A method for additive manufacturing includes identifying a discrepancy between a three-dimensional model and an object model. The three-dimensional model is a model of a three-dimensional object that is being constructed by an additive manufacturing process, and the three-dimensional object is being constructed based on the object model. The method further includes determining a reconfiguration recommendation based on the identified discrepancy. The method further includes reconfiguring the additive manufacturing process based on the reconfiguration recommendation.

A method for optimizing manufacturing data in a subtractive manufacturing system includes obtaining a model of and tolerance requirements for an object to be manufactured and performing measurements on the manufacturing system in a static condition. The method further includes simulating a manufacturing process in the manufacturing system using the obtained static information to obtain runtime information, determining which manufacturing data is responsible for producing each feature of the manufactured object, simulating manufacturing of the object, and comparing the simulated finished product of the object with the three-dimensional model of the object, detecting a deviation between the simulated finished product and the obtained tolerance requirements included in the model, and based on the detected deviation and the determination of which manufacturing data is responsible for producing each feature, optimizing the manufacturing data such that an object manufactured based on the optimized manufacturing data complies with the obtained tolerance requirements.

A method for manufacturing a plurality of components, each of the plurality of components including at least one electrical feedthrough, in which a functional element is fastened in a feedthrough opening in a base body by way of an electrically insulating material, an information being acquired in association with each of the plurality of components, the method comprising the steps of: providing, in one of a plurality of manufacturing steps of the method, each of the plurality of components or one of a plurality of pre-stages of each of the plurality of components with an information store, at least one of (i) the information being stored in the information store, and (ii) an identifier is stored in the information store and the information is stored in a database in association with the identifier.

The present disclosure discloses an Industrial Internet of Things (IIoT) with a dual independent platform, which comprises a user platform, a service platform, a management platform, a sensor network platform and an object platform that interact in turn. The service platform adopts centralized layout, and the management platform and the sensor network platform adopt independent layout. The present disclosure also discloses a control method of the IIoT with the dual independent platform. The present disclosure builds the IIoT based on the five platform structure, in which the sensor network platform and the management platform are arranged independently, and each corresponding platform includes a plurality of independent sub-platforms, so that the independent sensor network platform and the management platform can be used for each production line device to form an independent data processing channel and transmission channel, and reduce the data processing capacity and transmission capacity of each platform.

A testing method of a human-computer combination quality testing system includes steps of: after manufacture, importing relevant CAD models, submitting the CAD models to a digital testing part for being examined; if a product is determined to be unqualified, returning the product for retreatment; if the product is determined to be qualified, submitting the product to a manual testing part for being examined by relevant inspectors; if the product is determined to be qualified by the inspectors, leaving the product as a qualified product; if the product is determined to be unqualified by the inspectors, returning the product for retreatment; then changing the relevant rule with a rule corrector of a system improving part according to a misjudging condition of the digital testing part; describing a corrected rule, which is corrected by the developer, by a rule descriptor; then applying the corrected rule to a system by a rule parser.

The present disclosure discloses an Industrial Internet of Things (IIoT) system for automatic control of production line manufacturing parameters, which comprises a user platform, a service platform, a management platform, a sensor network platform and an object platform that interact in turn. The service platform adopts centralized layout, and the management platform and the sensor network platform adopt independent layout. The present disclosure also discloses a control method of the IIoT for automatic control of production line manufacturing parameters. The present disclosure builds the IIoT based on the five platform structure, in which the sensor network platform and the management platform are arranged independently, and each corresponding platform includes a plurality of independent sub-platforms, so that the independent sensor network platform and the management platform can be used for each production line device to form an independent data processing channel and transmission channel, and reduce the data processing capacity and transmission capacity of each platform.

A system and method for machine tool operations optimization is disclosed. The computer based system contains vibrational data for at least one machine tool, where the vibrational data is used to determine optimal machining, parameters for the machine tool and where an amount of profit improvement gained by adopting the optimal machining parameters is calculated.

Provided is a veneer sorting control device including: a sorting condition setting unit 11 that sets sorting conditions for each of a plurality of kinds of defects so as to sort a veneer into a plurality of quality ranks; a defect detection unit 13 that detects the plurality of kinds of defects with respect to each of a plurality of pieces of veneer image data acquired from an image storage unit 100; a quality rank sorting unit 14 that sorts a plurality of the veneers into a plurality of quality ranks in correspondence with the sorting conditions which are set and defect detection states; a first totalization unit 15 that totalizes the number or a number ratio of the veneers in the plurality of quality ranks which are sorted; and a display control unit 17 that displays the totalization result on a screen. The number of the veneers sorted into the plurality of quality ranks can be confirmed by a simulation using the veneer image data stored in the image storage unit 100.

A manufacturing system is disclosed herein. The manufacturing system includes one or more stations, a monitoring platform, and a control module. Each station of the one or more stations is configured to perform at least one step in a multi-step manufacturing process for a component. The monitoring platform is configured to monitor progression of the component throughout the multi-step manufacturing process. The control module is configured to dynamically adjust processing parameters of each step of the multi-step manufacturing process to achieve a desired final quality metric for the component.

A manufacturing system is disclosed herein. The manufacturing system includes one or more stations, a monitoring platform, and a control module. Each station of the one or more stations is configured to perform at least one step in a multi-step manufacturing process for a component. The monitoring platform is configured to monitor progression of the component throughout the multi-step manufacturing process. The control module is configured to dynamically adjust processing parameters of each step of the multi-step manufacturing process to achieve a desired final quality metric for the component.