Publicado

2018-04-01

Monitoreo de la degradación de los vehículos de transporte de cargas a través de la disponibilidad

Freight vehicle condition monitoring through the availability

Palabras clave:

disponibilidad, disponibilidad límite, uso racional, flotas de transporte, toma de decisiones (es)
availability, availability threshold, rational use, transport fleet, decision making (en)

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Autores/as

La aplicación de enfoques de toma de decisión basados en el monitoreo de la degradación de los sistemas a situaciones reales presenta un grupo de barreras tales como la complejidad de los métodos, la disponibilidad de datos, tecnología y personal capacitado. En este trabajo se propone una vía para el monitoreo del estado del vehículo de transporte de cargas a través de la disponibilidad. Para ello se introduce la condición límite de uso racional de los vehículos y se presenta la expresión de la disponibilidad límite vinculada a los resultados económicos de la operación del vehículo, lo que posibilita valorar la conveniencia de la operación del mismo. La aplicación de la propuesta a una flota ilustra sus posibilidades en condiciones reales, obteniéndose un grado de acuerdo "Casi perfecto" entre los resultados del análisis de la disponibilidad y el resultado económico de la operación del vehículo.
The application of decision making approaches based on systems degradation monitoring in real situations are difficult. Among those difficulties are methods complexity and data, technology and capable personnel availability. In this paper, a way for monitoring freight vehicle condition through availability assessment is proposed. In order to do that, the rational use limit condition of freight vehicles is proposed and a mathematical model of the availability threshold linked with operation economic results is presented. The latest makes possible to value the vehicle operation convenience. The application of the proposal to a fleet shows its possibilities in real conditions. An "Almost perfect" agreement degree between the availability assessment results and the economic result of the vehicle operation was obtained.

Citas

Knesevic, J., Mantenimiento. Madrid, Isdefe, 1996.

Alaswad, S. and Xiang, Y.-A., Review on condition-based maintenance optimization models for stochastically deteriorating system. Reliability Engineering and System Safety. 157, pp. 54-63, 2017. DOI: 10.1016/j.ress.2016.08.009

Ahmad, R. y Kamaruddin, S.-A review of condition-based maintenance decision-making. European Journal of Industrial Engineering, 6(5), pp. 519-541, 2012. DOI: 10.1504/EJIE.2012.048854.

Zhou, X., Xi, L. y Lee J., Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation. Reliability Engineering & System Safety, 92, pp. 530-534, 2007.DOI: 10.1016/j.ress.2006.01.006.

Li, L., You, M. and Ni, J., Reliability-based dynamic maintenance threshold for failure prevention of continuously monitored degrading systems. Journal of Manufacturing Science and Engineering, Transactions of the ASME, 131, pp. 031010-1-031010-9, 2009. DOI: 10.1115/1.3123340.

Tywoniak, S., Rosqvist, T., Mardiasmo, D. and Kivits, R.-A., Towards an integrated perspective on fleet asset management: engineering and governance considerations. Proceedings of 3rd World Congress on Engineering Asset Management and Intelligent Maintenance Systems Conference (WCEAM-IMS 2008): Engineering Asset Management -A Foundation for Sustainable Development, 2008, pp. 1553-1567.

Collins, D.-H., Anderson-Cook, C.-M. and Huzurbazar, A.-V., System Health Assessment. Quality Engineering, 23(2), pp. 142-151, 2011. DOI: 10.1080/08982112.2010.529484.

Panagiotidou, S. and Tagaras, G. Statistical process control and condition-based maintenance, a meaningful relationship through data sharing. Production and Operations Management, 19(2), pp. 156-171, 2010. DOI: 10.3401/poms.1080.01073.

Xiang, Y., Joint optimization of X control chart and preventive maintenance policies: a discrete-time Markov chain approach. European Journal of Operational Research, 229(2013), pp. 382-390, 2013. DOI: 10.1016/j.ejor.2013.02.041.

Zhong, J., Ma, Y. and Tu, Y.-L. Integration of SPC and performance maintenance for supply chain system. International Journal of Production Research, 54(19), pp. 5932-5945, 2016. DOI: 10.1080/00207543.2016.1189104.

Jiang, R. and Shi, G., Condition-based vehicle fleet retirement decision, a case study. International Journal of Performability Engineering, 6(4), pp. 355-362, 2010.

Jiang, R. and Shi, G., Development and application of vehicle health index. Advanced Materials Research, (118-120), pp. 459-463, 2010. DOI: 10.4028/www.scientific.net/AMR.118-120.459.

Jiang, R., An overall performance measure for vehicle retirement decision. Chemical Engineering Transactions, 33, pp. 775-780, 2013. DOI: 10.3303/CET1333130.

Nowakowski, T., Tubis A., and Werbińska-Wojciechowska, S., Maintenance decision making process - a case study of passenger transportation company, en W. Zamojski, et al. Theory and engineering of complex systems and dependability, Springer, Brunów. pp. 305-318, 2015. DOI: 10.1007/978-3-319-19216-1_29.

Dekker, R., Applications of maintenance optimization models: a review and analysis. Reliability Engineering & System Safety, 51(3), pp. 229-240, 1996.

Van Horenbeek, A., Pintelon, L. and Muchiri, P., Maintenance optimization models and criteria. International Journal of System Assurance Engineering and Management, 1(3), pp. 189-200, 2010. DOI: 10.1007/s13198-011-0045-x.

van de Kerkhof, R.-M., Akkermans, H.-A. and Noorderhaven, N.-G., Knowledge lost in data: organizational impediments to condition-based maintenance in the process industry, in Logistics and Supply Chain Innovation, Lecture Notes en H. Zijm et. al. Logistics, , Springer International Publishing: Switzerland, 2016.

Tsui, K.-L., Chen, N., Zhou, Q., Hai Y. and Wang, W., Prognostics and health management: a review on data driven approaches. Mathematical Problems in Engineering, 2015, 17 P, 2015. DOI: 10.1155/2015/793161.

Shin, J.-H. and Jun, H.-B., On condition based maintenance policy. Journal of Computational Design and Engineering, 2(2015), pp. 119-127, 2015. DOI: 10.1016/j.jcde.2014.12.006.

Bivona, E. and Montemaggiorea, G.-B., Understanding short- and long-term implications of “myopic” fleet maintenance policies: a system dynamics application to a city bus company. System Dynamics Review, 26(3), pp. 195-215, 2010. DOI: 10.1002/sdr.450.

Stecki, J.-S., Rudov-Clark, S. and Stecki, C., The rise and fall of CBM (Condition based Maintenance). Key Engineering Materials. 588(2014), pp. 290-301. 2014. DOI: 10.4028/www.scientific.net/KEM.588.290.

Liao, H., Elsayed, E.-A. and Chan, L.-Y., Maintenance of continuously monitored degrading systems. European Journal of Operational Research, 175(2006), pp. 821-835, 2006. DOI: 10.1016/j.ejor.2005.05.017.

Yeh, R.-H. and Chang, W.-L., Optimal threshold value of failure-rate for leased products with preventive maintenance actions. Mathematical and Computer Modelling, 46(2007), pp. 730-737, 2007. DOI: 10.1016/j.mcm.2006.12.001.

Penabad-Sanz, L., Iznaga-Benítez, A.M. y Rodríguez-Ramos, P.A., Disposición y disponibilidad como indicadores para el transporte. Revista Ciencias Técnicas Agropecuarias, 25(4), pp. 64-73, 2016.

Gerdes, M., Scholz, D. and Galar, D., Effects of condition-based maintenance on costs caused by unscheduled maintenance of aircraft. Journal of Quality in Maintenance Engineering, 22(4), pp. 394-417, 2016. DOI: 10.1108/JQME-12-2015-0062.

Parthanadee, P., Buddhakulsomsiri, J. and Charnsethikul, P., A study of replacement rules for a parallel fleet replacement problem based on user preference utilization pattern and alternative fuel considerations. Computers & Industrial Engineering, 63(2012), pp. 46-57, 2012. DOI: 10.1016/j.cie.2012.01.011.

Kochnov, N. y Basté, J., Reparación de los automóviles. Vol. 1, La Habana, Cuba: EMPSES, 1986.

Trompet, M., Anderson, R.J. and Graham, D.J., Variability in comparable performance of urban bus operations. Transportation Research Record, December, pp. 177-184, 2009. DOI: 10.3141/2111-20.

Redmer, A., Strategic vehicle fleet management - the composition problem. LogForum, 11(1), pp. 119-126, 2015. DOI: 10.17270/J.LOG.2015.1.11.

Buchanan, J. and Scott, J. Vehicle utilization at bay of plenty electricity. Interfaces, 22(2), pp. 28-35, 1992.

Lopes-da-Costa-Filho, J.L. and de Athayde-Prata, B., Programação de caminhões de múltiplos tipos no transporte de derivados de petróleo para a construção de rodovias. Journal of Transport Literature, 9(2), 2015. DOI: 10.1590/2238-1031.jtl.v9n2a11.

Goel, A., A mixed integer programming formulation and effective cuts for minimising schedule durations of Australian truck drivers. Journal of Scheduling, 15(6), pp. 733-741, 2012. DOI: 10.1007/s10951-012-0282-0.

McKinnon, A., Synchronised auditing of truck utilisation and energy efficiency: a review of the British Government’s transport KPI programme, en World Conference on Transport Research. University of California, Berkeley, 2007.

Alves, R.T., Fiedler, N.C, da Silva, E.N., da Silva-Lopes, E. and do Carmo, F.C.d.A., Análise técnica e de custos do transporte de madeira com diferentes composições veículares. Revista Árvore, 37, pp. 897-904, 2013.

Afanasiev, L.L., et al, Sistema único de transportación y transportaciones por vehículos automotores. Moscú: Transport. 1984.

Everitt, B.S., The analysis of contingency tables. CRC Press.1992

Landis, J. and Koch, G., The measurement of observer agreement for categorical data. Biometrics, 33, pp. 159-74, 1977.

López-de-Ullibarri-Galparsoro, I. y Pita-Fernández, S., Medidas de concordancia: el coeficiente kappa. Cad aten primaria, 6, pp. 169-171, 1999.