Digital Twin Simulation of the Automotive Body in White Dispensed Bead Quality Validation and Inspection Process
Abstract Standard joining techniques such as adhesive, sealer, and mastic dispensing play a vital role in automotive Body in White manufacturing processes. Traditionally, validation involves verifying dispensed bead placement and presence, relying on human inspectors who utilize camera and closed circuit TV (CCTV) systems for quality confirmation. Equipment validation involves assessing camera quantity and placement, typically determined post-installation through the “camera field of view” placement method. Unfortunately, this approach has led to purchasing excessive or sometimes unnecessary equipment, contributing to elevated launch costs. This publication introduces a Digital Twin approach for predicting the quantity and field of view of passive vision cameras used in dispensed bead applications. The method employs simulation to validate the process before actual integration. Additionally, the placement of beads undergoes validation through Virtual Reality simulation, enhancing training for quality inspectors and thereby increasing the number of inspections achievable per shift. The use of Digital Twin and Virtual Reality modeling also results in improved development time for quality inspection documentation, a task typically handled by Quality Engineers. The proposed procedure has demonstrated noticeable reductions in costs, inspection documentation development time, and an enhancement in quality validation procedures. Ongoing research aims to explore the impact of increased inspection frequency within manufacturing facilities, with a specific focus on the implications for reprocessing time.
Authors
- Ali Ahmad Malik (ORCID: https://orcid.org/0000-0001-7191-3614)
- Liz Lekarczyk
Institutions
- Oakland University (US)
- Michigan United (US)
Publication Details
- Published
- 2024-08-25
- DOI
- https://doi.org/10.1115/detc2024-144508
- Citations
- 1
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.35