Methods, systems, and apparatus's for improving orthodontic treatments. In an embodiment, an orthodontic tracking template is provided for assisting in determining whether a patient's teeth are in an appropriate tooth arrangement for transitioning between a wire and bracket orthodontic treatment to a patient-removable orthodontic appliance treatment. The tracking template may include a shell portion defining a plurality of tooth-receiving cavities arranged to fit over at least a portion of the patient's teeth in an intermediate tooth arrangement without applying a tooth-moving force to the teeth or to any brackets attached to the teeth.

Methods, systems, and apparatus's for improving orthodontic treatments. In an embodiment, an orthodontic tracking template is provided for assisting in determining whether a patient's teeth are in an appropriate tooth arrangement for transitioning between a wire and bracket orthodontic treatment to a patient-removable orthodontic appliance treatment. The tracking template may include a shell portion defining a plurality of tooth-receiving cavities arranged to fit over at least a portion of the patient's teeth in an intermediate tooth arrangement without applying a tooth-moving force to the teeth or to any brackets attached to the teeth.

Provided is a molding machine management system that manages production of a plurality of molding machines, including: a display unit configured to display a production performance and a planned production status in association with a time axis for each molding machine, and, when the molding machine management system receives an abnormality of a molding machine, to display the abnormality of the molding machine in association with the time axis for each molding machine. The molding machine management system configured as described above can appropriately manage each molding machine.

First training data including a set value related to a molding machine, a measured value obtained by measuring a physical quantity related to molding, and a degree of quality of a molded product generated by the molding machine is collected, a first learning model for outputting a degree of quality of a molded product when a set value and a measured value are input is generated by machine learning based on collected first training data, second training data including a defect degree for each defect type of a molded product, a measured value, and a set value capable of reducing the defect degree is collected, and a second learning model for outputting a set value capable of reducing a defect degree when a defect degree and a measured value are input is generated by machine learning based on collected second training data and a degree of quality output from the first learning model.

A method for monitoring a molding process carried out in cycles includes determining at least two nearest neighbors in the form of cycle data from at least two past cycles, such that the cycle data of the at least two nearest neighbors lie nearer to the current cycle data than the cycle data which do not pertain to the at least two nearest neighbors. Only those past cycles for which quality data are contained in the data collection are used for the determination of the at least two nearest neighbors. A predictability criterion is checked to determine whether a quality variation of the quality data of the cycles of the at least two nearest neighbors is smaller than a maximum variation and/or larger than a minimum variation. If the predictability criterion is not met, a first notification that a quality and/or a quality datum of the molded part is not reliably predictable is issued.

Method for improving a cycle time of a molding system operating in cycles, wherein the molding system is set up to produce molded parts in cycles, wherein the cycles include partial phases, for at least one partial phase or at least one group of partial phases a partial phase duration is measured or ascertained with reference to settings of the molding system, an optimum partial phase duration is calculated for the at least one partial phase or the at least one group of partial phases on the basis of a machine configuration, if the measured or ascertained partial phase duration deviates from the optimum partial phase duration by more than a predefined amount, an indication that the setting of the molding system is improvable with respect to the at least one partial phase or the at least one group of partial phases is issued.

An injection molding system includes: an injection molding machine configured to operate in accordance with a command generated using a first language, and inject a molten material into a mold to mold a molded object; a robot configured to operate in accordance with a command generated using a second language, and convey the molded object; and a control device configured to control the injection molding machine and the robot. When determining that an error occurs in at least one of the injection molding machine and the robot, the control device transmits, to the injection molding machine, a command generated using the first language and for causing the injection molding machine to execute a return operation, and transmits, to the robot, a command interpretable by the second language and for causing the robot to execute a return operation, so as to cause the injection molding machine and the robot to execute the return operations.

A molding management apparatus includes an operation section as a selection section that selects an objective variable, a correlation calculation section that calculates a correlation between time series data corresponding to an objective variable and a plurality of time series data sets corresponding to explanatory variables describing the objective variable, and a display section for displaying a plurality of time series data sets corresponding to the explanatory variable in a display mode based on correlation, and displaying the time series data corresponding to the objective variable and the plurality of time series data sets corresponding to the explanatory variable displayed in a display mode based on correlation along a common time axis.

Provided is an apparatus for taking out a molded product, which is capable of determining occurrence of a suction error and/or likelihood of a suction error of the molded product with high accuracy and of knowing a cause thereof. A pressure data storing section stores time-series pressure data from a pressure detector. A suction error cause determining section determines occurrence of a suction error and/or likelihood of a suction error of a molded product by a suction member on a basis of a time-series comparison result obtained by comparing the stored time-series pressure data with predetermined time-series reference data. When the suction error cause determining section determines the occurrence of the suction error and/or the likelihood of the suction error, the suction error cause determining section determines a cause of the occurring suction error and a solution therefor based on a time-series change pattern.

Amorphous metals are a new class of materials in which advantageous physical properties can be achieved. Amorphous metals require rapid cooling in the injection-molding process, which is not achieved in the case of a large number of geometries. The invention relates to a method for adapting a component description of a workpiece to be produced with amorphous properties, which method comprises: —defining a cooling behaviour of at least a part of a workpiece to be produced, taking account of a component description of the workpiece; —adapting at least a part of the component description, taking account of the defined cooling behaviour of the workpiece.