Application of Failure Mode Effect Analysis for Improved Scheduling in Maintenance of Machines
Umesh Gupta1, Ankit Bansal2, Sandeep Singh3
1Dr. Umesh Gupta *, Associate Professor, Vaish College of Engineering, Rohtak, India.
2Dr. Ankit Bansal, Associate Professor, Vaish College of Engineering, Rohtak, India.
3Sandeep Singh, Assistant Professor, Vaish College of Engineering, Rohtak, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 30, 2020. | Manuscript published on April 10, 2020. | PP: 895-899 | Volume-9 Issue-6, April 2020. | Retrieval Number: E3025039520/2020©BEIESP | DOI: 10.35940/ijitee.E3025.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Maintenance of machines is crucial measures in order to have stable and improved work flow. Any kind of failure might result in complete failure of the machine. Hence it becomes essential to identify the vulnerable failures that might occur in the components of any machine. The present work is carried out in order to improve the scheduling in maintenance of a lathe machine. Different components of the machine are studied in this research. “Failure mean effective analysis (FMEA)” method is applied to identify the failures associated with the components of the machine. Risk priority number is calculated based on which the components are provided with ranks. The rank signifies the flow of maintenance for all the components. The results reveal that the flexure bearing needs the least maintenance as it has the highest rank.
Keywords: FMEA, Machines, Maintenance, Scheduling, Failures.
Scope of the Article: Artificial Intelligence and Machine Learning