Abstract
The proper positioning of machine tools in flexible manufacturing system is one of the factors that lead to increase in production efficiency. Choosing the optimum position of machine tools curtails the total part handling cost between machine tools within the flexible manufacturing system. In this article, a two-stage approach is presented to investigate the best locations of the machine tools in flexible manufacturing system. The location of each machine tool is selected from the available specific and fixed locations in such a way that it will result in best throughput of the flexible manufacturing system. In the first stage of the two-stage approach, the throughput of randomly selected locations of the machine tool in flexible manufacturing system is computed by proposing a production simulation system. The production simulation system utilizes genetic algorithms to find the locations of the machine tools in flexible manufacturing system that achieve the maximum throughput of the flexible manufacturing system. In the second stage, the generated locations are fed into artificial neural network to find a relation between a machine tools location and the throughput that can be used to predict the throughput for any other set of locations. Artificial neural network will result in mitigating the computational time.
| Original language | English |
|---|---|
| Pages (from-to) | 1-9 |
| Number of pages | 9 |
| Journal | Advances in Mechanical Engineering |
| Volume | 7 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Jun 5 2015 |
| Externally published | Yes |
Keywords
- Flexible manufacturing system
- artificial neural network
- genetic algorithm
- layout design
ASJC Scopus subject areas
- Mechanical Engineering