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Makarand S. Kulkarni

Researcher at Indian Institute of Technology Bombay

Publications -  84
Citations -  1338

Makarand S. Kulkarni is an academic researcher from Indian Institute of Technology Bombay. The author has contributed to research in topics: Reliability (statistics) & Computer science. The author has an hindex of 20, co-authored 75 publications receiving 1043 citations. Previous affiliations of Makarand S. Kulkarni include Indian Institutes of Technology & National Institute of Industrial Engineering.

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A methodology for joint optimization for maintenance planning, process quality and production scheduling

TL;DR: A model has been developed for integrating maintenance scheduling and process quality control policy decisions and it provided an optimal preventive maintenance interval and control chart parameters that minimize expected cost per unit time.
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Combined Taguchi and dual response method for optimization of a centerless grinding operation

TL;DR: In this article, a successful application of combined Taguchi and dual response methodology to determine robust condition for minimization of out of roundness error of workpieces for centerless grinding operation is presented.
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Weibull accelerated failure time regression model for remaining useful life prediction of bearing working under multiple operating conditions

TL;DR: In this paper, a Weibull Accelerated Failure Time Regression (WAFTR) model is presented that considers both operating condition parameters and condition monitoring signal during model parameter estimation.
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Joint consideration of production scheduling, maintenance and quality policies: a review and conceptual framework

TL;DR: A review of literature addressing the joint consideration of quality, maintenance and scheduling is presented and research gaps are highlighted and a conceptual methodology is presented that can lead to further developments in this field.
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Bearing diagnosis based on Mahalanobis–Taguchi–Gram–Schmidt method

TL;DR: In this paper, a methodology is developed for defect type identification in rolling element bearings using the integrated Mahalanobis-Taguchi-Gram-Schmidt (MTGS) method.