Methods for controlling a converter for converting glass tubes to glass articles include preparing condition sets including settings for a plurality of process parameters, operating the converter to produce glass articles, measuring attributes of the glass articles, operating the converter at each of the condition sets, associating each glass article with a condition set used to produce the glass article and the attributes measured, developing operational models from the attributes measured and the condition sets, determining run settings for each of the plurality of process parameters based on the operational models, and operating the converter with each of the process parameters set to the run settings determined from the operational models.

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.

Embodiments presented herein provide techniques for planning and scheduling in a factory. The technique begins by generating a bottleneck loading plan from a plurality of inputs. A simulation is run using the bottleneck loading plan. The factory is simulated using decisions made based on the bottleneck loading plan and a lot-to-machine schedule is generated with the simulation bottleneck loading plan.

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.

An apparatus is provided for generating electrical signals for stimulating a system under test (SUT). The apparatus comprises: a remote control panel configured to receive programming values and output programming signals; and a function generator. The function generator comprises: a communication port configured to receive the programming signals from the control panel; a memory configured to store instructions and predetermined values; a processor configured to process the programming signals and predetermined values according to the instructions stored in the memory; a digital-to-analog converter (DAC) configured to convert the processed signals into analog output signals; an output port configured to make the analog output signals available to the SUT; and an input port configured to receive second signals from the SUT.

A decision support tool to assist decision-making in the operation of a facility. The decision support tool allows a user to perform operational programming of the facility so that the analysis of specific operational events is flexible and on-demand. This is achieved by allowing the user to set scope and timeframe of the analysis according to business needs. As a result, the organization can make better-informed judgments whether to add operational activities and how to adjust the ones already formulated in the program. The decision support tool can also allow for the application of strategies to communicate intent behind the programming instructions and to improve the quality of business decisions.

Embodiments of the disclosure provide for intelligent model integration within a process simulation system. Some embodiments receive data associated with the operation of a plant, determine, using at least one specially configured algorithm and based on the received data, at least one qualifying dataset determined qualified to train an intelligent model, train the intelligent model using the at least one qualifying dataset, and deploy the trained intelligent model for use.

A decision support tool to assist decision-making in the operation of a facility. The decision support tool allows a user to perform operational programming of the facility so that the analysis of specific operational events is flexible and on-demand. This is achieved by allowing the user to set scope and timeframe of the analysis according to business needs. As a result, the organization can make better-informed judgments whether to add operational activities and how to adjust the ones already formulated in the program. The decision support tool can also allow for the application of strategies to communicate intent behind the programming instructions and to improve the quality of business decisions.

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.

Provided is a control apparatus comprising a control unit configured to control a control target by a control model machine-learned so as to output an operation amount of the control target according to a state of equipment provided with the control target; a simulation unit configured to simulate, by using a simulation model, the state of the equipment in a case where the operation amount, which is output by the control model, is given to the control target; and a stop unit configured to stop control of the control target by the control model, based on a simulation result.