Optimizing preventive maintenance policy: A data-driven application for a light rail braking system

Abstract

This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions.

New reliability-based model of stock optimisation for railroad passenger wagon maintenance

“…The increase in costs of materials increases to 202,500 US Dollars up until the reliability falls to zero for Group 13 cars. The coefficient of determination of dependency for passenger wagon reliability in terms of costs of materials and in line with equation (12) amounts to 0.7439. Hence, for example, maintaining railroad car reliability at 90% requires allocating approx.…”

“…The derived mathematical model describing the curve in Figure 6 is as follows: 13 (12) where: R 13m (t) -reliability of Group 13 cars, T m13total cost of Group 13 materials (US Dollars). The curve in Figure 6 for Group 13 passenger wagons shows an increase in costs of parts and materials amounting up to 62,456 US Dollars and reflecting a car reliability of 100%.…”

“…The remaining 34 x 2 = 68 mathematical models were obtained in the same way for the passenger wagon groups based on the technical characteristics given in Table 1. After obtaining the model for dependency of reliability for the group of wagons in terms of operating time and costs of parts using regression models, phase 2 defined 36 inequalities according to equation (8) and in line with constraints to costs of parts and materials (right side of equation (8) -b 1 to b 36 ) as a function of reliability for groups of passenger wagons according to equations (10) and (12) with a given goal function based on equation 7for calculating optimal costs of maintenance. Shown below in Table 2 is the result of the obtained optimal quantities of parts and materials for some of the total 567 parts and materials which were included in the study, using the linear programming method as well as goal function, while the value of optimal costs in the US Dollars necessary for maintaining the reliability of the entire fleet of passenger wagons at the given 90% level for a total of 36 inequalities.…”

“…The maintenance policy defines one of three already defined actions for preventive maintenance in certain time intervals for each of the brake subsystems. Based on data for operation, maintenance and faults, Corman et al [12] modelled system and subsystem reliability with respect to maintenance policies using Weibull distribution. Nikšić's [13] doctoral thesis explored availability, reliability and the structure of a railroad car fleet belonging to Croatian Railways and also analysed faults in a particular series of tow railroad cars and maintenance costs.…”

Change in the maintenance strategy as a method of improving the efficiency of the process of operation of railway means of transport

“…In the group of maintenance projects, particularly noteworthy is the change in the maintenance strategy concerning the maintenance plan structure and the change in the measures of intervals between checks and scheduled repairs (so-called maintenance levels). Reduction of preventive maintenance costs and implementation of modern maintenance methods, such as Condition-Based Maintenance (CBM) is the subject of many scientific publications devoted to this issue [1][2][3]. The research and development work, which were done on the change in the maintenance strategy [4][5][6][7][8][9][10], prove that the costs of preventive maintenance of railway means of transport form up to 30,5% of the Life Cycle Costs (LCC) and are the second dominating cost category after the costs of power or fuel consumption.…”