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.

A stemming system includes a computing device and a stemming device. The computing device includes data processing hardware and memory hardware in communication with the data processing hardware. The data processing hardware includes a transmitter and a receiver. The stemming device is communicatively-coupled to the computing device. The stemming device includes a base portion and a valve-engaging portion. The valve-engaging portion includes a transducer that obtains a measurement communicated to the receiver of the computing device. The measurement includes at least one physical parameter associated with installing a tire-wheel assembly valve to a wheel throughout a process of disposing the valve within a valve hole of the wheel. The processor analyzes a data signature associated with the measurement for determining if the valve has been adequately or inadequately installed by the stemming device.

The invention relates to a system for controlling manual operations during production of an assembly of parts, the system comprising a portable hand tool allowing an assembly technician to perform manual operations on a plurality of elements of said assembly of parts, and locating means integrated at least in part into an electronic module attached to said portable hand tool and able to determine a location of at least one manual operation associated with an element by locating the position of said portable hand tool in a three-dimensional coordinate system associated with a set of modelling data representing a three-dimensional modelled image of said assembly of parts. According to the invention, said locating means comprise a depth camera belonging to said electronic module and a processing module able to estimate the position of said portable hand tool on the basis of images captured by said depth camera.

A wire harness production supporting device configured to produce a wire harness by in turn laying out a plurality of electric wires on a wire laying out drawing. This wire harness production supporting device is composed of a time recording section configured to, each time one of the plurality of electric wires is laid out, store a time at which the one of the plurality of electric wires has been laid out, in a storing section, and a progress status administrating section configured to obtain a progress status of the production of the wire harness based on the time at which the one of the plurality of electric wires has been laid out having been stored in the storing section.

In an operation management system in the related art, it is necessary to add an identification mark such as an RFID tag to each component to be managed and prepare a fastening tool having an antenna. In contrast, a mechanical fastening unit management method is provided using an augmented reality space generated by superimposing a virtual space on a real space. In the augmented reality space where a real fastening unit (RBn) and a virtual fastening unit (IBn) are in a one-to-one correspondence, information that the real fastening unit is selected as a fastening target is acquired with a camera or the like, and analyzed by an augmented reality server connected to the camera. Accordingly, it is possible to easily record that a predetermined operation is progressing as scheduled, and to provide a high quality mechanical fastening unit management method or system that is low in operation cost.

Aspects of the disclosed technology provide an Artificial Intelligence Process Control (AIPC) for automatically detecting errors in a manufacturing workflow of an assembly line process, and performing error mitigation through the update of instructions or guidance given to assembly operators at various stations. In some implementations, the disclosed technology utilizes one or more machine-learning models to perform error detection and/or propagate instructions/assembly modifications necessary to rectify detected errors or to improve the product of manufacture.

A monitoring system comprises a manufacture system with capability to manufacture a plurality of biopharmaceutical products, at least one image capture device arranged to capture a scene comprising the manufacture system, and a processing element connected to said at least one image capture device and arranged to process images captured by said at least one image capture device to track operator interactions and/or a result of operator interactions within the scene. The processing element is further is arranged to compare a predefined workflow process scheme relating to the selected biopharmaceutical product to at least a part of the tracked operator interactions with the manufacture system and/or to at least a part of the result of the tracked operator interactions with the manufacture system, and determine whether at least one pre-set criterion set by the workflow process scheme is fulfilled based on the comparison.

Provided is a system for improving the efficiency of a work for attaching a heat insulating member to the surface of a device requiring heat insulation. The member attachment support system supports the work of attaching a plurality of members to the device. The member attachment support system comprises: an identification information storage unit which is provided for each of the plurality of members, and stores identification information associated with the attachment position of the member; a terminal device which acquires identification information from the identification information storage unit; and a display device which displays a support image that indicates the attachment position, on the device, corresponding to the identification information acquired by the terminal device.

A system for use in facilitating a manufacturing operation that includes a wireless beacon paired with each vehicle of multiple vehicles routable along a production line in a sequence. The wireless beacon emits a signal containing information that identifies the paired vehicle. A wireless transceiver is at a predetermined location along the production line, and the wireless transceiver scans for the signal. A server device is in communication with the wireless transceiver. The server device stores pairing data of which wireless beacon is paired with each vehicle, and sequence data of the vehicles routed along the production line, and receives, from the wireless transceiver, a signal containing the information that identifies the paired vehicle. The server device also verifies, based on the pairing data, the sequence data, and the information in the signal, that an order in which the vehicles enter the predetermined location corresponds to the sequence.

A workbench system comprising: a workbench; a sensor system comprising one or more sensors, the sensor system configured to identify a user in a workspace in which the workbench is located; a controller operatively coupled to the sensor system and configured to: based on the identity of the user, determine a task to be performed by the user using the workbench system; and based on the identity of the user and the determined task, control one or more properties of the workbench.