REVIMA is a virtual reality system for maintainability simulation in Aeronautics. It comprises both hardware and software developments, plus system integration. REVIMA required the design of a new haptic system. It is used both to track hand movements and to return force feedback that provides the sensation of working with a physical mock-up. The main software modules are: image generation, collision detection and control. System integration is based on two LAN connected PCs that share the different tasks and data.The visualization module has been built using low-cost graphic systems, and we have thoroughly analysed this problem to achieve a drawing frame rate acceptable for simulation analysis. The models comprise more than two thousand different elements that require about two million polygons to describe their shapes. Different organization strategies have been tested in order to achieve the real simulation goal. We also present the different visualization algorithms we have used.

Configuration is a complex task generally involving varying measures of constraint satisfaction, optimization, and the management of soft constraints. Although many successful systems have been developed, these are often difficult to maintain and to generalize in rapidly changing domains. In this paper, we consider building intelligent knowledge-based systems with maintainability well to the fore in our requirements for such systems. We introduce two case studies: the initial proof of concept, which was in the domain of computer configuration, and a further field-tested study, the configuration of compressors. Central to our approach is the use of the proof planning technique, and the clean separation of different kinds of knowledge: factual, heuristic, and strategic.

In the present paper we study three aspects in the theory of non-homogeneous Markov systems under the continuous-time formulation. Firstly, the relationship between stability and quasi-stationarity is investigated and conditions are provided for a quasi-stationary structure to be stable. Secondly, the concept of asymptotic attainability is studied and the possible regions of asymptotically attainable structures are determined. Finally, the cyclic case is considered, where it is shown that for a system in a periodic environment, the relative structure converges to a periodic vector, independently of the initial distribution. Two numerical examples illustrate the above theoretical results.

Our concern is with a particular problem which arises in connection with a discrete-time Markov chain model for a graded manpower system. In this model, the members of an organisation are classified into distinct classes. As time passes, they move from one class to another, or to the outside world, in a random way governed by fixed transition probabilities. In this paper, the emphasis is placed on evaluating exact values of the probabilities of attaining and maintaining a structure.

In an earlier paper (Bartholomew (1977)) the problem of maintaining a grade (or age) structure by controlling the recruitment flows was discussed. Here we carry out a parallel analysis for the case where control is by promotion. We show how to calculate the probability that a structure can be maintained and investigate the performance of several strategies for keeping a structure as near as possible to that desired. As before, the results demonstrate the limitations of a deterministic analysis of the problem.

Grade and age structures in manpower systems are often far from ideal. This fact raises the question of how the flows of people — and particularly the recruitment flow — should be controlled in order to attain and maintain a more desirable structure. The problem has received considerable attention from a deterministic point of view. This paper adopts a stochastic approach to the study of maintainability and shows, among other things, that the problem is more subtle than the deterministic analysis suggests.