Share:


Reserve fleet indexed to exogenous cost variables

Abstract

Identifying the optimal time to replace a passenger bus in a buses fleet has implications on the size of the reserve fleet. Such calculations rest on endogenous and exogenous economic variables: the former include operating and maintenance costs and bus depreciation; the latter include market imponderables such as the inflation and real discount rates, as well as energy costs, particularly fuel. The authors have created models for the withdrawal/replacement of buses using endogenous economic variables. The models include standard econometric models reflecting the influence of maintenance policies, especially Condition Monitoring (CM) or predictive maintenance, and the size of the reserve fleet. The paper deals with exogenous economic variables, specifically the influence of the cost of money, the inflation and real discount rates rate and the cost of fuel. Both variables fluctuate over time. The paper proposes analytical models for determining the influence of those variables on the withdrawal time and the size of the reserve fleet. It then comprehensively summarizes the variables in a global model, showing its relevance to the dimensioning of the reserve fleet and the withdrawal time.

Keyword : life cycle cost (LCC), reserve fleet, maintenance, econometric models, economic life, lifespan

How to Cite
Nogueira Raposo, H. D., Farinha, J. M. T., Ferreira, L. A., & Galar, D. (2019). Reserve fleet indexed to exogenous cost variables. Transport, 34(4), 437-454. https://doi.org/10.3846/transport.2019.11079
Published in Issue
Sep 13, 2019
Abstract Views
1295
PDF Downloads
708
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Amaya, E. J.; Tonaco, R.; Souza, R. Q.; Álvares, A. J. 2007. Sistema inteligente de manutenção baseada em condição para usina hidrelétrica de Balbina, in 8° Congreso Iberoamericano de Ingeniería Mecánica (CIBIM8), 23–25 Octubro 2007, Cusco, Perú, 1–7. Available from Internet: http://congreso.pucp.edu.pe/cibim8/pdf/12/12-17.pdf (in Portuguese).

André, J. 2008. Probabilidades e Estatística para Engenharia. Editora: Lidel. 600 p. (in Portuguese).

Aoudia, M.; Belmokhtar, O.; Zwingelstein, G. 2008. Economic impact of maintenance management ineffectiveness of an oil and gas company, Journal of Quality in Maintenance Engineering 14(3): 237–261. https://doi.org/10.1108/13552510810899454

Araujo, M. S.; Bezerra, C. A. 2004. Desenvolvimento de componentes para sistemas estocásticos de apoio à decisão, in IV Congresso Brasileiro de Computação – CBComp 2004, 8–12 Outubro 2004, Itajaí, Santa Catarina, Brasil, 101–107. Available from Internet: http://www.ufrgs.br/niee/eventos/CBCOMP/2004/pdf/Engenharia_Software/t170100034_3.pdf (in Portuguese).

Assaf Neto, A. 2014. Finanças Corporativas e Valor. Editora: Atlas. 824 p. (in Portuguese).

Assis, R. 2014. Apoio à Decisão em Manutenção e Gestão de Ativos Físicos. Editora: Lidel. 592 p. (in Portuguese).

Assis, R.; Julião, J. 2009. Gestão da manutenção ou gestão de activos? (Custos ao longo do ciclo de vida), in 10º Congresso Nacional de Manutenção, 10–20 Novembro 2009, Figueira da Foz, Portugal, 1–19. (in Portuguese).

ASTM E917-17. Standard Practice for Measuring Life-Cycle Costs of Buildings and Building Systems. https://doi.org/10.1520/E0917-17

Beichelt, F. 2001. A replacement policy based on limiting the cumulative maintenance cost, International Journal of Quality & Reliability Management 18(1): 76–83. https://doi.org/10.1108/02656710110364459

Bescherer, F. 2005. Established Life Cycle Concepts in the Business Environment – Introduction and Terminology. Laboratory of Industrial Management, Helsinki University of Technology, Finland.

Cabral, J. S 2006. Organização e Gestão da Manutenção: dos Conceitos à Prática. Editora: Lidel. 384 p. (in Portuguese).

Cabrita, C. P.; Cardoso, A. J. M. 2015. Conceitos e definições de falha e avaria nas normas portuguesas de manutenção NP EN 13306:2007 e NP EN 15341:2009, Revista de Manutenção 125(2): 4–9. (in Portuguese).

Campello, R. J. G. B.; Amaral, W. C. 2001. Modeling and linguistic knowledge extraction from systems using fuzzy relational models, Fuzzy Sets and Systems 121(1): 113–126. https://doi.org/10.1016/S0165-0114(99)00175-X

Campos, L. C. D.; Vellasco, M. M. B. R.; Lazo, J. G. L. 2010. A stochastic model based on neural networks, in The 2011 International Joint Conference on Neural Networks, 31 July–5 August 2011, San Jose, CA, USA, 1482–1488. https://doi.org/10.1109/IJCNN.2011.6033399

Casarotto Filho, N.; Kopittke, B. H. 2010. Análise de Investimentos: Matemática Financeira, Engenharia Econômica, Estratégia Empresarial. Editora: Atlas. 432 p. (in Portuguese).

Chen, D.; Wang, L.; Li, L. 2015. Position computation models for high-speed train based on support vector machine approach, Applied Soft Computing 30: 758–766. https://doi.org/10.1016/j.asoc.2015.01.017

Couellan, N.; Jan, S.; Jorquera, T.; Georgé, J.-P. 2015. Self-adaptive support vector machine: a multi-agent optimization perspective, Expert Systems with Applications 42(9): 4284–4298. https://doi.org/10.1016/j.eswa.2015.01.028

Durairaj, S. K.; Ong, S. K.; Nee, A. Y. C.; Tan, R. B. H. 2002. Evaluation of life cycle cost analysis methodologies, Corporate Environmental Strategy 9(1): 30–39. https://doi.org/10.1016/S1066-7938(01)00141-5

Emblemsvag, J. 2001. Activity‐based life‐cycle costing, Managerial Auditing Journal 16(1): 17–27. https://doi.org/10.1108/02686900110363447

Farinha, J. M. T. 2011. Manutenção: a Terologia e as Novas Ferramentas de Gestão. Editora: Monitor. 216 p. (in Portuguese).

Feldens, A. G.; Muller, C. J.; Filomena, T. P.; Neto, F. J. K.; Castro, A. S.; Anzanello, M. J. 2010. Política para avaliação e substituição de frota por meio da adoção de modelo multicritério, ABCustos, São Leopoldo: Associação Brasileira de Custos 5(1): 61–91. Available from Internet: https://abcustos.emnuvens.com.br/abcustos/article/view/86 (in Portuguese).

Figueiredo, L. M. J. 2009. Modelo Multicritério de Apoio à Substituição de Equipamentos Médicos Hospitalares: Dissertação para a atribuição do Grau de Mestre em Engenharia Biomédica. Instituto Superior Técnico, Universidade Técnica de Lisboa, Lisboa, Portugal. 100 p. Available from Internet: https://fenix.tecnico.ulisboa.pt/downloadFile/395139481609/Tese.pdf (in Portuguese).

FTA. 1987. FTA Circular C 9030.1A. US Department of Transportation, Federal Transit Administration (FTA), Washington, DC, US.

Gurney, K. 1997. An Introduction to Neural Networks. CRC Press. 234 p.

Hritonenko, N.; Yatsenko, Y. 2007. Optimal equipment replacement without paradoxes: a continuous analysis, Operations Research Letters 35(2): 245–250. https://doi.org/10.1016/j.orl.2006.03.001

Huang, J.-Y.; Yao, M.-J. 2008. On the coordination of maintenance scheduling for transportation fleets of many branches of a logistic service provider, Computers & Mathematics with Applications 56(5): 1303–1313. https://doi.org/10.1016/j.camwa.2008.01.037

ISO 55000:2014. Asset Management – Overview, Principles and Terminology.

ISO 55001:2014. Asset Management – Management Systems – Requirements.

ISO 55002:2014. Asset Management – Management Systems – Guidelines for the Application of ISO 55001.

Jin, D.; Kite-Powell, H. L. 2000. Optimal fleet utilization and replacement, Transportation Research Part E: Logistics and Transportation Review 36(1): 3–20. https://doi.org/10.1016/S1366-5545(99)00021-6

Keles, P.; Hartman, J. C. 2004. Case study: bus fleet replacement, The Engineering Economist: a Journal Devoted to the Problems of Capital Investment 49(3): 253–278. https://doi.org/10.1080/00137910490498951

Khasnabis, S.; Alsaidi, E.; Ellis, R. D. 2002. Optimal allocation of resources to meet transit fleet requirements, Journal of Transportation Engineering 128(6): 509–518. https://doi.org/10.1061/(ASCE)0733-947X(2002)128:6(509)

Korpi, E.; Ala‐Risku, T. 2008. Life cycle costing: a review of published case studies, Managerial Auditing Journal 23(3): 240–261. https://doi.org/10.1108/02686900810857703

Leung, F. K. N.; Cheng, A. L. M. 2000. Determining replacement policies for bus engines, International Journal of Quality & Reliability Management 17(7): 771–783. https://doi.org/10.1108/02656710010336361

Lindholm, A.; Suomala, P. 2005. The possibilities of life cycle costing in outsourcing decision making, in Frontiers of eBusiness Research 2004: FeBR 2004: Conference Proceedings, 20–22 September 2004, Tampere, Finland, 226–241.

Luna, I.; Ballini, R.; Soares, S. 2006. Técnica de identificação de modelos lineares e não-lineares de séries temporais, Revista Controle & Automação 17(3): 245–256. https://doi.org/10.1590/S0103-17592006000300001 (in Portuguese).

Makridakis, S. G.; Wheelwright, S. C.; Hyndman, R. J. 1998. Forecasting: Methods and Applications. Wiley. 656 p.

Motta, R. R.; Calôba, G. M. 2002. Análise de Investimentos: Tomada de Decisão em Projetos Industriai. Editora: Atlas. 391 p. (in Portuguese).

Müller, D. 2007. Processos Estocásticos e Aplicações. Editora: Almedina. 276 p. (in Portuguese).

NP EN 15341:2009. Manutenção: Indicadores de Desempenho da Manutenção (KPI). Norma Portuguesa. (in Portuguese).

Oliveira, J. A. N. 1982. Engenharia Econômica: Uma Abordagem às Decisões de Investimento. Editora: McGraw Hill. 172 p. (in Portuguese).

PAS 55-1:2008. Asset Management. Part 1: Specification for the Optimized Management of Physical Assets. British Standards, UK.

PAS 55-2:2008. Asset Management. Part 2: Guidelines for the application of PAS 55-1. British Standards, UK.

Pooyan, N.; Shahbazian, M., Salahshoor, K.; Hadian, M. 2015. Simultaneous fault diagnosis using multi class support vector machine in a dew point process, Journal of Natural Gas Science and Engineering 23: 373–379. https://doi.org/10.1016/j.jngse.2015.01.043

Raposo, H.; Farinha, J. T.; Oliveira, R.; Ferreira, L. A.; André, J. 2014. Time replacement optimization models for urban transportation buses with indexation to fleet reserve, in MPMM Maintenance Performance Measurement and Management: Proceedings of Maintenance Performance Measurement and Management (MPMM): Conference 2014, 4–5 September 2014, Coimbra, Portugal, 41–48. https://doi.org/10.14195/978-972-8954-42-0_7

Reis, M. A.; Melo, S. A. B. V.; Duarte, A. A.; Schnitman, L. 2010. A utilização de redes Bayesianas no processo decisório de intervenções em equipamentos, in XVIII Congresso Brasileiro de Automática, 12–16 Setembro 2010, Bonito, Brasil, 5058–5064. (in Portuguese).

Rogers, J. L.; Hartman, J. C. 2005. Equipment replacement under continuous and discontinuous technological change, IMA Journal of Management Mathematics 16(1): 23–36. https://doi.org/10.1093/imaman/dph027

Scarf, P. A.; Bouamra, O. 1999. A capital equipment replacement model for a fleet with variable size, Journal of Quality in Maintenance Engineering 5(1): 40–49. https://doi.org/10.1108/13552519910257050

Simões, A. S. 2011. Manutenção Condicionada às Emissões Poluentes em Autocarros Urbanos: Diagnóstico por Cadeias Escondidas de Markov: Tese Aprovada em Provas Públicas Para a Obtenção do Grau de Doutor em Transportes. Instituto Superior Técnico, Universidade Técnica de Lisboa, Lisboa, Portugal. 322 p. Available from Internet: http://files.isec.pt/DOCUMENTOS/SERVICOS/BIBLIO/teses/Tese_Dout_Antonio-Simoes.pdf (in Portuguese).

Sullivan, W. G.; McDonald, T. N.; Van Aken, E. M. 2002. Equipment replacement decisions and lean manufacturing, Robotics and Computer-Integrated Manufacturing 18(3–4): 255–265. https://doi.org/10.1016/S0736-5845(02)00016-9

Tsoukalas, L. H.; Uhrig, R. E.; Zadeh, L. A. 1997. Fuzzy and Neural Approaches in Engineering. Wiley-Interscience. 600 p.

Vey, I. H.; Rosa, R. M. 2004. Utilização do custo anual uniforme equivalente na substituição de frota em empresas de transporte de passageiros, Revista Eletrônica de Contabilidade 1(1): 150–173. https://doi.org/10.5902/198109465890 (in Portuguese).

Vujanović, D.; Momčilović, V.; Bojović, N.; Papić, V. 2012. Evaluation of vehicle fleet maintenance management indicators by application of DEMATEL and ANP, Expert Systems with Applications 39(12): 10552–10563. https://doi.org/10.1016/j.eswa.2012.02.159

Wijaya, A. R.; Lundberg, J.; Kumar, U. 2012. Robust‐optimum multi‐attribute age‐based replacement policy, Journal of Quality in Maintenance Engineering 18(3): 325–343, Emerald Group Publishing Limited 1355-2511. https://doi.org/10.1108/13552511211265910

Yager, R. R.; Zadeh, L. A. (Eds.). 1992. An Introduction to Fuzzy Logic Applications in Intelligent Systems. Springer. 356 p. https://doi.org/10.1007/978-1-4615-3640-6

Zhao, H. 2009. A chaotic time series prediction based on neural network: evidence from the Shanghai composite index in China, in 2009 International Conference on Test and Measurement, 5–6 December 2009, Hong Kong, China, 382–385. https://doi.org/10.1109/ICTM.2009.5413024

Zohrul Kabir, A. B. M. 1996. Evaluation of overhaul/replacement policy for a fleet of buses, Journal of Quality in Maintenance Engineering 2(3): 49–59. https://doi.org/10.1108/13552519610130440