Prediction of failures by using crow/AMSAA model in microsoft excel

Muhammad, M.B. and Raza, T. and Majid, M.A.A. (2016) Prediction of failures by using crow/AMSAA model in microsoft excel. In: UNSPECIFIED.

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Abstract

Failures due to poor maintenance practices are perceived as the dominant factor that limits production capacity, product quality and profitability. To overcome these failures, companies are using different techniques like inspection, using key performance indicators (KPIs), analysing the vibration of equipment, eliminating the design errors, operation errors and installation errors, in order to reduce the failure rate and increase production and profit. Most complex machines like automobiles, radars, aircrafts, and main servers are repaired not replaced during failure. This failure could result to high maintenance cost and a financial loss to the company. Therefore, it is necessary to predict and analyze the reliability of repairable equipment in order to reduce the occurrence of failure and increase the availability and reliability of the equipment. The Crow- AMSAA plots are powerful tool for predicting the upcoming failures. In this paper Non Homogenous poisson process (NHPP) or Crow/AMSAA is used to predict the upcoming failures by using Microsoft excel. This could help industry to increase their mean time between failures (MTBF) in order to improve reliability. A case study of centrifugal pumps is taken in this paper to clarify the functioning of Crow- AMSAA (C-A) plots using Microsoft Excel. The results show that next failure of centrifugal pumps is predicted successfully. © IEOM Society International. © IEOM Society International.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 0; Conference of 6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016 ; Conference Date: 8 March 2016 Through 10 March 2016; Conference Code:135628
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:19
Last Modified: 09 Nov 2023 16:19
URI: https://khub.utp.edu.my/scholars/id/eprint/7344

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