Developing a life cycle cost model for real-time condition monitoring in railways under uncertainty

Abstract

The Shanghai Transport Committee has estimated that passenger traffic increased fivefold between 2005 and 2014, and will continue to increase. At the same time, the maintenance costs of the Shanghai Metro have increased to about six times their original value. To ensure reliability, availability, maintainability and safety (RAMS) in railways, equipment sometimes needs to be upgraded; new technology is an effective way of modernizing the system. Condition monitoring techniques are considered to be a pragmatic approach to improve RAMS in railways. Bearings are seen to be a key factor in the successful operation of railways, as their performance is related to safety and reliability. To meet the safety requirements, an efficient method is to implement a real-time condition monitoring (RTCM) technique. To evaluate the economic cost of this investment in RTCM, the life cycle cost (LCC) should be considered. A Petri net combined with the Monte Carlo method is used to simulate the LCC evaluation process and a case study of how to employ this method is presented.

Keywords

Railway bearings life cycle cost Petri net Real-time condition monitoring

Get full access to this article

View all access options for this article.

References

Institute of Urban Comprehensive Traffic Plan in Shanghai. The 5th investigation report on comprehensive traffic in Shanghai. Report, Shanghai Transportation Committee, China, 2014.

Erdoğan

Tekin

. Condition monitoring for system performance. Engng Sci Technol, Int J 2013; 16(2): 97–105.

Roden

. Monitoring system gives early warning of problems. Int Railway J 2005; 45(9): 36–49.

Marino

Distante

Mazzeo

. A real-time visual inspection system for railway maintenance: automatic hexagonal-headed bolts detection. IEEE Trans Syst Man Cybern, Part C: Appl Rev 2007; 37(3): 418–428.

El-Akruti

Dwight

Tieling

. The role of life cycle cost in engineering asset management. Engineering asset management-systems, professional practices and certification, Springer, 2015, pp. 173–188.

Arthur Megaloconomos. Total asset management - life cycle costing guideline. Report, New South Wales Treasury, Australia, 2004.

Proctor P. Infrastructure Risk Modelling – Electric Machine Point Operating Mechanism: HW Type. Report, EE&CS Railtrack H.Q., UK, 2000.

García Márquez

Lewis

Tobias

. Life cycle costs for railway condition monitoring. Transport Res Part E: Logistics Transport Rev 2008; 44(6): 1175–1187.

Hokstad P. Life cycle cost analysis in railway systems. Report, SINTEF Industrial Management Safety and Reliability, Norway, 1998.

10.

IEC 300-3-3: 1996. Dependability management - part 3: application guide - section 3: life cycle costing.

11.

Kim

Lee

. Development of a life cycle cost estimate system for structures of light rail transit infrastructure. Autom Construct 2010; 19(3): 308–325.

12.

Vintr Z and Vintr M. An assessment of mean time between failures for a group of rolling bearings. In: Huang HZ (ed.) The IEEE international conference on quality, reliability, risk, maintenance, and safety engineering, Xi'an, China, 17–19 June 2011, pp.177–181.

13.

Ferreira

Balthazar

Araujo

. An investigation of rail bearing reliability under real conditions of use. Engng Fail Anal 2003; 10(6): 745–758.

14.

Johnson

. The statistical treatment of fatigue experiments, Amsterdam, The Netherlands: Elsevier, 1964.

15.

Lipson

Sheth

. Statistical design and analysis of engineering experiments, New York: NY: McGraw-Hill, 1973.

16.

Bergling G. Fiabilidad de los Rodamientos. La Revista de Rodamientos, 1976, pp.188–121.

17.

Lindemann

. Performance modelling with deterministic and stochastic Petri nets. Perform Eval Rev 1998; 26: 3–14.

18.

Ghazel M. A behavioural model for the level crossing collision risk assessment. In: Guarascio M, Brebbia CA and Garzia F (eds) The third international conference on safety and security, Rome, Italy, 1–3 July 2009, pp.637–645.

19.

Andrews

. A modelling approach to railway track asset management. Proc IMechE, Part F: J Rail Rapid Transit 2012; 227(1): 56–73.

20.

Andrews

Prescott

de Rozières

. A stochastic model for railway track asset management. Reliab Engng Syst Saf 2014; 12(7): 126–139.

21.

Di Zhang

Lei

. Railway train wheel maintenance model and its application. Transport Res Record: J Transport Res Board 2014; 2448: 28–36.

22.

Rama D and Andrews J. A system-wide modelling approach to railway infrastructure asset management. In: Jackson L and Andrews J (eds) Advances in risk and reliability technology symposium, Loughborough, UK, 21–23 May 2013, pp.7–22. Loughborough: Loughborough University.

23.

Kumar UD, Crocker J, Knezevic J, et al. Reliability maintenance and logistic support: a life cycle approach. 1st ed. Kluwer Academic Publishers: USA, 2000.