Reliability Analysis of Power Tiller-Reference-Cited by-同舟云学术

Reliability Analysis of Power Tiller

Published:2023 Issue:3 Volume:7 Page:299-303
ISSN:2581-4621
Container-title:international journal of engineering technology and management sciences
language:
Short-container-title:IJETMS

Author:

Gowtham M ^ORCID,Arunagirinathan M ^ORCID,Jeeva T ^ORCID,Kesavan G ^ORCID,Mrs.Hemalatha J ^ORCID

Abstract

Reliability analysis of a power tiller involves studying the probability of its performance and functionality over a given period. This analysis aims to identify the factors that affect the reliability of the power tiller and to determine ways to improve its performance. The reliability of a power tiller can be evaluated using different methods such as statistical analysis, probability theory, and simulation modelling. These methods enable the assessment of the power tiller's performance in different operating conditions and help to identify the critical components that contribute to its overall reliability. Some of the factors that affect the reliability of a power tiller include its design, manufacturing process, maintenance, and the environment in which it operates. The reliability analysis of a power tiller also involves identifying the failure modes and effects of different components and determining the probability of these failures occurring.

Publisher

Mallikarjuna Infosys

Subject

General Medicine

Reference21 articles.

1. [1] D. Ganapathy, “Preserving India’s palm Leaf Manuscripts for the Future,” WAGLOBAL, Kerala, India, 2016.

2. [2] N. S. Panyam, V. L. T.R., R. Krishnan, and K. R. N.V., “Modeling of palm leaf character recognition system using transform based techniques,” Pattern Recognition Letters, vol. 84, pp. 29–34, 2016.

3. [3] K. P. Geena and G. Raju, “View-based feature extraction and classification approach to Malayalam palm leaf document image,” International Journal of Innovative Research in Computer and Communication Engineering, vol. 2, no. 5, pp. 264–267, 2014.

4. [4] R. Chamchong and C. C. Fung, “A framework for the selection of binarization techniques on palm leaf manuscripts using support vector machine,” Advances in Decision Sciences, vol. 2015, Article ID 925935, 7 pages, 2015.

5. [5] N. P. Challa and R. V. K. Mehta, “Applications of image processing techniques on palm leaf manuscripts-A survey,” in Proceedings of the Conference on Cognitive Science and Artificial Intelligence, CA, USA, February 2017.