Application of capital replacement models with finite planning horizons

Capital replacement models with finite planning horizons can be used to model replacement policies in complex operational contexts. They may also be used to investigate the cost consequences of technological change. This paper reviews the application of these models in various such contexts. We also compare fixed planning horizon models with variable planning horizon models. As technological change, and hence the requirement of users and customers, often drives replacement decisions rather than cost optimality, the modelling focuses not only on obtaining optimal policies, but also on determining the increased cost of sub-optimal policies. The role of penalty cost formulations is also discussed. These ideas are illustrated using a number of case histories from medicine and transport

A robust replacement model: medical equipment

Perceived shortcomings in the applicability of capital equipment replacement modelling, identified in a 1987 survey within the UK are addressed and a robust replacement model formulated. First, however, a comparison between the 1987 survey and a similar 1988 survey undertaken within the USA is made and explanations for apparent differences in conclusions are presented. A replacement model is then developed in the context of medical equipment where factors such as service and risk play a role in replacement decision-making. A mechanism for quantitatively allowing for qualitative and for political type factors within a short time horizon replacement model is introduced by means of a penalty factor. A case example is presented for medical ventilator equipment

A robust replacement model: medical equipment

Perceived shortcomings in the applicability of capital equipment replacement modelling, identified in a 1987 survey within the UK are addressed and a robust replacement model formulated. First, however, a comparison between the 1987 survey and a similar 1988 survey undertaken within the USA is made and explanations for apparent differences in conclusions are presented. A replacement model is then developed in the context of medical equipment where factors such as service and risk play a role in replacement decision-making. A mechanism for quantitatively allowing for qualitative and for political type factors within a short time horizon replacement model is introduced by means of a penalty factor. A case example is presented for medical ventilator equipment

On the impact of optimization models in maintenance decision making: the state of the art

In this note we present a general framework for optimization of replacement times. It covers a number of models, including various age and block replacement models, and allows a uniform analysis for all these models. A relation to the marginal cost concept is described

Maintenance, replacement and reliability : editorial

No abstract