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.

The invention relates to a production machine with a control program for visualizing stations and/or machine components, highlighting the speed-determining station and/or the speed-determining machine component in order to optimize the process time. The invention also relates to a method of optimizing the process time for a production machine with such a control program and to a data carrier with such a control program.

A method of controlling an industrial gas production facility comprising: receiving time-dependent power data receiving time-dependent operational characteristic data; defining one or more power constraints for the operational parameters of the power network; defining one or more process constraints for the operational parameters of each industrial gas plant; generating, based on the power data, the operational characteristic data, the one or more power constraints and the one or more process constraints, control set point values for the one or more industrial gas plants to achieve a pre-determined production parameter for the industrial gas production facility; and sending the control set point values to a control system to control the one or more industrial gas plants by adjusting one or more control set points of the industrial gas plants to achieve the pre-determined production parameter for the industrial gas production facility.

The present invention is directed to a system and method for load balancing specimen containers between a plurality of automated detection apparatuses. The method may include receiving a specimen container at a container pick-up station in a first automated detection apparatus; determining loading ability, transfer status, and cell availability of the first automated detection apparatus and one or more downstream automated detection apparatuses; and transferring the specimen container from the first automated detection apparatus to a downstream automated detection apparatus when a first ratio of effective available cell count to effective capacity in the first automated detection apparatus is less than a second ratio of total effective available cell count to total effective capacity of a sum of the first automated detection apparatus and the one or more downstream automated detection apparatuses.

It is possible to more efficiently make a factory plan configured to maximize a productivity index.

Provided is a factory plan device including a calculation unit configured to specify a process and a production resource candidate based on a shape of a component of a target product by inputting past production performance data of a product, production volume data, design data of the product, specification data of a production resource, and layout data of a factory, and to calculate a process plan configured to determine order of the process and the production resource, a production plan configured to determine working date and time of the production resource, and a layout of the production resource so as to maximize a predetermined productivity index in the factory.

A method for processing a query for data stored in a distributed database includes receiving, at an edge device, the query for data stored in the distributed database from a query device. The method includes causing, by the edge device, the query to be stored on a dynamic ledger maintained by the distributed database. The method includes detecting, by the edge device, that summary data has been stored on the dynamic ledger. The method includes generating, by the edge device, an approximate response to the query based on the summary data stored on the dynamic ledger. The method includes transmitting, to the query device, the approximate response.

A method of configuring robot fleets with additive manufacturing capabilities includes receiving a request for a robotic fleet to perform a job and determining a job definition data structure based on the request. The job definition data structure defines a set of tasks to be performed in furtherance of the job. The method includes determining a provisioning configuration for each additive manufacturing system based on the task to which the additive manufacturing system is assigned, the set of 3D printing requirements, the printing instructions, and the status of the additive manufacturing system. The method includes provisioning the additive manufacturing system based on the provisioning configuration and a set of additive manufacturing system provisioning rules that are accessible to an intelligence layer to ensure that provisioned systems comply with the provisioning rules. The method includes deploying the robotic fleet based on the robotic fleet configuration data structure to perform the job.

A system and method for producing products based upon demand are disclosed. In some cases, the products include containers and the contents therein. The containers are disposed on vehicles and are independently routable along a track system and are deliverable to at least one unit operation station. A control system: receives demand for finished products; determines a route for vehicles based upon the status of one or more unit operation stations; and causes a vehicle to progress along a determined route to create one or more of the demanded finished products. The system may be used to produce the same fluent products, different fluent products, and other types of products including assembled products.

Some embodiments include electric power demand stabilization methods and systems that may include measuring the power draw of a plurality of controllable devices; determining a rolling average power draw for the plurality of controllable devices over a period of time; measuring an instantaneous power draw of the plurality of controllable devices; and calculating a power budget comprising the difference between the instantaneous power draw and the rolling average power draw. In the event the power budget is positive, increasing power to at least a first subset of the plurality of controllable devices. In the event the power budget is negative, decreasing power to at least a second subset of the plurality of controllable devices.

Provided are a system, method, and computer program product for optimizing a manufacturing process. The method includes receiving manufacturing data associated with a manufacturing process for manufacturing a product. The manufacturing data may include data from a plurality of data sources associated with a plurality of stages of the manufacturing process, and the manufacturing data may include values for a plurality of parameters including at least one process parameter value and at least one quality parameter value. The method includes generating a time-sequenced data structure including the manufacturing data and transforming the time-sequenced data structure to a positionally-dimensioned data structure based on timing data associated with the plurality of stages. The method includes determining a new value for the at least one process parameter value based on the positionally-dimensioned data structure and at least one algorithm and optimizing the manufacturing process based on the new value.