Session: 03-09-01: Data-Driven Innovation in Smart Product Design and Manufacturing

Paper Number: 166700

Digital Twin Inputs and Feedback Loop for Automotive Body in White Dispensing Quality Inspector Training 

Automotive Body in White dispensing, or ‘gluing’, quality validations are critical for safety, crash and customer satisfaction requirements. Within this process, a robot end-effector applies an adhesive bead, in accordance with the introduced parameters. The dispensing nozzle diameter, distance to the part and consistent sheet conformity are critical parameters that can subsequently vary during the manufacturing process; noting the importance of a qualification inspection process to ensure consistency. The robotically applied beads are traditionally validated with manual inspector support at specified frequencies; with each team member completing initial training through ‘On the Job’ (OJT) reviews. This process is extensive and can introduce human-error within the inspection process, with traditional OJT requiring a minimum of 120 hours of bead application processes, quality requirements for the assigned area, inspection frequency and discrepancy identification procedures. Prior research has shown OJT can be decreased for a variety of quality and part installation processes by introducing a Digital Twin of the manufacturing environment with training methods. This publication will introduce a baseline analysis of the Digital Twin simulation inputs required for accurate dispensed bead inspection training specifications for industry standard development. Previous publications have emphasized the importance of Digital Twin feedback parameters and selection is critical for accurate data review. Furthermore, while researchers have identified the necessary feedback criteria for welding processes, minimal research has been conducted for dispensing applications; posing an industry limitation. Quality inputs have been identified to include bead placement, proximity to part edge and location, evaluation criteria including length and width. Simulation inputs include a JACK / JILL model, which will replicate the inspection process, along with detailed instructions for the dispensed bead evaluation process; including individual task instructions with CAD components, detailed location information and exact quality criteria to be reviewed with comparison photographic evidence for training criteria development. Additional validation requirements and evaluation criteria will also be presented; providing a benchmark that can be utilized for multiple OJT methods for quality inspection, part installation and operator support. The developed criteria can be implemented within other manufacturing processes in which manual operations or training may be required. While prior research has presented simulation models for training and operator integration, a comprehensive list for specification and industry standard development has not been developed. Future research will provide case studies of industrial applications and ‘human learning cure’ feedback loop calculations, which will be utilized to provide and develop industry benchmarks for standard development.

Presenting Author: Liz Lekarczyk Oakland University

Presenting Author Biography: Liz Lekarczyk is a current PhD student at Oakland University in Rochester, Michigan. Her primary research interests include Digital Twins within manufacturing environments; specifically for operator training and equipment reviews. Liz has worked in the automotive industry for seven years in various Body in White and General Assembly roles within launch support, equipment integration and operator training. These experiences greatly increased her passion for Digital Twins and integration into automotive and general manufacturing applications. Liz previously obtained her Mechanical Engineering Bachelor and Master degree from Oakland University, where she is currently studying under the advisement and support of Dr. Ali Ahmad Malik.

Authors:

Liz Lekarczyk Oakland University
Ali Ahmad Malik Oakland University