What is it about?

Purpose – The aim of this paper is to follow an analytic-deductive approach to realize the issues related to the present power crisis and growing demand of backup power systems (BPSs), especially in India. It not only explores the need of high-cost BPSs in the current scenario but also puts an emphasis to reduce the running cost through parametric optimizations. Design/methodology/approach – Literature review identifies dependency of every sector on BPS and also highlights present and future challenges erupting in this age of power scarcity. Different improvement initiatives being used to improve efficiency of BPS have been studied, but quite rare application of Six Sigma in BPS sector, in actual was found. A define-measure-analyze-improve-control (DMAIC) model of Six Sigma is being suggested and practiced for bringing a breakthrough in efficiency or mileage of a diesel genset (used as a BPS).

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Why is it important?

Research limitations/implications – The whole work more or less revolves around the Indian energy scenario and seems to be talking about the power generation process and its optimization, in context of only diesel genets as BPS. Originality/value – The paper outlines the need for energy reform in industry. The DMAIC approach of Six Sigma in the BPS sector is too infrequent and next, motivates to reduce BPS cost and its associated expenditures, which are generally ignored.


Findings – Importance of BPS cannot be ignored, particularly in developing countries, but feeble effort was seen to improve its power generation cost. An imprecise and outdated framework used for bringing a change in the BPS sector is unable to increase its overall equipment efficiency. The diversified methodology of Six Sigma has been successfully implemented through a case study discussed and further validates the approach adopted to tackle the problem formulated further in the paper.

Dr Bikram Jit Singh
MMDU Mullana

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This page is a summary of: Optimizing backup power systems through Six Sigma, International Journal of Lean Six Sigma, May 2014, Emerald, DOI: 10.1108/ijlss-09-2012-0008.
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