An Approach to Risk Quantification Based on Pseudo-Random Failure Rates

3rd IFAC Workshop on Advanced Maintenance Engineering, Services and Technology AMEST 2016: Biarritz, France, 19—21 October 2016. - IFAC-PapersOnLine, Volume 49, Issue 28, 2016, Pages 179-184The risk quantification is one of the most critical areas in asset management (AM). The relevant information from the traditional models can be shown in risk matrices that represent a static picture of the risk levels and are according to its frequency and its impact (consequences). These models are used in a wide spectrum of knowledge domains. In this paper, we describe a quantitative model using the reliability and failure probability (as frequency in our risk model), and the preventive and corrective costs (as consequences in our risk model). The challenge here will be the treatment of reliability based on failure rate values with different e random distributions (normal, triangular etc.) according to the available data. These possible values will enable the simulation of the behavior of the system in terms of reliability and, consequently, to use this information for making a risk based analysis. The traditional risk-cost-benefit models applied to maintenance usually provides an optimum for the time to apply a preventive task. But in this case, a time window is obtained showing minimum and maximum thresholds for the best time to apply the preventive maintenance task, together with other interesting statistics useful for the improvement of complex industrial asset management

Power consumption and gas dispersion in agitated vessels

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An overview

The efficient functioning of modern society depends on the smooth operation of many complex systems comprised of several pieces of equipment that provide a variety of products and services. These include transport systems (trains, buses, ferries, ships and aeroplanes), communication systems (television, telephone and computer networks), utilities (water, gas and electricity networks), manufacturing plants (to produce industrial products and consumer durables), processing plants (to extract and process minerals and oil), hospitals (to provide services) and banks (for financial transactions) to name a few. All equipment is unreliable in the sense that it degrades with age and/or usage and fails when it is no longer capable of delivering the products and services. When a complex system fails, the consequences can be dramatic. It can result in serious economic losses, affect humans and do serious damage to the environment as, for example, the crash of an aircraft in flight, the failure of a sewage processing plant or the collapse of a bridge