| Title: |
Job Scheduling Management Research of Intelligent Manufacturing Based on the Internet of Things |
| Authors: |
G.R. Li, Y.F. Ge, Y.X. Wang, S.P. Hu |
| Source: |
Chemical Engineering Transactions, Vol 46 (2015) |
| Publisher Information: |
AIDIC Servizi S.r.l., 2015. |
| Publication Year: |
2015 |
| Collection: |
LCC:Chemical engineering
LCC:Computer engineering. Computer hardware |
| Subject Terms: |
Chemical engineering, TP155-156, Computer engineering. Computer hardware, TK7885-7895 |
| More Details: |
In-depth and detailed requirements of intelligent manufacturing are analyzed for the virtual cloud enterprise, and it is explained that the process of the main task of job scheduling about intelligent manufacturing based on Internet of things. It is concluded that the relationship and associations among parameters after the research of the physical model and object model based on Internet of things. Parameters include the process of production and basic information data. Different orders are analyzed and compared for job scheduling condition, then it is concluded that to get the specific process of qualified products. The detailed analysis and disassemble program are carried on back business of work ticket and splitting business, which makes the management more rationalization and improves the efficiency of intelligent manufacturing. Finally the scheduling of query is carried on and other business query functions have been implemented, which is the solar panels of a factory production. The system of job scheduling is more reasonable and more efficient in scheduling management, which saves time and resources for the enterprise. This research could be applied in the job scheduling of cloud virtual enterprise. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2283-9216 |
| Relation: |
https://www.cetjournal.it/index.php/cet/article/view/4308; https://doaj.org/toc/2283-9216 |
| DOI: |
10.3303/CET1546139 |
| Access URL: |
https://doaj.org/article/4e7cf3c13071479fa15ce8deb9e92646 |
| Accession Number: |
edsdoj.4e7cf3c13071479fa15ce8deb9e92646 |
| Database: |
Directory of Open Access Journals |
