Prioritization of bridges for maintenance planning using data envelopment analysis

Abstract

Resources-especially funds allotted-for the maintenance of bridges, are generally scanty. Thus, it becomes difficult to select bridges for maintenance from among several competing bridges to ensure their safety and serviceability to the desired level. A bridge health index is considered a reasonably accurate depiction of the condition of a bridge and hence is the basis for most of the decisions on fund allocation. However, it still remains to be seen whether such a decision-making tool results in an efficient fund allocation. From data collected on Indian bridges, it is observed that fund allocation based on bridge condition is not always judicious. Rather, a number of factors affect the final decision on fund allocation. Hence, an alternative approach of data envelopment analysis (DEA) has been used for scoring the efficiency of 14 bridges selected for the study. Depending on the availability of data, this method can take into account other factors besides the bridge health index that influence decisions on maintenance planning. The variables selected for the DEA are: bridge health index, deck area of the bridge, maintenance cost of the bridge, and the age of the bridge. The allocation of funds for the maintenance of bridges based on DEA has proved to be comparatively more efficient. This has been illustrated with the help of a numerical example. The proposed method would enable bridge authorities to formulate better strategies for planning and executing bridge maintenance activities in a cost-effective manner.

Data Envelopment Analysis for Efficiency Measurement of Bridge Resilience

“…DEA is a widely used technique for efficiency measurement in research areas such as healthcare, agriculture, food processing, and selection of new technologies, among others (Ozbek et al, 2009;Zhu, 2104). Some studies (Wang et al, 2008;Ozbek et al, 2010;Wakchaure & Jha, 2011) have applied DEA in the bridge engineering and management domain. Wang et al (2008) used DEA along with the analytical hierarchy process and proposed a methodology to assess the bridge risk and decide the priority level for maintenance.…”

“…Ozbek et al (2010) applied DEA to measure the efficiency of several bridges in Virginia counties that need maintenance. Wakchaure & Jha (2011) presented a method using the DEA, which would help to select those bridges in need of maintenance management and to enhance the efficiency of the bridge management system. Therefore, all these studies showcase the implementation of the DEA concept in bridge engineering and management domains, such as bridge risk assessment and maintenance management.…”

“…Also, if the high flood level increases and comes parallel to the design HFL or FRL, the bridge might be closed for the traffic, affecting the bridge resilience score. However, according to Tanassoulis (2001), Ozbek et al (2010), and Wakchaure & Jha (2011) such variables could be used either by deducting from large values, taking the inverse, or treating them as the output variables. Therefore, this study uses inverse values of the bridge age, area, design HFL, and FRL as the input variables for the final evaluation process in DEA.…”

Data quality assessment of maintenance reporting procedures

“…Maintenance prioritization (Farhan & Fwa, 2009;Moazami et al, 2011;Taghipour et al, 2011) (Ouma et al, 2015) (Wakchaure & Jha, 2011) (Liu et al, 2012;Cafiso et al, 2002;Hankach et al, 2011;Trojan & Morais, 2012b) (Monte & de Almeida-Filho, 2016;de et al, 2015b) Resource Planning (Azadeh et al, 2013) Almeida et al, 2013) (Garmabaki et al, 2016;de Almeida., 2001;Liu & Frangopol, 2006) Maintenance Scheduling (Coulter et al, 2006;Eslami et al, 2014) ( Van et al, 2013) (Certa et al, 2013) (Almeida, A. T., 2012) Operational Level…”

A Decision Concept to the Historic Pedestrian Bridges Recovery Planning

“…Park et al [37] presented a prior ranking approach to the maintenance management of coastal bridges and composed of more reasonable approach studied on previous priority ranking approach to realize bridge maintenance. Wakchaure and Jha [38] developed an alternative approach of data envelopment analysis for scoring the efficiency of 14 selected bridges. Nielsen, Chattopadhyay, and Dhamodharan Raman [39] proposed a bridge life management decision model using degradation, defect initiation and growth, maintenance options, and relevant costs.…”