Open Access Open Access  Restricted Access Subscription or Fee Access

Optimization of Effects of FMEA to Enhance Quality and Efficiency of CNC Machines in Valve Manufacturing Industry

Raj Kumar Salvi

Abstract


Failure mode and effects analysis (FMEA) is a systematic method for identification and
preventing problems of products and process before its occurrence. FMEA focus on
preventing defects, enhancing safety and increasing customer satisfaction. The FMEA needs to define parameters such as Severity (S), Occurrence (O), Detection (D) and Risk Priority Number (RPN). The conventional FMEA and grey relational analysis approaches are applied in this work. The rankings of the failure modes are both determined by conventional FMEA and the grey relational analysis. These approaches help to enhance the reliability of the prediction and the predicted ranking of CNC machines failure can be used for better decision-making concerning inspection and maintenance avoiding the possible risks and ultimately reduce the loss to the industry in terms of time, money and quality.

Full Text:

PDF

References


Z. Wu, J. Ahmad, J. Xu. A group

decision making framework based on

fuzzy VIKOR approach for machine

tool

selection

with

linguistic

information, Appl Soft Comput. 2016;

: 314–24p.

Z. Yang, B. Xu, F. Chen, Q. Hao, X.

Zhu, Y. Jia. A new failure mode and

effects analysis model of CNC

machine tool using fuzzy theory, Int

Conf Inform Automat. 2010; 32: 24–

p.

X. Wang, Y. Zhang, G. Shen. An

improved FMECA for feed system of

CNC machining center based on ICR

and DEMATEL method, Int J Adv

Manuf Technol. 2016; 83: 43–54p.

H. Li, F. Chen, Z. Yang, L. Wang, Y.

Kan. Failure mode analysis on

machining center based on possibility

theory, Int Conf Electr Eng Automat

Control. 2016; 367: 627–36p.

G. Gupta, R.P. Mishra. A failure

mode effect and criticality analysis of

conventional milling machine using

fuzzy logic: case study of RCM, Qual

Reliabil Eng Int. 2016; 06: 125–36p.

Y.M.

Degu,

R.S.

Moorthy.

Implementation of machinery failure

Salvi

mode and effect analysis in Amhara

Pipe Factory P.L.C., Bahir Dar,

Ethiopia, Am J Eng Res. 2014; 03(1):

–63p.

R.K. Salvi, C. Agarwal, B.P.

Nandwana, M.A. Saloda. Failure

mode and effect analysis for CNC

machines used in GG valves industry,

Int J Fract Damage Mech. 2016; 1(1):

–33p.

R.K. Salvi, C. Agarwal, B.P.

Nandwana,

M.A.

Saloda.

Implementation of machinery failure

mode and effect analysis for CNC

machines in valve manufacturing

industry, Int J Mech Hand

Automat.2016; 1(1): 10–5p.

R. Thakore, R. Dave, T. Parsana. A

case study: a process FMEA tool to

enhance quality and efficiency of

bearing manufacturing industry, Schol

J Eng Technol. 2015; 3(4B): 413–8p.

E. Bozdag, U. Asan, A. Soyer, S.

Serdarasan. Risk prioritization in

failure mode and effects analysis

using interval type-2 fuzzy sets,

Expert Syst Appl. 2015; 42: 4000–15p.

R.K. Salvi. Failure Mode and Effect

Analysis for CNC machines used in

GG Valve Industry. Maharana Pratap

University of Agriculture and

Technology,

Udaipur-313001,

Rajasthan, India, 2017.

R.K. Salvi, S. Jindal. FMEA to

enhance quality and efficiency of

CNC machines: a case study in valve

manufacturing industry, Indian Inst

Ind Eng (IIIE). 2017; 10(4): 35–41p.

Q. Zhou, V.V. Thai. Fuzzy and grey

theories in failure mode and effect

analysis for tanker equipment failure

prediction, Saf Sci. 2016; 83: 74–9p.




DOI: https://doi.org/10.37628/jcam.v3i2.433

Refbacks

  • There are currently no refbacks.