Abstract
In industry, spare equipments are often shared by many workplaces with identical equipments to assure the production rate required to fulfill delivery dates. These types of systems arc called "Maintenance Float Systems". The main objective of managers that deal with these types of systems is to assure the required capacity to deliver orders on time and at minimum cost. Not delivering on time has often important consequences; it call cause loss of costumer goodwill, loss of sales and call damage organization's image. Maintenance cost is the indicator more frequently used to configure maintenance float systems and to invest in maintenance workers or spare equipments. Once the system is configured, other performance indicators must be used to characterize and measure the efficiency of the system. Different improvement initiatives call be performed to enhance the performance of maintenance float systems: performing preventive maintenance actions, implementation of autonomous maintenance, improvement of equipments maintainability, increase of maintenance crews' efficiency etc. "Carrying out improvement based on facts" is a principle of Total Quality Management (TQM) in order to step to business excellence. It requires monitoring processes through performance measures. This work aims to characterize and highlight the differences and relationships between three types of performance measures-equipment availability, equipment utilization and workplace occupation, in the context of maintenance float system. Definitions and expressions of these three indicators are developed for maintenance float systems. The relationship between maintenance float systems efficiency and the referred indicators is shown. Other indicators are also proposed and compared with the first ones (number of standby equipments, queue length etc.).

Abstract
Proportional hazards modelling is a powerful technique which can be used to investigate the effects of various explanatory variables on the life length of equipment. In this paper the analysis of aircraft cargo door complaints is considered, as this can cause serious delay problems. Particular attention is given to the assumptions supporting the application of the model. Consideration is given to problems in the choice of the appropriate basic metric time, definition of covariates and adapting the methodologies to this particular problem. Emphasis is placed upon the validation of the results by attempting several different structures of the dependent variables. Copyright © 1989 John Wiley & Sons, Ltd.

Abstract
The aim of this paper is to illustrate primarily the suitability and secondly the ability of both PHM and ‘two-sample’ tests in answering problems in the reliability field. The findings stress the fact that ‘two-sample’ tests should be preferred for comparison purposes and PHM for modelling the behaviour of the equipment in the presence of various factors. Copyright © 1991 John Wiley & Sons, Ltd.

Abstract
Purpose - The purpose of this paper is to determine the state probabilities for a float system when overhauls are performed periodically. Design/methodology/approach - First, a model is developed to express the relationship between the rate of occurrence of failure and time interval between overhauls. Then, a methodology is defined to develop differential equations for each system state in order to calculate corresponding system state probabilities. Findings - Since it is considered that units requiring an overhaul stay in operation until replacement, the possibility of failure of those units has to be included. Then, the determination of system state probabilities has to be done iteratively. Practical implications - The methodology proposed in this paper enables comparison of different designs for a float system submitted to periodic overhauls through some different performance measures. System state probabilities can also be used to determine the idle time of units, which is essential to obtain the cost of production loss and, therefore, the system maintenance cost. Originality/value - This paper considers simultaneously three different factors that influence maintenance float system performance: the number of spare units and the number of maintenance crews (which mean minimising the downtime effect) and the overhaul frequency (which means decreasing the number of failures). © Emerald Group Publishing Limited.

Abstract
This paper is concerned with the use of simulation as a decision support tool in maintenance systems, specifically in MFS (Maintenance Float Systems). For this purpose and due to its high complexity, in this paper the authors propose a flexible way to develop typical MFS models, for any number of machines in the workstation, spare machines and maintenance crews. Arena simulation language is used to understand a specific MFS, create the corresponding MFS model and analyze most common performance measures.

Abstract
This paper is concerned with the use of simulation as a decision support tool in maintenance systems, specifically in MFS (Maintenance Float Systems). For this purpose and due to its high complexity, in this paper the authors explore and present a possible way to construct a MFS model using Arena simulation language, where some of the most common performance measures are identified, calculated and analysed. Nevertheless this paper would concentrate on the two most important performance measures in maintenance systems: system availability and maintenance total cost. As far as these two indicators are concerned, it was then quite clear that they assumed different behavior patterns, specially when using extreme values for periodic overhauls rates. In this respect, system availability proved to be a more sensitive parameter.