Author:
Gugaliya Agam,Naikan V.N.A.
Abstract
Purpose
When induction motors are considered, there is no specific cost model for net savings per year due to condition-based maintenance (CBM) covering various parameters such as downtime, energy, quality, etc. The purpose of this paper is to develop a cost model for the financial viability of the implementation of CBM for induction motors.
Design/methodology/approach
A literature review has been carried out to identify the existing failure modes of motor, available condition monitoring techniques, the usefulness of CBM and different maintenance models available. Then, a cost model considering all parameters has been proposed.
Findings
A cost model has been proposed for the maintenance of induction motors. Method for the economic evaluation of the model has also been suggested in the paper. The application of the model has been illustrated through a case study of a steel plant, which suggests that investment in the condition monitoring of induction motors increases the net profit of the organization.
Research limitations/implications
The proposed model is specifically designed for induction motors. All the motors under consideration are assumed to be of the same specifications, and fault in any motor is supposed to have the same effect on quality, cost, criticality, etc., of the operation and end product.
Practical implications
This paper will help the maintenance manager in decision making when maintenance action has to be carried out for a given motor under CBM for the better utilization of the equipment and resources. This paper also shows how to compute ROI on CBM investment.
Originality/value
The paper provides a cost model for the economic evaluation of implementing CBM for induction motors which will be useful to researchers and maintenance managers in effective decision making and maintenance planning. The methodology and the cost models are the original contribution of the authors.
Subject
Industrial and Manufacturing Engineering,Strategy and Management,Safety, Risk, Reliability and Quality
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