Abstract
Improving paint quality is of significant importance for vehicle manufacturing. In this paper, a quality propagation model is presented to analyze and improve quality in automotive paint shops. Specifically, we study the vehicle painting process with multiple inspection stations. After each inspection, vehicles failed to achieve quality requirement will be repaired before moving to the next operation. In such systems, the quality variations may propagate along the painting process. To study it, a three-state quality propagation model has been developed, and analytical formulas to evaluate product quality have been derived. In addition, to improve quality performance, a bottleneck analysis method has been introduced to identify the most critical stage that impedes product quality in the strongest manner so that its improvement will lead to the largest improvement of the whole system. To illustrate the applicability of the method, a case study to improve paint quality at an automotive paint shop is introduced. © IFAC.
| Original language | English |
|---|---|
| Title of host publication | 7th IFAC Conference on Manufacturing Modelling, Management, and Control, MIM 2013 - Proceedings |
| Publisher | IFAC Secretariat |
| Pages | 1890-1895 |
| Volume | 46 |
| ISBN (Print) | 9783902823359 |
| DOIs | |
| Publication status | Published - 2013 |
| Externally published | Yes |
| Event | 7th IFAC Conference on Manufacturing Modelling, Management, and Control, MIM 2013 - Saint Petersburg, Russian Federation Duration: 19 Jun 2013 → 21 Jun 2013 |
Publication series
| Name | IFAC Proceedings Volumes (IFAC-PapersOnline) |
|---|---|
| Volume | 46 |
| ISSN (Print) | 1474-6670 |
Conference
| Conference | 7th IFAC Conference on Manufacturing Modelling, Management, and Control, MIM 2013 |
|---|---|
| Place | Russian Federation |
| City | Saint Petersburg |
| Period | 19/06/13 → 21/06/13 |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Funding
This work is supported in part by NSF Grant No. CMMI-1063656.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Research Keywords
- Bottleneck
- Flow model
- Paint shop
- Quality
- Repair
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