Failure Evaluation and Analysis of Mechatronics-Based Production Systems during Design Stage Using Structural Modeling

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A method based on structural modelling is developed for failure evaluation and analysis of mechatronics-based production systems. Majority of the elements in production systems are mechatronics-based, which includes various elements such as; electrical, electronic and mechanical. Each of these may have different failure types that may be interdependence/interactive. The reliability of the system mainly depends on how well the failures are taken care of during design stage. In general, individual failures are generalized into probable failure modes and early identification of these helps to reduce their probability. However, consideration of failures and their interdependence / interactions will help to evaluate and analyse the failures of complicated systems in an efficient and effective manner and increase the inherent system reliability. The system structure modeling helps in this regard. Digraph model, in conjunction with matrix method, is employed for failure evaluation and analysis of a mechatronics-based production system based on its structure.

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Edited by:

Dr. M. Selvaraj, Dr. M. S. Alphin, Dr. M. Nalla Mohamed, Dr. G. Selvakumar

Pages:

799-805

Citation:

M.K. Loganathan et al., "Failure Evaluation and Analysis of Mechatronics-Based Production Systems during Design Stage Using Structural Modeling", Applied Mechanics and Materials, Vol. 852, pp. 799-805, 2016

Online since:

September 2016

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$41.00

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[1] R Neugebauer, B. Denkena, K. Wegener, Mechatronic systems for machine tools, Annals of the CIRP 56 (2007) 657 – 686.

DOI: https://doi.org/10.1016/j.cirp.2007.10.007

[2] K.M. Blache, A.B. Shrivastava, Defining failure of manufacturing machinery and equipment, Proc. Annual Reliability and Maintainability Symposium, IEEE, Anaheim, California, USA, 24-27 January 1994, pp.69-75.

DOI: https://doi.org/10.1109/rams.1994.291084

[3] A. Brall, A model for success in implementing an R&M program by a supplier of manufacturing machinery, Proc. Annual Reliability and Maintainability Symposium, IEEE, Anaheim, California, USA, 24-27 January 1994, pp.59-64.

DOI: https://doi.org/10.1109/rams.1994.291082

[4] F.H. Raffa, F. Pakish, R&M Initiatives for the 60-degree V-6 engine manufacturing program, Proc. Annual Reliability and Maintainability Symposium, IEEE, Anaheim, California, USA, 24-27 January 1994, pp.76-82.

DOI: https://doi.org/10.1109/rams.1994.291085

[5] G. Zhou, Y. Jia, H. Zhang, et al., A new single-sample failure model and its application to a special CNC system, Int. J. Qual. Reliab. Mgt., 22 (2004) 421-430.

[6] D.H. Kim, S.H. Kim, J.Y. Song, Diagnosing the cause of operational faults in machine tools with an open architecture CNC, J. Mech. Sci. Technol (KSME Int. J. ) 19 (2005) 1597-1610.

DOI: https://doi.org/10.1007/bf03023937

[7] G. Shen, X. Wang, Y. Zhang, et al., Fuzzy analysis on criticality of tool magazine based on type-2 membership function, Proc. IEEE Int Conf on Electrical and Control Engineering (ICECE), Wuhan, China, 25-27 June 2010, pp.3779-3783.

[8] M.K. Loganathan, O.P. Gandhi, Reliability enhancement of manufacturing systems through functions, Journal of Engineering Manufacture (2015) 1 – 19 [DOI: 10. 1177/0954405415612324].

[9] M.K. Loganathan, M.S. Gandhi, O.P. Gandhi, Functional cause analysis of complex manufacturing systems using structure, Journal of Engineering Manufacture, 229 (2015) 533 – 545.

DOI: https://doi.org/10.1177/0954405414528310

[10] M. Marcus, H. Minc, Permanents, Am. Math. Monthly 72 (1965) 571-591.

[11] A. Baykasoglu, A review and analysis of graph theoretical-matrix permanent, approach to decision making with example applications, Artificial Intelligence Review 42 (2014) 573 – 605.

DOI: https://doi.org/10.1007/s10462-012-9354-y

[12] C.E. Ebeling, An introduction to reliability and maintainability engineering, Tata McGraw-Hill Education, New Delhi, (2004).