Maintenance management balanced scorecard approach for urban transport fleets

Abstract

Attending the important role of maintenance function in any production or service provider company, the measurement and assessment of maintenance performance is crucial for competitiveness and future survival. That situation is even more critical in urban transport fleets where some specific boundary conditions and special characteristics will affect maintenance policy and implementation. This paper presents a deep review of different studies worldwide to define the most proper and effective maintenance performance indicators, selecting and refining the most important ones to obtain a reduced maintenance management balanced scorecard. That balanced scorecard is proposed as a main tool for urban transport fleet maintenance managers to assess efficiency and effectiveness of maintenance processes and will be used as a basis for a future benchmarking process for this type of companies.

An adaptable end-to-end maintenance performance diagnostic framework

“…Tsang et al (1999) introduce a holistic approach to establish maintenance performance measures using the well-known balanced scorecard, which translates a business unit's strategy around four perspectives: financial, customer, internal process, and learning and growth (Kaplan and Norton, 1996). In recent studies, various versions of the modified balanced scorecard have been developed for maintenance performance-related applications, focusing mainly on the inclusion of non-financial perspectives (Campos et al, 2017;Maci an et al, 2019;Sirin et al, 2020;Tanoto et al, 2022), and alignment with objectives and information systems (Campos et al, 2017). The European standard for maintenance key performance indicators provides an organizational model of maintenance function, which is composed of six sub-functions: health-safety-environment, management, people competence, engineering, organization and support, and administration and supply (EN:15341, 2019).…”

“…In recent studies, various versions of the modified balanced scorecard have been developed for maintenance performance-related applications, focusing mainly on the inclusion of non-financial perspectives (Campos et al. , 2017; Macián et al. , 2019; Sirin et al.…”

Application of the logistic regression for determining transition probability matrix of operating states in the transport systems

“…An alternative for the systems that do not satisfy Markov property are classic reliability methods, allowing to determine empirical characteristics such as: renewal stream, renewal function, time to the next defect or intensity of the renewal stream [6,14,35] and calculating the main system assessment measures based on them [15,23,42]. In the literature, as part of similar studies, various models are presented [30,43], including semi-Markov [7,24] and also those using artificial neural networks [10,33], factorization algorithm [31], fault trees [52] or reliability models [36,42].…”