Abstract
During construction operations, fleet management aims at maximizing the uptime and efficiency of construction machinery while also minimizing the cost of ownership through lifecycle planning and management. In the deterministic approach, the theory suggests that one type of machinery is considered to be critical. However, taking into account the real circumstances under which projects are performed with issues such as machine reliability, worker performance, and/or errors in estimating the scope of work, it is evident that there are significant limitations to the existing approach. Hence, to address this issue, uncertainty in fleet productivity is modelled with fuzzy set theory. In this context, the notion of composite criticality under which the productivity of a fleet depends on more than one type of machinery because of the fluctuations of the individual productivities is introduced. To this purpose, a simple case study is presented to illustrate this concept. It is concluded that this approach leads to a better understanding of the estimation of activity duration and cost estimation which in turn means better project scheduling and financial planning.
Highlights
In construction operations project managers are faced with the task of completing activities under multiple constraints while ensuring the optimal use of available machinery
Construction equipment fleet management involves a variety of functions including machine maintenance, safety audits, GPS tracking, optimal fleet composition, cost tracking, fuel consumption monitoring and operator training
For many years the deterministic approach has dominated the methodological approach to the estimations of machine productivity and fleet composition
Summary
In construction operations project managers are faced with the task of completing activities under multiple constraints while ensuring the optimal use of available machinery. In this context, construction equipment fleet management involves a variety of functions including machine maintenance, safety audits, GPS tracking, optimal fleet composition, cost tracking, fuel consumption monitoring and operator training. The study of a fleet of machinery in which there is uncertainty in the productivity of its individual components poses a significant challenge. The purpose of this paper is to apply a fuzzy set theory to examine issues of uncertainty and imprecision in machinery fleet composition. The conclusions and possibilities for future research are presented
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