Network level bridges maintenance planning using Multi-Attribute Utility Theory

Abstract

Bridge infrastructure managers are facing multiple challenges to improve the availability and serviceability of ageing infrastructure, while the maintenance planning is constrained by budget restrictions. Many research efforts are ongoing, for the last few decades, ranging from development of bridge management system, decision support tools, optimisation models, life cycle cost analysis, etc. Since transport infrastructures are deeply embedded in society, they are not only subject to technical requirements, but are required to meet the requirements of societal and economic developments. Therefore, bridge maintenance planning should accommodate multiple performance goals which need to be quantified by various performance indicators. In this paper, an application of Multi-Attribute Utility Theory (MAUT) for bridge maintenance planning is illustrated with a case study of bridges from the Netherlands road network. MAUT seeks to optimise multiple objectives by suggesting a trade-off among them and finally assigns a ranking to the considered bridges. Moreover, utility functions of MAUT appropriately account for the involved uncertainty and risk attitude of infrastructure managers. The main contribution of this study is in presenting a proof-of-concept on how MAUT provides a systematic approach to improve the decisionmaking of maintenance planning by making use of available data, accommodating multiple performance goals, their uncertainty, and preferences of infrastructure managers.

Life Cycle Sustainability Assessment for Multi-Criteria Decision Making in Bridge Design: A Review

“…The environmental criterion that has been used most by the reviewed articles (21 papers) is the emission of pollutants. On the contrary, four authors (Gervásio & da Silva, 2012;Bukhsh et al, 2018Bukhsh et al, , 2019Navarro et al, 2020) only consider the impact on the ozone layer depletion derived by construction and maintenance activities of bridges. It is worth noting that, among the articles investigated, only three base their environmental results on the use of specific, recognised environmental impact assessment techniques.…”

“…On the one hand, Navarro et al (2020) apply the life cycle impact assessment technique ReCiPe, including all the impact categories of such technique in their work and explicitly following the environmental ISO standards for the assessment. On the other hand, Bukhsh et al (2018Bukhsh et al ( , 2019 apply the CML 2001 methodology. It shall be mentioned that Gervásio and da Silva (2012) base their life cycle environmental assessment on the environmental ISO standards, although they do not explicitly mention the impact assessment technique used.…”

Categorization of the Condition of Railway Embankments Using a Multi-Attribute Utility Theory

“…Once the functions are constructed, the selection of the appropriate alternative can be done using an optimization method. This technique involves several steps [21], including the definition of objectives and constraints, followed by the definition of attributes and by the development of a single utility function for each of the selected attributes. By assigning relative weights to the multiple attributes, an amalgamation step follows, which includes combining the single criterion utility functions using the relative weights into one measure based on mathematical assumptions about the decision maker's preference structure.…”

“…Several publications also address the implementation of MAUT in the railway sector for selecting transportation corridors linked to a traffic simulation model [27], selecting railway lines for reconstruction [28], or railway route planning and design [29]. Additional papers consider civil engineering infrastructure assets, where MAUT is incorporated in maintenance decision-making [21,30,31]. In order to implement MAUT for the categorization of railway embankments, a selection of proper attributes and alternatives shall be conducted.…”

Performance‐Indikatoren für die Bewertung von Strukturen aus Konstruktionsbeton auf europäischer Ebene nach COST TU1406

“…Folgende Key‐Performance‐Indikatoren (KPI) hat die Arbeitsgruppe 2 (WG2) der COST TU1406 für Straßenbrücken ausgearbeitet: reliability (R), availability (A), maintainability (M), safety (S), security (Se), environment (E), costs (C), health (H), politics (P), rating/inspection (I), durablity (D). In einer COST‐TU1406‐Expertenrunde wurden für die Charakterisierung der „Kern“‐Performance‐Indikatoren (KPI ist eine kleinere Gruppe von signifikanten Performance‐Indikatoren) in einem weiteren Schritt folgende Kriterien definiert: PI sind Größen, welche (a) messbar, (b) quantifizierbar, (c) mit einem Zielwert vergleichbar, (d) für ein Ranking anwendbar, (e) für eine wirtschaftliche Entscheidung geeignet sein müssen und welche den KPI zugeordnet werden können.…”