A worked surface of a workpiece is evaluated on the basis of how the surface is actually perceived by a person's (observer's) eyes (vision) or fingers (touch), and a work process whereby a workpiece is worked is changed on the basis of the evaluation.

A Self-monitoring manufacturing system adapted to produce at least one object. The system includes at least a first processing facility adapted to perform a respective first processing step with the object, and a production control unit, wherein the production data comprises nominal pre-processing object data. A production monitoring unit for checking a pre-processing object state of the object is arranged, such unit being adapted to obtain actual property data of the object in-line of the production in-advance of applying the first processing step, to generate deviation data by comparing the actual property data with the production data for the first processing step, and to provide the deviation data for performing the first production step with the first processing facility in deviation-adjusted manner.

A manufacturing management apparatus includes an operation information acquisition unit, a trace information acquisition unit, a storage unit, a manufacturing device determination unit, and a transfer destination indication unit. The storage unit stores inspection information on each article in association with the trace information. The manufacturing device determination unit creates combinations of the manufacturing devices that can perform manufacturing processes in consideration of operation information and trace information, determines a quality index from the inspection information for each of the created combinations, and determines, based on the quality index determined for each of the combinations, a combination of the manufacturing devices to be used. A transfer destination indication unit indicates a transfer destination of a part to a transfer device based on the determined combination of the manufacturing devices.

A system and method for reducing the magnitude of one or more harmonica of one or more uniformity parameters in a cured tire involves selective removal of tire material at one or more track/area locations along first and second bead profiles. Selective removal may occur via ablation at the bead seat, low flange and/or high flange zones to correct for a selected number of harmonic of such parameters as radial, lateral and tangential force variation. Ablation pattern are calculated and implemented on first and second tire beads to achieve desired levels of force reduction at selected angular locations (within the expanse from 0-360 degrees along each tire bead). Ablation patterns may be calculated for implementation at fixed or varied tire rotational speeds and/or fixed or varied levels of laser power.

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.

Aspects of the disclosed technology provide a computational model that utilizes machine learning for detecting errors during a manual assembly process and determining a sequence of steps to complete the manual assembly process in order to mitigate the detected errors. In some implementations, the disclosed technology evaluates a target object at a step of an assembly process where an error is detected to a nominal object to obtain a comparison. Based on this comparison, a sequence of steps for completion of the assembly process of the target object is obtained. The assembly instructions for creating the target object are adjusted based on this sequence of steps.

Various systems and methods for maintaining a record for a workpiece processed by a CNC electronically synchronized cell of a manufacturing assembly line are disclosed herein. Example embodiments involve a cell controller and a part-processing control system. The cell controller can be configured to: initialize a cell controller record; initiate a part assembly task involving at least one electronically synchronized part-processing operation and upon completion of each operation, update an inspection identifier of the cell controller. The part-processing control system can be configured to initialize a part-processing control system record; during completion of the part assembly task, query the cell controller for the inspection identifier, and update the part-processing control system record, based on a result of the querying; and upon completion of the part assembly task, compare the cell controller record and the part-processing control system record; and determine a status for the workpiece based on the comparison.

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 molding monitoring apparatus acquires an image of a molding molded by an injection molding machine, determines whether abnormality is present in the molding, and specifies an abnormality occurrence position thereof when the abnormality is present. Further, the molding monitoring apparatus calculates the number of abnormality occurrences for each abnormality occurrence position, and compares, among the calculated number of abnormality occurrences for each abnormality occurrence position, the number of abnormality occurrences for each abnormality occurrence position in a certain term with the number of abnormality occurrences for each abnormality occurrence position in another term.

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.