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Efficiency monitoring as a strategy for cost effective maintenance of induction motors for minimizing carbon emission and energy consumption

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  • Singh, Gurmeet
  • Anil Kumar, T.Ch.
  • Naikan, V.N.A.

Abstract

Induction motors are the major source of energy consumption in industries. Research work available on motor efficiency and energy consumption advocates the use of energy efficient motors to reduce the power consumption. However, these motors are also prone to faults which affects their operational efficiency. Over a period of time, the propagation of fault in the motor leads to the further drop in the efficiency which increases motor running loss. This loss is generally ignored by most of the researchers and managers and is a hidden cost borne by the industries. In this paper running of faulty induction motors and its associated financial losses have been addressed. It has been assumed that for a motor running at constant load, fault propagation leads to further drop in its efficiency. Three simulated scenarios: linear, exponential and quadratic drop in efficiency have been considered for estimation of running loss. An algorithm has also been proposed for planning maintenance actions based on operational losses due to faulty motor. This paper also highlights how efficiency and condition monitoring helps in reducing CO2 emission.

Suggested Citation

  • Singh, Gurmeet & Anil Kumar, T.Ch. & Naikan, V.N.A., 2019. "Efficiency monitoring as a strategy for cost effective maintenance of induction motors for minimizing carbon emission and energy consumption," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 193-201.
  • Handle: RePEc:eee:reensy:v:184:y:2019:i:c:p:193-201
    DOI: 10.1016/j.ress.2018.02.015
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    Cited by:

    1. Qiu, Xiwei & Sun, Peng & Dai, Yuanshun, 2021. "Optimal task replication considering reliability, performance, and energy consumption for parallel computing in cloud systems," Reliability Engineering and System Safety, Elsevier, vol. 215(C).

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