An object of the invention is to quickly provide an effective recovery plan for a delay problem occurring at a manufacturing site. A dynamic production planning system includes a dynamic production planning device, and the dynamic production planning device includes a process actual result storage unit that includes a record of time spent on production for each item and process, a process plan actual result storage unit that includes a production facility of which usage is planned and assumed work time thereof for each item and process, and a recovery scenario generating unit configured to calculate, for each item and process, an index indicating a risk of a delay using the time spent on production and the production facility of which usage is planned and the assumed work time thereof for each item and process.

A planning tool used to facilitate more efficient design of a central plant is configured to provide an advanced user interface. The user interface includes a symbol palette with selectable symbols that represent resource suppliers, subplants, energy loads, and resource storage devices associated with a central plant. The user interface allows users to drag these symbols onto a workspace and form various connections between the symbols. The user interface provides feedback to the user and prevents improper connections by evaluating user inputs according to a set of rules. The rules define valid relationships between the resource suppliers, subplants, energy loads, and resource storage devices. The user interface also allows users to specify equipment contained within the subplants. After a central plant model is created via the user interface, users can simulate operation of a central plant according to the model for planning, budgeting, and/or design considerations.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A machining simulation device is a machining simulation device which performs a machining simulation of the machine tool that machines a machining target based on a machining program with a tool, and includes: a machine simulation unit which performs, based on a position command and a transfer characteristic of the machine tool, a simulation of the movement of the machine tool when the machine tool is operated based on the machining program so as to estimate the position of the tool; and a machining simulation unit which performs a machining simulation of the machining target based on information of the tool and the position of the tool that is estimated.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that can optimize a manufacturing plant's operations and/or production based on simulations that utilize information about the current and forthcoming manufacturing conditions to determine the optimal operational characteristics for the different plant devices. Methods may include obtaining, using data from a set of sensors, a set of current operational characteristics for multiple plant devices in a plant. Multiple manufacturing scenarios can be simulated using different sets of operational characteristics for plant devices in which at least one operational characteristic from the set of current operational characteristics is varied. A first manufacturing scenario can be determined that satisfies overall operational parameter(s) for one or more plant devices or for the whole manufacturing plant. Setting(s) of one or more plant devices can be adjusted based on a set of operational characteristics corresponding to the first manufacturing scenario.

An interactive assistance system and method for computer-aided control optimization for a technical system is provided. For example, a gas or wind turbine, in particular for optimizing the action sequence or the control variables of the plant (e.g. gas supply, compression), wherein an input terminal is provided for reading at least one status parameter providing a first system status of the technical system, and at least one setting parameter for adapting a reward function. A simulation module having a pre-trained neuronal network, simulating the plant, serves to simulate an action sequence on the technical system, starting from the first system status and to the prediction of the resulting statuses of the technical system.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A method for modifying a production process for a product wherein the production process can be qualified by means of at least one quality parameter for the product and includes a plurality of individual processes, in at least some of which no control is used. The method includes the following steps: a) capturing at least one measurement quantity of at least one individual process without control; b) determining a quality parameter corresponding to the at least one measurement quantity; c) comparing the determined quality parameter with a desired value, which results from the measurement-quantity-associated individual process with control; d) evaluating, on the basis of the comparison, whether the use of control for the at least one individual process leads to an improvement in the quality parameter.

The present invention optimizes the configuration of production lines in a facility, e.g., a factory or industrial facility, through, for example, analyzing scheduling, human factors and other operational information related to the production line and/or facility. In embodiments of the invention described here, facility configuration information is obtained. The configuration information includes an electronic model describing a configuration of machines in a production line. Order information is obtained for a product to be produced by the production line. Operational information related to operation of the production line is obtained. The facility configuration information, a demand information, and the operational information are analyzed to produce an optimal schedule for a usage of the production line. The schedule is applied to the production line.