Obsolescence optimization of electronic and mechatronic components by considering dependability and energy consumption

M. A. Mellal , S. Adjerid , D. Benazzouz , S. Berrazouane , E. J. Williams

Journal of Central South University ›› 2013, Vol. 20 ›› Issue (5) : 1221 -1225.

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Journal of Central South University ›› 2013, Vol. 20 ›› Issue (5) : 1221 -1225. DOI: 10.1007/s11771-013-1605-9
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Obsolescence optimization of electronic and mechatronic components by considering dependability and energy consumption

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Abstract

Nowadays, rapid technological progress influences the dependability of equipments and also causes rapid obsolescence. The mechatronic and electronic equipment components are mostly affected by obsolescence. A new challenger unit possesses identical functionalities, but with higher performances. This work aims to find the optimal number of components which should be replaced by new-type units, under budgetary constraints. In this work, the new challenger unit is characterized by lower energy consumption and the optimization steps are based on genetic algorithm (GA). The result shows the importance of this type of replacement in order to economize energy consumption and to deal with obsolescence.

Keywords

obsolescence / lower energy consumption / mechatronic and electronic components / genetic algorithm

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M. A. Mellal, S. Adjerid, D. Benazzouz, S. Berrazouane, E. J. Williams. Obsolescence optimization of electronic and mechatronic components by considering dependability and energy consumption. Journal of Central South University, 2013, 20(5): 1221-1225 DOI:10.1007/s11771-013-1605-9

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References

[1]

ZafiropoulosE P. Reliability and cost optimization of electronic devices considering the component failure rate uncertainty [J]. Reliability Engineering and System Safety, 2004, 84(3): 271-284

[2]

MellalM A, AdjeridS, BenazzouzD. Modeling and simulation of mechatronic system to integrated design of supervision: Using a bond graph approach [J]. Applied Mechanics and Materials, 2011, 86: 467-470

[3]

MellalM A, AdjeridS, BenazzouzD. Modeling and simulation of mechatronic system to integrated design of supervision: Using a bond graph approach [C]. International Conference on Power Transmission. Xi’an, China, 20111-4

[4]

NohM S, HongD S. Implementation of remote monitoring system for prediction of tool wear and failure using ART2 [J]. Journal of Central South University of Technology, 2011, 18(1): 177-183

[5]

EltonE J, GruberM J. On the optimally of an equal life policy for equipment subject to technological improvement [J]. Operational Research, 1976, 27: 93-99

[6]

SchochetmanI E, SmithR L. Infinite horizon optimality criteria for equipment replacement under technological change [J]. Operations Research Letters, 2007, 35(4): 485-492

[7]

HritonenkoN, YatsenkoY. Optimal equipment replacement without paradoxes: A continous analysis [J]. Operations Research Letters, 2007, 35(2): 245-250

[8]

BorgonovoE, MarseguerraM, ZioE. A Monte Carlo methodological approach to plant availability modeling with maintenance, aging and obsolescence [J]. Reliability Engineering and System Safety, 2000, 67(1): 61-73

[9]

MichelO, LabeauP E, MercierS. Monte Carlo optimization of the replacement strategy of components subject to technological obsolescence [C]. International Conference on Probabilistic Safety Assessment and Management. Berlin, Germany, 20043098-3103

[10]

MercierS. Optimal replacement policy for obsolete components with general failure rates [J]. Applied Stochastic Models in Business and Industry, 2008, 24(3): 221-235

[11]

ClavareauJ, LabeauP E. Maintenance and replacement policies under technological obsolescence [J]. Reliability Engineering and System Safety, 2009, 94(2): 370-381

[12]

ElmakisD, LevitinG, LisnianskiA. Optimal scheduling for replacement of power system equipment with new-type one [C]// MMR’2002. Trondheim, Norway, 2002227-230

[13]

MercierS, LabeauP E. Optimal replacement policy for a series system with obsolescence [J]. Applied Stochastic Models in Business and Industry, 2004, 20(1): 73-91

[14]

DubosG F, SalehJ H. Risk of spacecraft on-orbit obsolescence: Novel framework, stochastic modeling and implications [J]. Acta Astronautica, 2010, 67(1/2): 155-172

[15]

BilimN. Optimum cutting speed of block-cutting machines in natural stones for energy saving [J]. Journal of Central South University of Technology, 2012, 19(5): 1234-1239

[16]

ChaudhryI A. Job shop scheduling problem with alternative machines using genetic algorithms [J]. Journal of Central South University of Technology, 2012, 19(5): 1322-1333

[17]

KwonS M, KimC H, ShinJ H. Optimal rotor wear design in hypotrochoidal gear pump using genetic algorithm [J]. Journal of Central South University of Technology, 2011, 18(3): 718-725

[18]

HollandJ. Adaptation in natural and artificial systems [M]. Ann Arbor: University of Michigan Press, 1975

[19]

SumathiS, SurekhaPComputational intelligence paradigms [M], 2010London, EnglandTaylor & Francis Group547-589

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