When a specification setting unit sets a specification of a lot number “k+1” after setting a specification of a lot number “k”, a mounting program selector performs a mounting program corresponding to the lot number “k”, and then selects a mounting program corresponding to the lot number “k+1” according to matching between a mounting number from the mounting program and a planned number of products of the lot number “k”. A printing program selector selects a printing program corresponding to the lot number “k”, and then selects a printing program corresponding to the lot number “k+1” according to matching between a sum of a printing number from the printing program and a defective product number and the planned number of products of the lot number “k”. Consequently, on-demand production of an electronic device can easily be manufactured on a manufacturing line.

A device for manufacturing an n-layered optical information carrier having an injection molding unit for manufacturing a carrier body with a first information layer, and furthermore, a first embossing unit for manufacturing a second information layer. The second information layer has an input via which information carriers can be received in the embossing unit. The embossing unit moreover has an output unit via which the coated information carriers are output. (n−2) additional embossing units are associated with the device, for manufacturing in each case an additional information layer, wherein “n” is greater than two. The respective units are linked to one another so that the n-layered information carrier is manufactured in an inline manufacturing. The (n−2) additional embossing units can be coupled to and uncoupled from the device, wherein the additional embossing units in each case have an input and an output unit.

To provide a numerical controller and a machine learning device that predict an abnormality, based on machine learning with perception of temporal change in data. The numerical controller includes the machine learning device provided with a learning unit that conducts machine learning of trends in operation of a machine on occasions of occurrence of abnormalities in the machine, based on time-series data acquired by a data logger device and relating to the operation of the machine and abnormality information relating to the abnormalities which have occurred in the machine and a prediction unit that predicts an abnormality which will occur in the machine, based on results of the machine learning in the learning unit and time-series data acquired by the data logger device and relating to current operation of the machine.

A misalignment sensing system for a molding structure and a method for using same. The molding structure includes a first component and a second component, at least one of the components being selectively repositionable between a closed configuration of the mold structure and an open configuration of the mold structure. The misalignment sensing system includes an alignment member including a male portion coupled to and extending from the first component of the molding structure, and a female portion defined in the second component of the molding structure, the female portion being configured to receive the male portion when the molding structure is in a closed configuration; and at least one sensor connected to one of the male and female portions and being configured to detect a deformation of any one of the male portion and the female portion, the deformation being induced by a misalignment of the molding structure.

A method for recording mass production work cycles of a facility. The facility having a machine and a replaceable mass production tool which is secured to the machine and is moved by the machine. According to the method, number sequences are formed that indicate how many cycles have been carried out by a specific tool in cooperation with a specific machine. The required detection of the cooperation of the particular tool with the particular machine is carried out on the basis of a comparison between the time curves of the values of two measured physical variables, wherein one physical variable is measured on the tool, and the second physical variable is measured on the machine, the two physical variables being such that the values thereof change cyclically with the rhythm of the work cycle carried out by the tool and the machine together.

Provided is a molding support apparatus that supports production of a molded product of a composite material, and the apparatus includes: a hardware processor that calculates a Talbot feature of the molded product, based on a Talbot image acquired from an X-ray Talbot imaging apparatus that images the molded product, and identifies, using the calculated Talbot feature, an item that allows adjustment of the Talbot feature from among a plurality of types of items constituting a production process for producing the molded product.

A method or system for industrial process optimization, including sensing data about an industrial process cycle that operates according to a set of process setpoints; determining a target performance for the process cycle based on the sensed data; selecting process set-points from a hypothesis space for a future industrial process cycle based on the target performance, and updating the hypothesis space.

There is disclosed a method (400) of operating a molding system (100), the method (400) executable by a controller (140) of the molding system (100). The method comprises appreciating (402) a plurality of operational parameters associated with the molding system (100); based on at least a sub-set of the plurality of operational parameters, generating (404) a machine performance index, the machine performance index being a single value representative of the at least a sub-set of the plurality of operational parameters and being instrumental in enabling an operator of the molding system (100) to appreciate an economic productivity factor associated therewith; causing (406) the machine performance index to be displayed on an interface of the controller (140).

To easily check a changing trend of machine state data on an injection molding machine during a predetermined period and/or in every predetermined period. An injection molding information management support device for managing machine state data regarding a machine state in operation of an injection molding machine during a predetermined period and/or in every predetermined period includes a machine state data acquisition unit that acquires a machine state data value for each molding cycle in the injection molding machine, and a frequency distribution data recording unit that converts the machine state data value into a preset class data value and records the class data value in a storage unit.

An information processing apparatus includes a controller. The controller is configured to obtain a measurement value of a sensor provided in mechanical equipment. The controller is configured to generate a first model by machine learning using the measurement value of the sensor measured in a first period of the mechanical equipment and store the first model in a storage portion. The controller is configured to generate a second model by machine learning using the measurement value of the sensor measured in a second period after a trigger event has occurred in the mechanical equipment and store the second model in the storage portion. The controller is configured to determine a state of the mechanical equipment by using the measurement value of the sensor measured in an evaluation period and the first model and the second model stored in the storage portion.