Abstract: The present disclosure promotes distribution of sensor data among a plurality of business operators. A controller that an information processing system according to the present disclosure includes collects first data including a plurality of items and personal information from mobile bodies belonging to a first business operator. The controller converts the first data to second data not being usable to identify individuals. The controller provides data in a range decided based on content of a predetermined data use contract, among the second data, to a second business operator. The controller calculates a consideration for the data that is to be paid by the second business operator, based on a data use record of the second business operator.

Abstract: The vehicle power supply apparatus includes: a drive power supply that supplies electric power to a motor for generating drive power; an auxiliary power supply that supplies electric power to a motor controller and door lock controllers; and a backup power supply. A control method for the vehicle power supply apparatus includes: discharging the in-vehicle equipment by using the electric power that is supplied from the backup power supply when it is determined that a vehicle has collided with an obstacle; and operating the door lock controllers by using the electric power that is supplied from the backup power supply after a lapse of a specified time period since initiation timing of the discharging step so as to unlock doors.

Abstract: A machining condition adjustment device includes a data acquisition unit that acquires at least one piece of data indicating a state of machining including a machining type in a machine tool, a priority condition storage unit that stores priority condition data in which the machining type is associated with a priority condition, a preprocessing unit that produces data to be used for machine learning, and a machine learning device that carries out processing of the machine learning related to at least either of a machining condition and a machining parameter for machining by the machine tool. The machine learning device includes a learning model storage unit that stores a plurality of learning models generated for each machining type and a learning model selection unit that selects a learning model, based on the machining type.

Abstract: An injection molding system includes a measuring unit to measure a movement of a line of sight of a worker observing a molded article, a line-of-sight data storage unit to store line-of-sight information representing movements of the worker's line of sight and a measurement time, an identifying unit to identify a focus area of the molded article, a focus area storage unit to store an image of the identified focus area, a molding defect type input unit to input or select a molding defect type, and a machine learning device to machine learn the molding defect type from the image of the focus area. The machine learning device inputs a type of a molding defect that has occurred in the molded article and carries out machine learning to learn and automatically recognize a feature quantity of the molding defect from the image of the focus area.

Abstract: The present disclosure promotes distribution of sensor data among a plurality of business operators. A controller that an information processing system according to the present disclosure includes collects first data including a plurality of items and personal information from mobile bodies belonging to a first business operator. The controller converts the first data to second data not being usable to identify individuals. The controller provides data in a range decided based on content of a predetermined data use contract, among the second data, to a second business operator. The controller calculates a consideration for the data that is to be paid by the second business operator, based on a data use record of the second business operator.

Abstract: A machine learning device provided in a worker management device observes, as state variables representing a current state of an environment, worker external state data indicating an external state of a worker and manufacturing machine state data indicating a state of a manufacturing machine, and acquires, as label data, worker status data indicating a status of the worker. The machine learning device then learns the worker external state data and the manufacturing machine state data in association with the worker status data by performing supervised learning using the observed state variables and the acquired label data.

Abstract: An injection molding system includes a measuring unit to measure a movement of a line of sight of a worker observing a molded article, a line-of-sight data storage unit to store line-of-sight information representing movements of the worker's line of sight and a measurement time, an identifying unit to identify a focus area of the molded article, a focus area storage unit to store an image of the identified focus area, a molding defect type input unit to input or select a molding defect type, and a machine learning device to machine learn the molding defect type from the image of the focus area. The machine learning device inputs a type of a molding defect that has occurred in the molded article and carries out machine learning to learn and automatically recognize a feature quantity of the molding defect from the image of the focus area.

Abstract: The vehicle power supply apparatus includes: a drive power supply that supplies electric power to a motor for generating drive power; an auxiliary power supply that supplies electric power to a motor controller and door lock controllers; and a backup power supply. A control method for the vehicle power supply apparatus includes: discharging the in-vehicle equipment by using the electric power that is supplied from the backup power supply when it is determined that a vehicle has collided with an obstacle; and operating the door lock controllers by using the electric power that is supplied from the backup power supply after a lapse of a specified time period since initiation timing of the discharging step so as to unlock doors.

Abstract: An injection molding management system includes: a molding information storage unit configured to store molding information on the usage of each type of molding material used in forming product molding, for each kind of molding; a remaining product quantity calculator configured to calculate the remaining product quantity of each kind of molding; a total usage calculator configured to calculate the total usage of each type of molding material used in the injection molding machines, based on the molding information of each kind of molding and the remaining product quantity of molding; a stock quantity storage unit configured to store the stock quantity of molding material; and an order quantity calculator configured to calculate the order quantity of each type of molding material, based on the total usage and the stock quantity of the molding material.

Abstract: In an injection molding system, a molded part transport apparatus and a worker share an area to perform cooperative work. When a molded part check mode is valid, conforming product identification inspection of a molded part is performed in an area where the worker works, and molded part sorting means sorts the molded part on the basis of a result of the inspection. As a result, the conforming product identification inspection of the molded part can be performed and the molded part can be sorted with the safety of the worker is maintained.

Abstract: A machining condition adjustment device includes a data acquisition unit that acquires at least one piece of data indicating a state of machining including a machining type in a machine tool, a priority condition storage unit that stores priority condition data in which the machining type is associated with a priority condition, a preprocessing unit that produces data to be used for machine learning, and a machine learning device that carries out processing of the machine learning related to at least either of a machining condition and a machining parameter for machining by the machine tool. The machine learning device includes a learning model storage unit that stores a plurality of learning models generated for each machining type and a learning model selection unit that selects a learning model, based on the machining type.

Abstract: An injection molding system includes a sensor that detects a state of a purged molding material, and a purged material analysis unit that obtains a detection signal of the sensor and analyzes the purged molding material. Whether or not the purge operation is completed is determined based on the detection signal of the sensor so as to complete the purge operation. The purge operation is thus allowed to be completed with a minimum purge amount.

Abstract: A manufacturing cell includes an allowable range setting unit configured to set an allowable range for physical quantity data or statistical processing data, and data output unit configured to output, in a case where the physical quantity data or the statistical processing data deviates from the allowable range, output information. The manufacturing cell further includes an abnormality information determination unit configured to compare the physical quantity data or the statistical processing data of a manufacturing cell as an abnormality source, with the retained physical quantity data or the retained statistical processing data of the manufacturing cell, to determine whether or not the abnormality is inherent to the manufacturing cell as the abnormality source, and a determination result notification unit for notifying a determination result.

Abstract: In an injection molding system, a holding force changing means reduces a holding force to a predetermined level or less if a predetermined or higher load is detected by an external load detection means after a molded article is transported to a work area of an operator by a molded article transport device. Thus, the operator can easily take out and inspect the molded article.

Abstract: Disclosed is an injection molding system including: a state observation section observing, when injection molding is performed, physical-amounts relating to the injection molding that is being performed; a physical-amount data storage section storing the physical-amount data; a reward-conditions setting section setting reward conditions for machine learning; a reward calculation section calculating a reward based on the physical-amount data and the reward conditions; an operating-conditions adjustment learning section performing machine learning of adjusting operating conditions based on the reward calculated by the reward calculation section, the operating conditions, and the physical-amount data; a learning-result storage section storing a learning result of the machine learning by the operating-conditions adjustment learning section; and an operating-conditions adjustment-amount output section determining and outputting an operating condition to be adjusted and an adjustment amount based on the machine lea

Abstract: An injection molding system includes a plurality of inspection apparatuses for inspecting molded article quality, a unit that transports a molded article molded by an injection molding machine, a molded article containment unit that is provided for each of types of post-treatment operations needed for the molded article, a transport destination designation unit that selects and designates the molded article containment unit to contain the molded article on the basis of a combination of inspection results from the plurality of inspection apparatuses, and a molded article sorting and transport unit that sorts and transports the molded article into the molded article containment unit designated by the transport destination designation unit.

Abstract: A machine learning device provided in a worker management device observes, as state variables representing a current state of an environment, worker external state data indicating an external state of a worker and manufacturing machine state data indicating a state of a manufacturing machine, and acquires, as label data, worker status data indicating a status of the worker. The machine learning device then learns the worker external state data and the manufacturing machine state data in association with the worker status data by performing supervised learning using the observed state variables and the acquired label data.

Abstract: In an injection molding system, an insert formed with a cavity or an insert member for molding an insert-molded article is shot by a camera, and the insert or the insert member to be inserted into a mold is identified based on a characteristic of the insert or the insert member shot by the camera and previously stored data on the insert or the insert member.

Abstract: An injection molding management system includes: a molding information storage unit configured to store molding information on the usage of each type of molding material used in forming product molding, for each kind of molding; a remaining product quantity calculator configured to calculate the remaining product quantity of each kind of molding; a total usage calculator configured to calculate the total usage of each type of molding material used in the injection molding machines, based on the molding information of each kind of molding and the remaining product quantity of molding; a stock quantity storage unit configured to store the stock quantity of molding material; and an order quantity calculator configured to calculate the order quantity of each type of molding material, based on the total usage and the stock quantity of the molding material.

Abstract: A manufacturing cell includes an allowable range setting unit configured to set an allowable range for physical quantity data or statistical processing data, and data output unit configured to output, in a case where the physical quantity data or the statistical processing data deviates from the allowable range, output information. The manufacturing cell further includes an abnormality information determination unit configured to compare the physical quantity data or the statistical processing data of a manufacturing cell as an abnormality source, with the retained physical quantity data or the retained statistical processing data of the manufacturing cell, to determine whether or not the abnormality is inherent to the manufacturing cell as the abnormality source, and a determination result notification unit for notifying a determination result.