Purpose -Studying the availability of medical equipment based on various maintenance types has been a major concern for hospitals. Most of the methodologies used are empirical and few are based on mathematical modelling. The objective of this paper is to present a mathematical maintenance model that analyses the effect of maintenance on the survival probability of medical equipment based on maintenance history and age of that equipment. Design/methodology/approach -A global model is proposed to measure the probability of equipment being available using real data extracted from maintenance history of infusion pumps and ventilators and analysed using Matlab. To confirm the validity of the developed model, the survival analysis approach is used to develop a model that measures the survival of equipment as a function of maintenance and age of equipment. The method is first tested using simulated data and the findings confirm the validity of the proposed approach. Findings -The analysis using survival approach reveals that conducting preventive maintenance (PM) on the selected medical equipment had an impact on survival of equipment. However, the manufacturer's recommended PM intervals do not correlate to the failure rate encountered. This will contribute to the debate on PM manufacturer's recommended intervals and might lead to the revision of maintenance strategies implemented by hospitals and clinical engineering (CE) practitioners. Research limitations/implications -Although the data collected for the infusion pumps were quite sufficient, that collected for the ventilators were more limited. The major difficulty is that of the availability of historical maintenance data and the effect of user errors may cause uncertainty in the analysis. A closer collaboration with the medical professional should facilitate the recording and access to such information. Practical implications -The use of mathematical modelling to analyse the effect of maintenance on the survival of medical equipment is a beneficial tool that is not exploited in the medical equipment industry. It will provide CE practitioners with scientific tool to analyse the effect of PM on the survival of medical equipment. Originality/value -This paper presents a mathematical approach to analyse the effect of maintenance on the survival of medical equipment, which is crucial in the assessment of maintenance strategies implemented in the medical equipment industry.

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This paper proposes a mathematical maintenance model that analyses the effect of maintenance on the survival probability of medical equipment based on maintenance history and age of the equipment. The proposed model is simulated in Scilab using real data extracted from maintenance history of anaesthesia machine from Draeger. The analysis using survival approach reveals that conducting preventive maintenance on the selected medical equipment had a positive impact on survival of equipment. The model is then used to analyse the cost of maintenance scenarios, and an appropriate scenario is proposed for anaesthesia machine. A new failure-cost model is developed, which may be used to calculate the number of failures of equipment and the annual maintenance cost. The proposed models may be used as a planning tool for selecting maintenance strategies for various medical equipments.In many applications, equipment failures may be divided into two categories, random failures (unpredictable) and those due to deterioration (ageing). The processes in which medical equipment may fail may be represented by probabilistic mathematical models and not by deterministic models. 9 It is assumed that medical equipment follows a constant failure rate, and the chance of a failure occurring in any future at time interval is the same. A constant failure rate (or hazard rate) model is a special case where the hazard function, associated to the probability of failure in a future at time if the device is still working at the beginning of time t, is constant.According to Troyer, 7 the exponential survival and the Weibull distribution are the most widely used reliability model machines, and the exponential survival is the most basic one with the constant failure rate or the flat section of the bathtub curve. Troyer 7 further claims that most industrial machines spend most of their lives in the constant failure rate (exponential), and Tarpey 17 indicated that most electronic components do not ware out, and their failure times are accurately described by an exponential distribution.A. KHALAF ET AL.This confirms the results because, for short periods, the probability of failure is governed only by PM, whereas for long periods, the effect of PM is small compared with CM. Failure-cost model verificationThe failure model in Equation (5) is simulated in Scilab, and a comparison is obtained from the closed-form expression to that obtained by simulation. Figure 8 in the following text shows the number of failures using the simulation and analytical methods for the anaesthesia machine. It may be noticed that the values obtained fit very well. Figure 8. Number of failures PA from simulation and analytical results A. KHALAF ET AL.

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