Article

O.R. modelling of the deterioration and maintenance of concrete structures

European Journal of Operational Research (Impact Factor: 2.04). 02/1997; 99(3):619-631. DOI: 10.1016/S0377-2217(96)00325-6
Source: RePEc

ABSTRACT This paper reports on a collaborative venture between operational researchers and civil engineers over 3 years. The main objectives were to collect and publish data on the observed rates of deterioration of particular defect types in a large number of concrete bridges, and to develop predictive mathematical models that relate inspection frequency to maintenance costs. The motivation was in part associated with the prototype modelling paper for inspection practices of major concrete structures, Christer (1988). The paper reports on the analysis of data collected and the estimation of deterioration using the concept of delay time. The two phase delay time model is extended to an extra phase in order to model the process of cracking and spalling in concrete. Maximum likelihood techniques are used to estimate modelling parameters and an appropriate test of fit is carried out. Cost based models are then formulated to predict the cost effects of maintenance and inspection decision options. The cost model is applied first to an element, and then to an aggregate number of component types to produce a cost model for maintenance of a bridge or set of bridges.

0 Bookmarks
 · 
50 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We focus on the analytical modeling of a condition-based inspection/replacement policy for a stochastically and continuously deteriorating single-unit system. We consider both the replacement threshold and the inspection schedule as decision variables for this maintenance problem and we propose to implement the maintenance policy using a multi-level control-limit rule.In order to assess the performance of the proposed maintenance policy and to minimize the long run expected maintenance cost per unit time, a mathematical model for the maintained system cost is derived, supported by the existence of a stationary law for the maintained system state.Numerical experiments illustrate the performance of the proposed policy and confirm that the maintenance cost rate on an infinite horizon can be minimized by a joint optimization of the maintenance structure thresholds, or equivalently by a joint optimization of a system replacement threshold and the aperiodic inspection schedule.
    Reliability Engineering [?] System Safety 05/2002; · 1.90 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The current practice of maintenance on fishing vessels varies according to the operating policies of the owner/operator. On most occasions, the crew does not carry out regular maintenance while at sea. As such, all maintenance work is completed while the vessel is at the discharging port. The time between discharge ports can be as long as three to six months, which allows for failures on the machinery propagating and leading to a catastrophic breakdown. Discusses the possibility of avoiding such events by means of implementing an inspection regime based on the delay-time concept. Operating and failure data that have been gathered from a fishing vessel are used to demonstrate the proposed approach. The outcome of the model is incorporated into the existing maintenance policy of the fishing vessel to assess its effectiveness.
    Journal of Quality in Maintenance Engineering 05/2001; 7(2):118-128.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper we discuss the state of the art in applications of maintenance optimisation models. After giving a short introduction to the area, we consider several ways in which models may be used to optimise maintenance, such as case studies, operational and strategic decision support systems, and give examples of each of them. Next we discuss several areas where the models have been applied successfully. These include civil structure and aeroplane maintenance. From a comparative point of view, we discuss future prospects.
    Reliability Engineering [?] System Safety 02/1997; · 1.90 Impact Factor