Abstract
A battery manufacturing system typically includes a serial production line with multiple inspection stations and repair processes. In such systems, productivity and quality are tightly coupled. Variations in battery quality may add up along the line so that the upstream quality may impact the downstream operations. The repair process after each inspection can also affect downstream quality behavior and may further impose an effect on the throughput of conforming batteries. In this article, an analytical model of such an integrated productivity and quality system is introduced. Analytical methods based on an overlapping decomposition approach are developed to estimate the production rate of conforming batteries. The convergence of the method is analytically proved and the accuracy of the estimation is numerically justified. In addition, bottleneck identification methods based on the probabilities of blockage, starvation, and quality statistics are investigated. Indicators are proposed to identify the downtime and quality bottlenecks that remove the need to calculate throughput and quality performance and their sensitivities. These methods provide a quantitative tool for modeling, analysis, and improvement of productivity and quality in battery manufacturing systems and can be applied to other manufacturing systems ameanable to investigation using integrated productivity and quality models. © 2015 Copyright © "IIE".
| Original language | English |
|---|---|
| Pages (from-to) | 1313-1328 |
| Journal | IIE Transactions (Institute of Industrial Engineers) |
| Volume | 47 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 2 Dec 2015 |
| Externally published | Yes |
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. It is also supported in part by the State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, China, and the grant 51175215 from National Science Foundation of China.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 9 Industry, Innovation, and Infrastructure
Research Keywords
- battery manufacturing
- bottleneck
- integration
- productivity
- Quality
- repair
- serial line
Fingerprint
Dive into the research topics of 'Modeling, analysis, and improvement of integrated productivity and quality system in battery manufacturing'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver