Name
Abstract | ||
|---|---|---|
The emergence and subsequent popularization of lean has been one of the most significant developments in the history of operations management. However, there is a lack of systematic theory on the control framework underlying lean production. It is therefore difficult to conduct more in-depth research on Lean theory, specifically in the context of emerging technologies as smart manufacturing or Industry 4.0. In this study, process control theory is used to re-define several major lean methods and tools. Then a Lean-Oriented Optimum-State Control Theory (L-OSCT) is proposed that integrates these lean methods and tools into optimum-state control theory. On the level of method and mechanism, we adopt a recently emerged synchronization approach to obtain global-wide leanness of a large-scale system. L-OSCT provides dynamic process control in industrial networking systems. At last, a case study in a large-size paint making company in China is used to validate the effectiveness of the approach. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s12652-018-1012-z | Journal of Ambient Intelligence and Humanized Computing |
Keywords | Field | DocType |
Lean production,Process control,Internet of things,Just in time,Customized production | Smart manufacturing,Synchronization,Computer science,Internet of Things,Manufacturing engineering,Emerging technologies,Lean manufacturing,Process control,Artificial intelligence,Industrial Ethernet,Machine learning | Journal |
Volume | Issue | ISSN |
10.0 | SP3.0 | 1868-5145 |
Citations | PageRank | References |
0 | 0.34 | 19 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kai Zhang | 1 | 114 | 56.69 |
| ting qu | 2 | 125 | 20.43 |
| Dajian Zhou | 3 | 0 | 0.34 |
| Matthias Thürer | 4 | 32 | 10.21 |
| Yang Liu | 5 | 59 | 8.09 |
| D. X. Nie | 6 | 3 | 1.42 |
| Cong-Dong Li | 7 | 8 | 3.20 |
| George Q. Huang | 8 | 876 | 103.99 |