Dependability Modelling and Sensitivity Analysis of Scheduled Maintenance Systems

Abstract

Abstract. In this paper we present a new modelling approach for dependability evaluation and sensitivity analysis of Scheduled Maintenance Systems, based on a Deterministic and Stochastic Petri Net approach. The DSPN approach offers significant advantages in terms of easiness and clearness of modelling with respect to the existing Markov chain based tools, drastically limiting the amount of user-assistance needed to define the model. At the same time, these improved modelling capabilities do not result in additional computational costs. Indeed, the evaluation of the DSPN model of SMS is supported by an efficient and fully automatable analytical solution technique for the time-dependent marking occupation probabilities. Moreover, the existence of such explicit analytical solution allows to obtain the sensitivity functions of the dependability measures with respect to the variation of the parameter values. These sensitivity functions can be conveniently employed to analytically evaluate the effects that parameter variations have on the measures of interest. Systems with Multiple Phases and Multiple MissionsWith the increasing complexity and automation encountered in systems of the nuclear, aerospace, transportation, electronic, and many other industrial fields, the deployment of processing systems in charge of performing a multiplicity of different control and computational activities is becoming common practice. Very often, the system and its external environment can be altered during the operation, in a way that the behaviour during a time interval can be completely different from that within other periods.The operational scenario devised for the Scheduled Maintenance System (SMS) problem is a typical one in the context of the on-board aeroplane control systems. SMS are to be used during their life-time for multiple missions. The system is run for a finite number of missions, and then it has to pass a maintenance check. Such maintenance can be more or less extensive and accurate. Typically, it is the case that after a prefixed number of missions the system is completely checked, so that all its components are as good as new ones after that. Moreover, other kinds of maintenance actions are usually performed between two major checks. For instance, some highly critical components could be checked and possibly repaired after each mission, and

Tuning of Database Audits to Improve Scheduled Maintenance in Communication Systems

“…In performing the system analysis and evaluation, we consider that the system works through missions of predefined duration [1]. To our purpose, two measures have been identified as the most sensible indicators, and the developed models have been tailored to them.…”

“…Contrasting, but correlated, issues have to be coped with; namely: high reliability/availability calls for frequent, deep-checking audits, while good performance in terms of accomplished services suffers from the execution power devoted to audits. We follow an analytical approach, essentially based on Deterministic and Stochastic Petri Nets (DSPN) [1,7]. Analytical models, which capture the behaviour of the database in presence of scheduled maintenance, are defined and evaluated, in terms of identified dependability and performance measures.…”

Efficient solution of extended Multiple-Phased Systems

“…Also called Phased Mission System (PMS) in other works, as in [2], since they can easily describe systems in which the behaviour is described as a mission, structured into multiple phases, each described by a different duration, system configuration, desired task, etc. MPS have been shown to be useful also in modelling systems with scheduled maintenance [3] (Scheduled Maintenance Systems -SMS). In a MPS, the standard question is to compute the reliability of the system, i.e.…”

“…In a MPS, the standard question is to compute the reliability of the system, i.e. the probability that the system survives the mission, but optimization also plays a role [4], especially for SMS to determine the best maintenance policy, as well as sensitivity analysis [3,5] to allow to reason about the structure of the mission and their parameters.…”

Modeling and Analysis of a Scheduled Maintenance System: a DSPN Approach

“…From the modelling point of view, a system under scheduled maintenance program (SMS) can be seen as a multiple phased system (MPS). Each phase is associated to the configuration of the system during some time interval (the part of the system being actually maintained or operational [1]), while the scheduled maintenance program drives phase changes. The behaviour of the system in each time period (phase) is governed by a complex stochastic process accounting for the simultaneous presence of the individual components failure processes and of maintenance actions, which depend on the phase performed.…”