured contributions to key performance indicators, to update the manufacturing operation models. An updated production efficiency model combining updated manufacturing models including the updated manufacturing operation models, to calculate the predictions of the key performance indicators, of the product variant, to be manufactured, depending on a product configuration of the respective product variant, is evaluated.

Method and apparatus for providing predictions of key performance indicators of a complex manufacturing system

A system and a method for managing a buffer system contain compartments for stocking contents needed for a production of products. The method includes: a) a determination from an initial configuration of the buffer system and a stack of orders of a production cycle and a configuration of the buffer system enabling an execution of the production cycle. The determination is completed by carrying out a virtual filling of the compartments with content required by the orders; b) providing instructions controlling content filling/emptying actions to a transport system for filling and/or emptying compartments; c) triggering an execution of the production cycle by the production equipment while recording usage of buffer system content; and d) updating the stack of orders after the end of the execution of the production cycle by removing from the stack of orders all orders which have been fully executed during the execution of the production cycle.

Method and system for automatic management of a buffer system

A method for computer-aided processing of state messages in an automation installation, wherein state messages are generated by components and detected with their generation points in time, where causative states present at the generation point of the state message or beforehand in other components are determined for a multiplicity of state messages of a respective component and the current state in the generated state message, where the propagation time between occurrence of the respective causative state and the generation point of the state message is calculated for each causative state, where groups are formed from the causative states, where in a respective group all causative states have at least the common feature that they were determined for the same current state in the respective component, and where at least one statistical parameter is determined from the propagation times which belong to the causative states of the same group and stored.

Method for computer-aided processing of state messages in an automation installation

Growing community of inventors

Lonnerstadt, Germany

Jens Schnittger