Abb Schweiz Ag

Katharina Stark

Mario Hoernicke

Nicolai Schoch

Dirk Schulz

Marcel Dix

Sten Gruener

Roland Braun

Michael Vach

Jens Doppelhamer

Pablo Rodriguez

Somayeh Malakuti

Raoul Jetley

Prerna Juhlin

Prerna Bihani

A method for non-MTP module integration includes receiving by a wrapper unit logic signals, bus signals and material signals from a non-MTP module, wherein the non-MTP module is a physical module of a process plant, wherein the logic signals comprise information of logic connections and/or functions of the non-MTP module, wherein the bus signals comprise information of outputs of a fieldbus of the non-MTP module, wherein the material signals comprise information of material connections of the non-MTP module; converting, by the wrapper unit, the bus signals to open platform communication identifier architecture, OPC UA, nodes; determining, by the wrapper unit an MTP interface using the logic signals and the material signals; and determining, by the wrapper unit, a MTP conform digital black box module, using OPC UA nodes and the MTP interface.

Non-MTP module integration

A system for optimal drive configuration using machine learning; the system includes: a data collector configured to collect data and establish correlations among the collected data; a training data set generator configured to compute configuration sets based on the collected data and based on the established correlations, further configured to compute measured success values for the configuration sets, further configured to generate training data sets that include the configuration sets together with corresponding measured success values; a machine learning module, configured to predict predicted success values for calculated configuration sets using the training data sets provided by the training data set generator using machine learning algorithm; and an optimization module, configured to order the calculated configuration sets, including a simulation module, configured to simulate the calculated configuration sets.

System and method for optimal drive configuration using machine learning

A modular automation support system for modular plants comprises an automation engineering support system comprising a feedback processing component configured to modify the operation of one or more other components of the automation engineering support system based on user feedback.

Modular automation support system

A computer-implemented method includes obtaining an amount of a resource and/or capability of a process module, and dividing this amount by the maximum amount of the respective resource and/or capability to obtain a theoretical utilization of the resource and/or capability as the theoretical utilization of the process module. A pool of available process modules is searched to identify candidate process modules to replace the process module. The theoretical utilization for each candidate module is determined and an optimized topology of the plant is generated by replacing the process module with a candidate process module that has a same or a higher theoretical utilization than process module.

Computerized optimization of an engineered modular plant topology

A method of generating control code for an industrial plant comprises: defining control logic for controlling the industrial plant by editing a cause-and-effect matrix provided by an engineering tool, wherein the defining comprises defining both instrument-based control logic and service-based control logic using the same cause-and-effect matrix; and generating the control code for controlling the industrial plant on the basis of the defined control logic.

Generating control code for an industrial plant

A modular automation support system for modular plants includes an engineering support system comprising a control and execution engine configured to: receive data from a monitoring infrastructure of a modular plant and convert that data into semantic data which conforms to a semantic data model; use one or more semantic rules or mechanisms relating the semantic data received from the monitoring infrastructure to services provided by modules of a pipeline of the modular plant to control the pipeline in executing a process.

A computer-implemented resource management method for modular plants may include: receiving data identifying a required module type to be assembled into the modular plant as part of a module pipeline including one or more modules; and executing an optimization algorithm to select, from a plurality of modules having the required module type, a module for inclusion in the module pipeline on the basis of one or more predetermined optimization criteria.

Resource management for modular plants

A method for configuring a modular industrial plant using an engineering tool includes using a plant engineering facility of the tool to create a representation of the modular industrial plant identifying modules to be orchestrated in the modular industrial plant. The modules include at least one function module that includes control software for the modular industrial plant. The method further includes using a module engineering facility of the tool to configure the function module for use in the modular industrial plant by editing a placeholder configuration file created by the tool for defining the configuration of the function module. Editing the configuration file causes a representation of the function module in the plant engineering facility to be automatically updated to reflect adaptations made to the function module using the module engineering facility. The method includes instructing the tool to assign the function modules so configured to the modular industrial plant.

Configuring modular industrial plants

An apparatus includes: a process control system; at least one process module; and a process module logic entity associated with the at least one process module. The process control system communicates with the at least one process module via a process module interface. The process module logic entity provides a control logic of the at least one process module.

Apparatus comprising a process control system and at least one process module, related method, computer program product, and data processing device

The disclosure describes a method associated with a simulation model of a process module configured to execute at least one module service. The process module is interlinkable or interlinked with further process modules to carry out a technical process in a cascade of module services, and includes Providing a process logic specification of the technical process, a control logic specification of the process module, a state engine of the process module from a configuration of the at least one service, and a process connection information of the technical process; Generating at least a part of the simulation model from a combination thereof, and Linking at least a part of the generated simulation model to a module type package for the process module, or extending a module type package for the process module by at least a part of the generated simulation model.

Method associated with a simulation model of a process module, computer program product, and non-volatile data storage medium

A computer-implemented method for determining an operational state of an industrial plant includes acquiring alarms raised within the plant and adding them to a pool of important alarms, determining whether a physical state of the plant indicated by a first alarm causes a second alarm or meets a predetermined state-dependent condition and, if so, moving the first alarm to a pool of informative alarms; and determining the operational state of the plant and/or a corrective action for improving this operational state based on the alarms in the pool of important alarms.

Computer-implemented method for determining an operational state of an industrial plant

A method for custom logic engineering in an industrial modular plant executing a production process includes receiving process data for the production process using at least one physical process module; determining a custom process topology by selecting, based on the received process data, at least one module type package, MTP; correlating to the at least one respective physical process module from a database, wherein the module type package is a digital representation of the respective physical process module; selecting at least one extender unit from the database based on the received process data; representing a logical function of the production process; determining connections between the extender unit(s) and the at least one MTP; setting properties of the extender unit(s) based on the received process data; and determining an extended control scheme for controlling dynamic behavior of the production process using the determined custom process topology.

Custom logic engineering of an industrial modular plant

An engineering system for orchestration of an industrial plant includes: a modular plant to be orchestrated including at least one processor from a topology having: a process orchestration layer, and a plurality of modules. A portion of the plurality of modules are formed as at least one combined module. Each combined module of the at least one combined module has at least two different modules of the portion of the plurality of modules. The process orchestration layer controls the plurality of modules. The control by the process orchestration layer includes in-direct control of the portion of the plurality of modules via control of the at least one combined module.

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Weinheim, Germany

Katharina Stark