Complex systems have become ubiquitous and indispensable for society; telecommunication networks, computers, transporting vehicles, offshore structures, nuclear power plants, and electrical appliances are well known examples. Thus, the design of reliable systems and the determination of their availability are both very important tasks for managers and engineers, given that reliability and availability (R&A) have a strong relationship to other concepts such as quality and safety. However, these tasks are extremely difficult to achieve, due to the fact that current analytical methods can become too complicated, time consuming, inefficient or even inappropriate when dealing with real-life systems. Although different analytical approaches can be used to calculate the exact reliability of a time-dependent complex system, when the system is highly complex, such approaches can become extremely difficult. Similarly, problems arise when trying to determine the exact availability at a given target time for systems subject to maintenance policies. As some authors point out, in those situations only simulation techniques, such as Monte Carlo Simulation (MS), Discrete Event Simulation (DES) or Agent-Based Modeling and Simulation (ABMS) can be useful to obtain estimates for R&A parameters.

Thus, the main topic of this track would be the use of computer simulation-based techniques and algorithms to determine reliability and/or availability levels in complex systems and to support the improvement of these levels both at the design stage and during the system operating stage.

Overall objectives

• To identify and publish worldwide best practices regarding development and use of simulation-based algorithms and techniques in system R&A scenarios.
• To share theoretical or applied models and decision support systems that make use of simulation to estimate and to improve system R&A levels.
• To forecast emerging technologies and tendencies regarding the use of computer simulation to the R&A areas.
• To provide the academic community with a base text that could serve as a reference in industrial engineering, operations research and computer sciences undergraduate/graduate courses.
• To propose hybrid approaches, which combine simulation and analytical techniques, to develop efficient methodologies oriented to solve problems related to R&A of real-life systems.