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Abell, Jeffrey A.

Publications and source records attributed to Abell, Jeffrey A..

Quality status display for a vibration welding process

A method includes receiving, during a vibration welding process, a set of sensory signals from a collection of sensors positioned with respect to a work piece during formation of a weld on or within the work piece. The method also includes receiving control signals from a welding controller during the process, with the control signals causing the welding horn to vibrate at a calibrated frequency, and processing the received sensory and control signals using a host machine. Additionally, the method includes displaying a predicted weld quality status on a surface of the work piece using a status projector. The method may include identifying and display a quality status of a suspect weld. The laser projector may project a laser beam directly onto or immediately adjacent to the suspect welds, e.g., as a red, green, blue laser or a gas laser having a switched color filter.

36 MATERIALS SCIENCE↗

Reconfigurable assembly work station

A reconfigurable autonomous workstation includes a multi-faced superstructure including a horizontally-arranged frame section supported on a plurality of posts. The posts form a plurality of vertical faces arranged between adjacent pairs of the posts, the faces including first and second faces and a power distribution and position reference face. A controllable robotic arm suspends from the rectangular frame section, and a work table fixedly couples to the power distribution and position reference face. A plurality of conveyor tables are fixedly coupled to the work table including a first conveyor table through the first face and a second conveyor table through the second face. A vision system monitors the work table and each of the conveyor tables. A programmable controller monitors signal inputs from the vision system to identify and determine orientation of the component on the first conveyor table and control the robotic arm to execute an assembly task.

42 ENGINEERING↗

Quality status display for a vibration welding process

A system includes a host machine and a status projector. The host machine is in electrical communication with a collection of sensors and with a welding controller that generates control signals for controlling the welding horn. The host machine is configured to execute a method to thereby process the sensory and control signals, as well as predict a quality status of a weld that is formed using the welding horn, including identifying any suspect welds. The host machine then activates the status projector to illuminate the suspect welds. This may occur directly on the welds using a laser projector, or on a surface of the work piece in proximity to the welds. The system and method may be used in the ultrasonic welding of battery tabs of a multi-cell battery pack in a particular embodiment. The welding horn and welding controller may also be part of the system.

42 ENGINEERING↗

System and method for controlling a vision guided robot assembly

A method includes the following steps: actuating a robotic arm to perform an action at a start position; moving the robotic arm from the start position toward a first position; determining from a vision process method if a first part from the first position will be ready to be subjected to a first action by the robotic arm once the robotic arm reaches the first position; commencing the execution of the visual processing method for determining the position deviation of the second part from the second position and the readiness of the second part to be subjected to a second action by the robotic arm once the robotic arm reaches the second position; and performing a first action on the first part using the robotic arm with the position deviation of the first part from the first position predetermined by the vision process method.

42 ENGINEERING↗

Binary classification of items of interest in a repeatable process

A system includes host and learning machines in electrical communication with sensors positioned with respect to an item of interest, e.g., a weld, and memory. The host executes instructions from memory to predict a binary quality status of the item. The learning machine receives signals from the sensor(s), identifies candidate features, and extracts features from the candidates that are more predictive of the binary quality status relative to other candidate features. The learning machine maps the extracted features to a dimensional space that includes most of the items from a passing binary class and excludes all or most of the items from a failing binary class. The host also compares the received signals for a subsequent item of interest to the dimensional space to thereby predict, in real time, the binary quality status of the subsequent item of interest.

97 MATHEMATICS AND COMPUTING↗