22nd Congress of International Council of the Aeronautical Sciences, Harrogate, UK, 28 August - 1st September, 2000
Paper ICAS 2000-6.2.1

MAINTENANCE OPTIMISATION OF A DIGITAL ENGINE CONTROL SYSTEM WITH LIMIT FAILURE RATE CONSTRAIN

M. Boussemart (1), T. Bickard (1), N. Limnios (2)
(1) Snecma Control Systems, France; (2) Université de Technologie de Compiègne, France

Keywords: Null

In this paper, we consider error tolerant systems that remain fail-operational when affected by some identified faults. The idea is to use this feature to enhance the maintenance procedures for safety-critical systems having a stochastic failure scheme (e.g. electric and electronic control components) when they are embedded in a larger system composed of lifelimited parts requiring periodical overhaul (e.g. a jet engine). The current certification objectives require the manufacturer to show that the system’s asymptotic failure rate is bounded to a prescribed value. One major constrain when optimizing the maintenance cost is to fulfil this certification objective. The paper starts with an unambiguous redefinition of often misused probabilistic terms such as failure rate and asymptotic failure rate. Then some theoretical results are given to compute the associated figure with continuous and discrete Markov models. These models are handled using studies about positive matrices, which calls for the Frobenius spectral analysis. In a second part, some examples of electronic control system architecture are given with some proposed associated failure model. Distributed architectures are particularly detailed because they are suspected to be well adapted to provide extended time limited dispatch capabilities due to their multiple reconfiguration capability. The optimization of economical criteria is then introduced. Controlled Markov models are shown to be well suited to solving maintenance problems. These systems can be described as a finite state machine. Each state transition is associated with a decision making : dispatch or repair. The cost of each alternative is evaluated considering the original state and the time since last maintenance action. Further decisions are oriented by all past actions. The optimization consists of computing a matrix linking the decision probability with the state. The optimization criterion is the mean operating cost considered over the up periods. The rationales of the choice for that economical criterion are given. The optimization problem is then turned into a linear optimization scheme, which is easy to solve with a simplex algorithm. For our real problem, facing a too large number of unknowns, an other approach need to be developed. Finally, a complete and easy to figure out example is given. Our method is applied on a triple modular redundant computer but also on a distributed architecture. The missions are supposed to be of constant duration. The state is observed at each mission end and the probability figures are computed, providing a help in taking the decision to repair or to dispatch by indicating what is the best action to minimize the operating cost on the long term.

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