Integration of FMECA and statistical snalysis for predictive maintenance
The estimation of time-to-failure of machines is of utmost importance in the Manufacturing Industry. As the world is moving towards Industry 4.0, it is high time that we progress from the traditional methods, where we wait for a breakdown to occur, to the prognostics based methods. It is the need of the era to be aware of any incident before it occurs. This study provides application of Statistical-based Predictive maintenance. A BOPP Production line has been considered as a case study for this research. Since the inception of the line in 2013, it is evident that 60% of breakdowns are due to lack of maintenance and timely replacement of bearings. Therefore, the research is based on the application of FMECA (Failure Modes, Effects and Criticality Analysis) to determine which bearing in the production line is most prone to failure and determination of which statistical model best fits the failure data of the most critical bearing. The result provides the best distribution fit for the failure data and the fit can be utilized for further study on RUL (Remaining Useful Life) of the bearing through Bayesian Inference.
Becker, W.T., Shipley, R.J. (2002). Failure Analysis and Prevention. In W. T. Becker, & R. J. https://doi.org/10.31399/asm.hb.v11.9781627081801
Carlson, C.S. (2014). Understanding and Applying the Fundamentals of FMEAs. 2014 Annual Reliability and Maintainability Symposium. Tucson: IEEE.
Carlson, C.S. (2016). Understanding and Applying the Fundamentals of FMEAs. Reliability and Maintainability Symposium.
Carnero, M. (2006). An evaluation system of the setting up of predictive maintenance programmes. Reliability Engineering and System Safety, 91, 945-963. https://doi.org/10.1016/j.ress.2005.09.003
Merovci, F., Elbatal, I. (2015). Weibull Rayleigh Distribution: Theory and Applications. Applied Mathematics & Information Sciences, 9(5), 1-11.
Mobley, R.K. (2002). An Introduction to Predictive Maintenance. Woburn, Massachusetts, USA: Elsevier Science. https://doi.org/10.1016/B978-075067531-4/50006-3
Muller, C. (2003). Reliability Analysis of the 4.5 Roller Bearing. Monterey, California: Naval Postgraduate School.
Rao, B. (1996). Handbook of Condition Monitoring. Oxford: Elsevier Advanced Technology.
Sahoo, T., Sarkar, P.K., Sarkar, A.K. (2014). Maintenance optimization for critical equipments in process industries based on FMECA method. International Journal of Engineering and Innovative Technology, 3(10), 107-112.
Susto, G.A., Beghi, A., Luca, C.D. (2012). A Predictive Maintenance System for Epitaxy Processes Based on Filtering and Prediction Techniques. IEEE Transactions on Semiconductor Manufacturing, 25(4), 638-649. https://doi.org/10.1109/TSM.2012.2209131
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