.png){kind=icon}
Return
Manufacturing system development framework using a data models driven approach
.png){kind=icon}
PRE
AI
DOI：10.1080/1352816031000075026.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We report on a data models driven approach for the development of a manufacturing system framework. Relational data schemes are used for the creation of data models. A modular approach is adopted for the creation of complex manufacturing system configurations. Each module is created by selecting the appropriate resources from the data models and is represented as a standard module template in the module library for future use. Several modules can be integrated together through an automated guided vehicles system to model a complex manufacturing system. Each module is autonomous in creating and executing its plans, but cooperative with other modules to realize the system's overall goals. For effective control of parts in the system, an event-based simulation strategy is implemented. The developed algorithm can resolve the situations arising due to any deadlock or conflict during a simulation run. System data tables are regularly updated as and when an event occurs in the system. The updated information includes machine status, part location and status, and capacity status, etc. of all parts and resources. A case study comprising eight part types with five different flow patterns in a three-module system is taken to show the effectiveness of the proposed approach.
Keywords:
DEADLOCK-AVOIDANCE
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.3
Papers:
1.1W
Citations:
3.7W
Organization
No organization information available
Cited Papers
No cited papers available