The valuable resources are rotating technology. In industrial applications, several machines are essential to the effective operation of any system. This article describes the engineering process for developing designs for analyzing variation and the optimization of condition monitoring by the impacts of vibration parameters using Taguchi processes to improve the quality of manufactured items. Crucial spinning equipment is included in the experiment to maximize the vibration frequency reactivity. Using Minitab 16 software, a Taguchi orthogonal array with three vibration parameter levels is built. The Taguchi approach minimizes quality characteristic changes caused by uncontrolled parameters by emphasizing the significance of examining response variation using the signal-to-noise (S/N) ratio. “The larger-the-better” was the principle that guided when it came to vibration frequency as a qualitative attribute. In order to investigate the performance characteristics, the impact of process factors on the condition monitoring process is examined using an examination of variance (ANOVA). Because it minimizes the number of tests and identifies the important parameter, it is also anticipated that the Taguchi technique will be an effective means to optimize different vibration parameters.

Keywords:Taguchi method, orthogonal array, vibration parameters, rotating machinery, ANOVA, Signal to noise ratio

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1. Michelini R, Crenna F, Rossi GB. Diagnostics for monitoring maintenance and quality manufacturing. Int Ser Eng Technol Appl Sci. 2001;1(1):1–74.
2. Benbouzid MEH. A review of induction motors signature analysis as a medium for faults detection. IEEE Trans Ind Electron. 2000;47(5):984–93.
3. Al-Khazali HAH, Askari MR. The experimental analysis of vibration monitoring in system rotor dynamic with validate results using simulation data. ISRN Mech Eng. 2012;2012:1–17.
4. Green I, Casey C. Crack detection in a rotor dynamic system by vibration monitoring—Part I: Analysis. J Eng Gas Turbines Power. 2005;127(2):425.
5. Ghafari SH. Condition monitoring of industrial fans. Proc 22nd Semin Mach Vib CMVA. 2004;1–6.
6. Lees AW, Sinha JK, Friswell MI. Multi-plane balancing of a rotating machine using run-down data. Proc 21st IMAC. 2003;(230):1–6.
7. Muszynska A. Vibrational diagnostics of rotating machinery malfunctions. Int J Rotating Mach. 1995;1(3–4):237–266.
8. Robichaud J, Eng P. Reference standards for vibration monitoring and analysis. Bretech Eng Ltd. 2009;1–10.
9. Phadke MS. Quality engineering using robust design. Englewood Cliffs, NJ: PTR Prentice Hall; 1989. 1–342.
10. Alagic I. Design of experiment and Taguchi method application in analysis of gear oil pump flow capacity. Proc 6th Workshop Eur Sci Ind Collab Adv Technol Manuf WESIC’08; 2008 Sep 25-26; Bucharest, Romania.
11. Rao RS, Padmanabhan G. Application of Taguchi methods and ANOVA in optimization of process parameters for metal removal rate in electrochemical machining of Al/5%SiC composites. Int J Eng Res Appl. 2012;2(3):192–197.
12. Bharti A, Moulick SK. Parametric optimization of multi-response factors in micro-drilling operation. Int J Sci Eng Res. 2013;4(7).
13. Gopalsamy B, Mondal B, Ghosh S. Taguchi method and ANOVA: An approach for process parameters optimization of hard machining while hardened steel. J Sci Ind Res. 2009;68(7):686–695.
14. Krishankant, Taneja J, Bector M, Kumar R. Application of Taguchi method for optimizing turning process by the effects of machining parameters. Int J Eng Adv Technol. 2012;2(1).
15. Yuvaraj PB, Inamdar KH, Patil PV. Application of Taguchi method for design of experiments in turning gray cast iron. Int J Eng Res Appl. 2012;2(3):1391–1397.
16. Kondapalli SP, Chalamalasetti SR, Damera NR. Application of Taguchi-based design of experiments to fusion arc weld processes: Review. Int J Technol Manag. 2013;2(1):1–8.

The valuable resources are rotating technology. In industrial applications, several machines are essential to the effective operation of any system. This article describes the engineering process for developing designs for analyzing variation and the optimization of condition monitoring by the impacts of vibration parameters using Taguchi processes to improve the quality of manufactured items. Crucial spinning equipment is included in the experiment to maximize the vibration frequency reactivity. Using Minitab 16 software, a Taguchi orthogonal array with three vibration parameter levels is built. The Taguchi approach minimizes quality characteristic changes caused by uncontrolled parameters by emphasizing the significance of examining response variation using the signal-to-noise (S/N) ratio. “The larger-the-better” was the principle that guided when it came to vibration frequency as a qualitative attribute. In order to investigate the performance characteristics, the impact of process factors on the condition monitoring process is examined using an examination of variance (ANOVA). Because it minimizes the number of tests and identifies the important parameter, it is also anticipated that the Taguchi technique will be an effective means to optimize different vibration parameters.

Keywords:Taguchi method, orthogonal array, vibration parameters, rotating machinery, ANOVA, Signal to noise ratio

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Michelini R, Crenna F, Rossi GB. Diagnostics for monitoring maintenance and quality manufacturing. Int Ser Eng Technol Appl Sci. 2001;1(1):1–74.
2. Benbouzid MEH. A review of induction motors signature analysis as a medium for faults detection. IEEE Trans Ind Electron. 2000;47(5):984–93.
3. Al-Khazali HAH, Askari MR. The experimental analysis of vibration monitoring in system rotor dynamic with validate results using simulation data. ISRN Mech Eng. 2012;2012:1–17.
4. Green I, Casey C. Crack detection in a rotor dynamic system by vibration monitoring—Part I: Analysis. J Eng Gas Turbines Power. 2005;127(2):425.
5. Ghafari SH. Condition monitoring of industrial fans. Proc 22nd Semin Mach Vib CMVA. 2004;1–6.
6. Lees AW, Sinha JK, Friswell MI. Multi-plane balancing of a rotating machine using run-down data. Proc 21st IMAC. 2003;(230):1–6.
7. Muszynska A. Vibrational diagnostics of rotating machinery malfunctions. Int J Rotating Mach. 1995;1(3–4):237–266.
8. Robichaud J, Eng P. Reference standards for vibration monitoring and analysis. Bretech Eng Ltd. 2009;1–10.
9. Phadke MS. Quality engineering using robust design. Englewood Cliffs, NJ: PTR Prentice Hall; 1989. 1–342.
10. Alagic I. Design of experiment and Taguchi method application in analysis of gear oil pump flow capacity. Proc 6th Workshop Eur Sci Ind Collab Adv Technol Manuf WESIC’08; 2008 Sep 25-26; Bucharest, Romania.
11. Rao RS, Padmanabhan G. Application of Taguchi methods and ANOVA in optimization of process parameters for metal removal rate in electrochemical machining of Al/5%SiC composites. Int J Eng Res Appl. 2012;2(3):192–197.
12. Bharti A, Moulick SK. Parametric optimization of multi-response factors in micro-drilling operation. Int J Sci Eng Res. 2013;4(7).
13. Gopalsamy B, Mondal B, Ghosh S. Taguchi method and ANOVA: An approach for process parameters optimization of hard machining while hardened steel. J Sci Ind Res. 2009;68(7):686–695.
14. Krishankant, Taneja J, Bector M, Kumar R. Application of Taguchi method for optimizing turning process by the effects of machining parameters. Int J Eng Adv Technol. 2012;2(1).
15. Yuvaraj PB, Inamdar KH, Patil PV. Application of Taguchi method for design of experiments in turning gray cast iron. Int J Eng Res Appl. 2012;2(3):1391–1397.
16. Kondapalli SP, Chalamalasetti SR, Damera NR. Application of Taguchi-based design of experiments to fusion arc weld processes: Review. Int J Technol Manag. 2013;2(1):1–8.