Cloud Computing Based Machining Optimization
| dc.contributor.author | Chandrasekaran, M | |
| dc.date.accessioned | 2015-09-22T05:37:34Z | |
| dc.date.accessioned | 2023-10-26T09:44:10Z | |
| dc.date.available | 2015-09-22T05:37:34Z | |
| dc.date.available | 2023-10-26T09:44:10Z | |
| dc.date.issued | 2014 | |
| dc.description | Supervisor: U. S. Dixit | en_US |
| dc.description.abstract | In the era of information technology the application of computer and web technology help to connect different manufacturers and customers globally on wire. Internet or web based manufacturing and very recently the concept of cloud computing and cloud manufacturing has started gaining popularity. The cloud computing is a concept of providing computing services and data on demand. The word (also phrased as cloud stands for internet but the phrase computing means much more than based computing Several researchers have applied web technologies for various applications such as mechanical design, production scheduling, process planning, etc. The application of web technology in the area of machining optimization and information sharing is the need of hour. In this work the feasibility of using cloud computing for the optimization of machining processes is explored. The optimization of machining process aims to obtain optimum cutting parameters for economic manufacturing of the product. Researchers have used a number of traditional and non-traditional optimization techniques for obtaining optimum parameters in single and multipass machining processes. The results of conventional offline optimization have many limitations and need to be fine tuned in the shop floor depending on the rigidity of machine tool, deviation in the properties of material and a number of random causes. In this thesis, a heuristic based online optimization methodology suitable for a cloud based system has been developed. It optimizes the process during production of jobs. The optimization strategy does not require any a priori machining models viz., tool life and surface roughness prediction models. The methodology is demonstrated for optimization of common machining processes using virtual machines that replace actual machining experiments by simulated results. | en_US |
| dc.identifier.other | ROLL NO. 07610308 | |
| dc.identifier.uri | https://gyan.iitg.ac.in/handle/123456789/459 | |
| dc.language.iso | en | en_US |
| dc.relation.ispartofseries | TH-1234; | |
| dc.subject | MECHANICAL ENGINEERING | en_US |
| dc.title | Cloud Computing Based Machining Optimization | en_US |
| dc.type | Thesis | en_US |