Journal of Failure Analysis and Prevention

, Volume 14, Issue 6, pp 772–783 | Cite as

Optimizing Process Parameters of Screw Conveyor (Sugar Mill Boiler) Through Failure Mode and Effect Analysis (FMEA) and Taguchi Method

  • A. Mariajayaprakash
  • T. Senthilvelan
Technical Article---Peer-Reviewed


This paper exhibits the failures of the boiler during the cogeneration process and provides solution to overcome the failures. The failures are frequently occurring in the screw conveyor of fuel-feeding system of the boiler and rarely occurring in the grate of the boiler. In this research work, three important statistical tools are employed to identify and further rectify the failures of the screw conveyor. The different techniques, viz., cause-and-effect diagram, failure mode and effect analysis (FMEA), and the Taguchi method have been applied. The cause-and-effect diagram, is the primary tool used to sort out all the possible root causes of the failures. The process parameters that cause the failures in the screw conveyor are identified by FMEA. Since the conventional FMEA has some limitations, fuzzy FMEA is employed. The most critical parameters selected by conventional FMEA and fuzzy FMEA are fuel type, fuel moisture, drum speed, and air flow. Finally, the selected process parameters are optimized by the Taguchi method to prevent the failures occurring in the screw conveyor. Among the various process parameters, the parameter, fuel type, significantly affects the performance of the screw conveyor.


Industrial boiler Ishikawa diagram FMEA Fuzzy FMEA Taguchi method 

List of Symbols


Number of tests in a trial


Response value of observation in the ith test


Design of experiments


Degrees of freedom


Degrees of freedom for factor A


Number of levels for factor A


Total degrees of freedom required


Total degrees of freedom of the available orthogonal array


Number of trials


Analysis of variance


Overall mean percentage defects


Variance of factor


Sum of square


Expected amount of variation


Percent contribution




Level of risk


Degrees of freedom for the error


Error variance

F(α, 1, νe)

F ratio required at the level of risk


Effective number of replications


Total number of experiments


Confidence interval


Average values of defects at different levels


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Copyright information

© ASM International 2014

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringRajiv Gandhi College of Engineering and TechnologyKirumampakkamIndia
  2. 2.Department of Mechanical EngineeringPondicherry Engineering CollegePillaichavadyIndia

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