Abstract: Provided is a production management system including: an operational data acquisition unit for acquiring operational data regarding a production element in a target production process as a target among a plurality of production processes for producing a product from a material; a quality data acquisition unit for acquiring, as quality data indicating quality of a target product, feedback data for evaluating the production element in the target production process based on quality of a downstream product in the target production process, the feedback data being output from a production management system for managing a downstream production process of producing the downstream product by using, as a material, the target product; an analysis unit for analyzing the operational feedback data; and a control information decision unit for deciding control information for controlling the production element in the target production process based on an analysis result.

Abstract: Disclosed are methods and systems for administering or managing a 3D-printing-based manufacturing process. The methods and systems can be tailored or optimized for administering or managing a 3D-printing-based manufacturing process where the products are made on demand for customers in response to orders received via an online retail website. In one embodiment, a method comprises generating a stock identifier used to identify a product during and after manufacturing, creating a plurality of jobs to be undertaken to manufacture the product, assigning a job status to each of the plurality of jobs associated with the stock identifier, and assigning the jobs associated with the stock identifier to various 3D printers and workers.

Abstract: A method for activating a vaporizer device may include a point-of-sale device receiving, based on an identifier of the vaporizer device, activation data associated with the vaporizer device. The vaporizer device may be activated by communicating, to the vaporizer device, the activation data. The point-of-sale device may communicate the activation data to the vaporizer device via a dock coupled with the vaporizer device. Moreover, the point-of-sale device may communicate the activation data to the vaporizer device through a packaging of the vaporizer device. Alternatively, the point-of-sale device may communicates the activation data to the vaporizer device by communicating the activation data to a computing device associated with a user of the vaporizer device. The computing device may further communicate the activation data to the vaporizer device via audio signals and/or optical signals corresponding to the activation data. Related systems and articles of manufacture are also provided.

Abstract: A mover system includes a track, a plurality of movers configured to move along the track, and one or more processors. The one or more processors are configured to receive a user input indicative of operational parameters for the mover system, determine operating settings for the mover system based on the operational parameters, and cause the plurality of movers to operate in accordance with the operating settings.

Abstract: A manufacturing condition optimization apparatus includes a yield estimator for estimating a yield of a product having a quality that passes inspection by inspection equipment when a manufacturing condition of the product that is manufactured by manufacturing equipment is changed and an optimization processor for calculating an amount of change in the manufacturing condition at which the yield is maximized.

Abstract: A heating ventilating or air conditioning (HVAC) system includes a unit configured for use in a heating or a cooling operation for an environment. The unit includes an interface configured to receive electric energy from an alternative energy source and a controller configured to perform an optimization of an objective function for the unit to determine a first amount of electric energy to receive from an energy grid and a second amount of the electric energy from the alternative energy source for use in the heating or cooling operation at each time step of an optimization period in response to a cost characteristic of the electric energy received from the energy grid. The unit is configured to use the first amount and the second amount for the heating or cooling operation.

Abstract: Disclosed herein are methods of manufacturing an oral appliance, the method comprising the steps of: a) importing into a computer aided design (CAD) computer program a digitized data set obtained from a three-dimensional scan of a patient's dentition; b) preparing a three-dimensional electronic model of the patient's dentition; c) subtracting the three-dimensional electronic model of the patient's dentition from an image of a solid block to obtain an appliance data set; and d) manufacturing a dental appliance in accordance with the appliance data set. Also disclosed are devices made by the above method, and methods of treating a condition, for example a sleep breathing disorder, by using a device made by the above method.

Abstract: A system for fabricating coded lenses includes a cutting tool configured to controllably cut a workpiece at a specified position-dependent depth while traversing a surface of the workpiece along a specified two-dimensional path. A signal generator is operative to generate a signal for controlling fabrication of a coded lens from the workpiece. A vibration tool is operative to ultrasonically vibrate the cutting tool for cutting of gratings on the workpiece.

Abstract: The robotic maintenance vehicle (RMV) has a propulsion system, a control system, an electrical power source, a maintenance module, a multi-axis robot, an optical system, and a location translator. The maintenance module is configured to hold different kinds of road maintenance materials. The multi-axis robot is configured to convey the road maintenance material from either the maintenance module to the road, the road to the maintenance module, or both. The optical system and the location translator are configured to be controlled by the control system and operate in conjunction to instruct the multi-axis robot where to pick up and/or place the road maintenance material. The multi-axis robot is configured to be selectively coupled to a distal arm tool.

Abstract: A time modular system architecture capable of deforming energy industrial information productive inventories as a current demand topography evolves over time is provided. In embodiments, the system comprises an energy source, a productive component, a network component and a digital component. The energy source outputs energy. The productive component comprises a product (taken in the expansive meaning of any goods or services produced in the economy) output by the system. The network component connects the energy source to the productive component. The digital component determines shifts in demand of the productive component, manages automated systems, and optimizes the energy source based on the shifts in demand of the productive-consumptive component. Each of the energy source, network component and productive component are dynamically modified to optimize utilization based on supply and demand to deliver higher economic and societal intensity per unit of energy source(s).

Abstract: Provided is a production management system including: an operational data acquisition unit for acquiring operational data regarding a production element in a target production process as a target among a plurality of production processes for producing a product from a material; a quality data acquisition unit for acquiring quality data indicating quality of a target product; an analysis unit for analyzing the operational and quality data to estimate an influence, caused by an upstream product, on the quality of the target product, the upstream product being a product of an upstream production process and serving as a material in the target production process; and a feedback unit for outputting, based on an analysis result, feedback data for evaluating a production element in the upstream production process based on the quality of the target product in the upstream production process.

Abstract: A method for processing a takt at a station includes: obtaining takt data of each station within a preset time period, and determining a takt boxplot of each station according to the takt data; obtaining a material blocking time, a material shortage time and a failure time in each takt, determining an effective takt of each station based on the takt data, the material blocking time, the material shortage time and the failure time, and determining an effective takt mode; obtaining planning takt data of each station, generating a station takt wall station based on the takt boxplot, the effective takt mode and the planning takt data; determining a takt fluctuation status and a bottleneck of each station according to the station takt wall. A system for processing a takt at a station, an apparatus, and a storage medium are also disclosed.

Abstract: A control device having the function of creating new setting parameters, which are candidates of a parameter to be applied when updating old software to new software, is provided with a software information storage unit, a recommended parameter creating unit, and a parameter storage unit, wherein the software information storage unit acquires and stores, from a storage medium, new software including new item information and candidate value information relating to the parameter, the recommended parameter creating unit creates new recommended parameters on the basis of the new item information and the candidate value information, and the parameter storage unit stores one of the new recommended parameters selected by an operator as a new setting parameter.

Abstract: Methods and apparatus for processing a substrate are provided herein. For example, a method comprises in a process chamber, processing a substrate in a presence of an electric field, subsequently capturing an image of the substrate, determining whether substrate arcing occurred based upon analysis of the captured image, and one of continuing processing of the substrate when no arcing is determined or stopping processing of the substrate when arcing is determined.

Abstract: Systems and processes for designing and generating personalized surgical implants and devices are described herein. In various embodiments, the process includes generating patient-specific implants designed for increased osseointegration and improved surgical outcomes. In various embodiments, the process includes extracting patient-specific data with one or more aspects of an anatomical feature, processing the one or more aspects of the anatomical feature to identify and classify a deformity, create a density map of the one or more aspects of the anatomical feature, and generating a patient-specific implant or device based on the deformity classification, the density map, or a combination thereof.

Abstract: To ensure robustness to a production variation. A control rule generating device for generating a control rule of a production facility including at least a production device, includes: a rule storage unit configured to store candidates of a dispatching rule serving as the control rule usable for each of the production facility and a control program for implementing the dispatching rule; and a control rule assigning unit configured to specify, for each of the production facility, the dispatching rule corresponding to a predetermined production plan among the candidates of the dispatching rule as the dispatching rule to be applied, and transmit the control program corresponding to the specified dispatching rule to the production facility.

Abstract: In an approach to improve manufacturing quality, embodiments of the present invention dynamically monitor a degree of influencing factors in a predetermined area, and identify one or more machines used in a predetermined manufacturing process. Further, embodiments generate a digital twin of a predetermined final product associated with the predetermined manufacturing process, and analyze an effect of the influencing factors on the identified one or machines or the predetermined final product. Additionally, embodiments identify upper limit of the influencing facts, and output proposed changes to prevent the effects of the influencing factors based on the identified upper limit.

Abstract: Disclosed is a method for monitoring a production process using limit values for a technical parameter of units produced by the production process or for a technical parameter of the production process. The values of the technical parameter of units produced by a production process or of a technical parameter of a production process are distributed according to an underlying distribution. The distribution is characterized by an asymmetric probability density function (700) or by an asymmetric cumulative distribution function (CDF). The method comprises: comparing at least one value of the technical parameter with an interval that is asymmetric with regard to a characteristic value of the distribution, and monitoring the production process based on the result of the comparison.

Abstract: 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.

Abstract: Provided is a model verification apparatus including a model storage unit configured to store a machine learning model that has been subjected to machine learning, by using a learning sample including state data indicating a state of equipment in which a controlled object is provided and action data indicating an action for deciding a manipulated variable to be applied to the controlled object, so as to output an action according to the state of the equipment, a learning range identification unit configured to identify a learning range indicating a range of the learning sample, a verification data acquisition unit configured to acquire verification data indicating a plurality of states of the equipment outside the learning range, and a verification result output unit configured to output a verification result indicating a plurality of actions to be output by the machine learning model in response to an input of the verification data.