A method of determining the resource efficiency of a plant for the production of drinks containers, wherein the plant has at least one resource-consuming part, wherein the part of the plant is operated at least for a time in a first operative state (B1) in which a product is produced and the part of the plant has a first resource consumption (V1) in this operative state (B1), and wherein the part of the plant is operated at least for a time in a second operative state (B2) and has a second resource consumption (V1) in this second operative state (B2), wherein at least one first resource consumption (V1) capable of being allocated to the first operative state (B1) and at least one second resource consumption (V2) capable of being allocated to the second operative state (B2) determined and the resource consumption (V1, V2) is allocated to the operative states (B1, B2). According to the invention a value characteristic of the resource efficiency of the part of the plant is determined while taking into consideration the first resource consumption (V1) and the second resource consumption (V2).

A controller for equipment obtains utility rate data indicating a price of one or more resources consumed by the equipment to serve energy loads. The controller generates an objective function that expresses a total monetary cost of operating the equipment over an optimization period as a function of the utility rate data and an amount of the one or more resources consumed by the equipment at each of a plurality of time steps. The controller optimizes the objective function to determine a distribution of predicted energy loads across the equipment at each of the plurality of time steps. Load equality constraints on the objective function ensure that the distribution satisfies the predicted energy loads at each of the plurality of time steps. The controller operates the equipment to achieve the distribution of the predicted energy loads at each of the plurality of time steps.

A building system includes building equipment operable to consume one or more resources and a control system configured to generate, based on a prediction model, predictions of a load on the building equipment or a price of the one or more resources for a plurality of time steps in an optimization period, solve, based on the predictions, an optimization problem to generate control inputs for the equipment that minimize a predicted cost of consuming the resources over the optimization period, control the building equipment to operate in accordance with the control inputs, monitor an error metric that characterizes an error between the predictions and actual values of the at least one of the load on the building equipment or the price of the one or more resources during the optimization period, detect an occurrence of a trigger condition, and in response to detecting the trigger condition, update the prediction model.

The technology herein developed arises from the need to monitor and automate the entire deep hole drilling, drilling and milling processes, in cutting machines, in order to not only optimize the relevant task performance but also to increase the useful life of the cutting tools involved. An operating system and method are disclosed that allow controlling the entire deep hole drilling, drilling and milling processes, acting directly and automatically on the control of the cutting parameters, such as for example drilling feed and cooling adjustment, by means of collecting and real-time analyzing of data from sensors arranged in said cutting machine.

An energy management system or plugin thereto includes a graphical user interface that displays visual elements corresponding to at least one manufacturing component and an energy management module instantiated in the graphical user interface. The energy management module is enabled to receive and display energy consumption status information from the manufacturing component and can control and modify the energy consumption of the manufacturing component by instructions sent from the energy management system to the component. The instructions can comprise a throttle instruction, an orchestrate instruction, or a disabled instruction which can be configured as predetermined presets corresponding to a desired energy protocol. The energy management module can also be used to group or sequence the components to distribute energy consumption to avoid exceeding the energy capacity of the manufacturing setting.

A facility that includes machines, includes a camera generating facility operation data, which includes an image of any given space. A computer system comprises: a data obtaining module obtaining the facility operation data; a work identification module identifying work that is performed in the facility, based on the image included in the facility operation data; and an output module outputting time-series information indicating a flow of the work. The work identification module identifies an object included in the image; identifies the work based on information about the identified object; and generates work analysis data, which associates the identified work, a period in which the identified work has been performed, and machines that is related to the identified work with one another. The output module outputs the time-series information or statistical information by using the work analysis data.

A management device includes a data acquisition unit that collects data related to power consumption supplied to a plurality of industrial machines from at least a power supply facility, a preprocessing unit that creates power consumption data based on the collected data, a decision making unit that determines a behavior of allocating a predetermined total suspension time to the plurality of industrial machines with respect to a current state of power consumption by the plurality of industrial machines with reference to a learning model associating a value of a behavior of allocating the predetermined total suspension time to the plurality of industrial machines with a state of power consumption by the plurality of industrial machines based on power consumption data, and a suspension time allocation unit that allocates the suspension time to the plurality of industrial machines.

A building system includes building equipment operable to consume one or more resources and a control system configured to generate, based on a prediction model, predictions of a load on the building equipment or a price of the one or more resources for a plurality of time steps in an optimization period, solve, based on the predictions, an optimization problem to generate control inputs for the equipment that minimize a predicted cost of consuming the resources over the optimization period, control the building equipment to operate in accordance with the control inputs, monitor an error metric that characterizes an error between the predictions and actual values of the at least one of the load on the building equipment or the price of the one or more resources during the optimization period, detect an occurrence of a trigger condition, and in response to detecting the trigger condition, update the prediction model.

To determine system settings for an industrial system, digital twin data of a digital twin of the industrial system is retrieved. System simulations of the industrial system are performed based on the digital twin data to explore candidate system settings for the industrial system prior to application of one of the candidate system settings to the industrial system. At least one optimization objective or at least one constraint used in the system simulations is changed while the system simulations are being performed on an ongoing basis. The results of the system simulations are used to identify one of the candidate system settings for application to the industrial system.

The embodiments herein relate to methods and apparatus for controlling a microgrid network. The microgrid comprises an energy negotiation resolution system configured to receive from each energy consuming component of the microgrid a list with information on power supply/production units; determine whether there is a conflict in priorities between received lists with regards to the listed energy production units, based on requests received from each energy consuming components; resolve the conflict when there is a conflict in priorities; and inform each energy consuming component involved in the conflict of the energy production unit to use as energy source. The embodiments also relate to the energy consuming component and a method therein.