An automated construction robot system includes: a mobile base assembly configured to be displaceable within a work area; a head assembly configured to process a work surface; an arm assembly configured to moveably-couple the head assembly and the mobile base assembly and controllably-displace the head assembly with respect to the work surface; a machine vision system configured to scan a target area and generate target area information; and a computational system configured to: manipulate one or more of the mobile base assembly, the head assembly and the arm assembly to apply a coating material to the work surface via the head assembly, process the target area information to generate one or more edge instructions, and manipulate the angle of incidence of the head assembly with respect to the work surface based, at least in part, upon the one or more edge instructions.

A variable-duty-cycle microcontroller is configured for use within an automated construction robot system and includes: an inlet port configured to receive coating material from a coating supply system; an outlet port configured to provide a regulated quantity of coating material to a head assembly; and a coating material regulation system configured to control the passage of the coating material from the inlet port to the outlet port, wherein the coating material regulation system is configured to process a variable-duty-cycle control signal and regulate the quantity of coating material applied to a work surface via the head assembly.

A system includes a manual tool data system having a manual tool data monitoring system configured to monitor one or more manual tools, a manual tool data acquisition system configured to acquire data corresponding to one or more operational parameters of the one or more manual tools, a manual tool data analysis system configured to analyze the data acquired by the manual tool data acquisition system, and a manual tool messaging system configured to generate messages based on the data analyzed by the manual tool data analysis system.

A method for the surface treatment of an article (2) by means of a robotic device (3) comprising a robotic arm (5) and a spraying head (4) fitted on the robotic arm (5); the method comprises a learning step, during which the operator moves the spraying head (4) by means of a handling device (9) and the movements made by the spraying head (4) are stored by a storage unit (8); and a reproduction step, which is subsequent to the learning step and during which the robotic arm (5) is operated so that the spraying head (4) repeats the movements stored by the storage unit (8).

A method and associated paint finishing system are disclosed for performing predictive maintenance on equipment used for delivering liquid paint in a paint finishing facility. The method comprises: identifying a set of components of the equipment and associated maintenance requirements; for each of the components, providing a set of operating parameters (401-404) that affect useful service life of the component; for each component, providing an algorithm (410) relating the operating parameters to a remaining time by when a maintenance operation on the component is to be performed; monitoring each of the operating parameters (401-404) during operation of the paint finishing facility; for each component, applying the algorithm (410) with the monitored operating parameters (401-404) to calculate the remaining time for the component (420); and for each component providing to a maintenance operative an alert indication relating to the remaining time for the component.

A system includes a production process information system configured to be installed within a service shop, an air supply flow meter configured to detect air flow to a first manual sprayer and send the detected air flow to the production process information system, and a coating material flow meter configured to detect fluid flow to the first manual sprayer and send the detected fluid flow to the production process information system. The production process information system is configured to determine sprayer usage parameters based on the air flow and the fluid flow.

A robot system includes at least one robot, a first sensor, at least one second sensor, and circuitry. The at least one robot is to work on a workpiece. The first sensor is to detect a three-dimensional shape of the workpiece. The at least one second sensor is to detect a three-dimensional position of the workpiece. The circuitry is configured to control the at least one robot based on teaching data. The circuitry is configured to correct the teaching data according to the three-dimensional shape detected by the first sensor. The circuitry is configured to correct the teaching data according to the three-dimensional position detected by the at least one second sensor.

An apparatus for orienting a partially coated spherical-object includes a pedestal, a camera, and a controller. The spherical object contains a coating over a portion of a surface. The coating defines a spherical-cap, and the spherical cap defines a polar-axis. The polar-axis is oriented normal to a plane defining a base of the spherical cap, wherein an intersection of the plane and the surface defines a boundary line. The pedestal retains the spherical object and selectively rotates the spherical object about a longitudinal axis of the pedestal. The camera captures an image of the spherical object on the pedestal. The controller is in communication with the pedestal and the camera. The controller is operable to control the rotation of the pedestal, detect the boundary line in the image, and determine when the pedestal has positioned the spherical object to cause the boundary line to have a zero curvature.

An example system includes at least one acoustic sensor and one optical sensor to monitor a thermal spray system controlled by a plurality of control parameters and performing a process associated with a plurality of process outputs. The system includes a computing device including a machine learning module and a control module. The machine learning module is configured to determine, based on at least the plurality of control parameters, an at least one time-dependent acoustic data signal, an at least one image data signal, and the plurality of process outputs, a relationship between the plurality of control parameters and the plurality of process outputs by machine learning. The control module is configured to control the thermal spray system to adjust the plurality of process outputs toward a plurality of respective operating ranges.

In order to provide a checking facility for checking workpieces and also a treatment facility for treating workpieces, which enable efficient and reliable quality optimisation, it is proposed that workpiece parameters are detected, for example by means of an automatic checking station, and a workpiece-specific data set is created on this basis and/or from facility parameters.