A risk-based availability estimation using Markov method

Abstract

Purpose – Asset intensive process industries are under immense pressure to achieve promised return on investments and production targets. This can be accomplished by ensuring the highest level of availability, reliability and utilization of the critical equipment in processing facilities. In order to achieve designed availability, asset characterization and maintainability play a vital role. The most appropriate and effective way to characterize the assets in a processing facility is based on risk and consequence of failure. The paper aims to discuss these issues. Design/methodology/approach – In this research, a risk-based stochastic modeling approach using a Markov decision process is investigated to assess a processing unit's availability, which is referred as the risk-based availability Markov model (RBAMM). RBAMM will not only provide a realistic and effective way to identify critical assets in a plant but also a method to estimate availability for efficient planning purposes and resource optimization. Findings – A unique risk matrix and methodology is proposed to determine the critical equipment with direct impact on the availability, reliability and safety of the process. A functional block diagram is then developed using critical equipment to perform efficient modeling. A Markov process is utilized to establish state diagrams and create steady-state equations to calculate the availability of the process. RBAMM is applied to natural gas absorption process to validate the proposed methodology. In the conclusion, other benefits and limitations of the proposed methodology are discussed. Originality/value – A new risk-based methodology integrated with Markov model application of the methodology is demonstrated using a real-life application.

Performance modeling of the serial processes in refining system of a sugar plant using RAMD analysis

“…Adhikary et al (2012) investigated the reliability, availability and maintainability characteristics of a 210 MW coal-fired thermal power plant. Ahmed et al (2014) developed a risk-based stochastic model using a Markov decision process to assess availability of a processing unit, which is referred as the riskbased availability Markov model (RBAMM). Barabady concluded that high reliability is desirable to reduce the maintenance costs of systems.…”

Risk-based availability modelling and reputation management on fault tolerant cloud computing systems

“…Distributed computing has assisted the frequently developing storing and information handling desires, be that as it may, it has likewise offered ascend to various risks. One of the fundamental destinations of an effective maintenance is to maximise the accessibility of resources in a cloud environment (Ahmed et al, 2014). Accessibility is the capability of a component to play out its required capacity at a given time or over an expressed timeframe when worked and kept up in a recommended way (Khan et al, 2008).…”

“…The risks emerge because of the different variables, for example, the area of the data centres, farms, information isolation, information trustworthiness, foundation and absence of information about the administering arrangements (Mosa et al, 2012). In a distributed computing circumstance, the resources are used when required and this is depended upon to change over into decreased costs of support and adaptable versatility (Ahmed et al, 2014). To prepare a client demand, the provision provider relaxes on the possessions to be used for the specific job and when these resources should be discharged (Mani and Mahendran, 2017).…”

Markov modeling and reliability analysis of urea synthesis system of a fertilizer plant

“…Kiilumen and Frisk (2014) developed a method to examine the long-term reliability of an anisotropic conductive adhesive (ACA)-attached polyethylene terephthalate (PET) flex-on-board (FOB) assembly for industrial application used in harsh environments. Ahmed et al (2014) provided a risk-based stochastic modeling approach using a Markov decision process to assess the availability of a processing unit, which is referred to as the risk-based availability Markov model (RBAMM). discussed the performance analysis of the furnace draft air cycle of a thermal power plant.…”