Reliability Evaluation and Risk Based Maintenance in a Process Plant

Kiran, S. Harish; Kumar, Kailash; Sreejith, B.; Muralidharan, M.

doi:10.1016/j.protcy.2016.05.117

Cited by 29 publications

(16 citation statements)

References 6 publications

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“…Risk-based maintenance (RBM) methodology provides a tool for maintenance planning and decision making to reduce the probability of failure of equipment and the consequences of failure (Arunraj and Maiti, 2007; Kiran et al , 2016). RBM methodologies can either be classified as quantitative or qualitative.…”

Section: Maintenance Framework Methodologies and Tools For Marine Mechanical Systemsmentioning

confidence: 99%

Maintenance practices and parameters for marine mechanical systems: a review

Kimera

Nangolo

2019

JQME

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Purpose The purpose of this paper is to review maintenance practices, tools and parameters for marine mechanical systems that can be classified as plant, machinery and equipment (PME). It provides an insight for the maintenance crew on which maintenance parameters and practices are critical for a given PME systems. Design/methodology/approach The review paper characterizes the various maintenance parameters and maintenance practices used onshore and offshore for PME and identifies the possible gaps. Findings A variety of maintenance techniques are being used in the marine industry such as corrective maintenance, preventive maintenance and condition-based maintenance. As marine vehicles (MV) get older, the most important maintenance parameters become maintenance costs, reliability and safety. Maintenance models that have been developed in line with marine mechanical systems have been validated using a single system, whose outcome could be different if another PME system is used for validation. Research limitations/implications There is a limited literature on MV maintenance parameters and maintenance characterization regarding mechanical systems. The maintenance practices or strategies of marine mechanical systems should be based on maintenance parameters that suit the marine industry for a given PME. Originality/value Based on the available literature, the paper provides a variety of maintenance framework, parameters and practices for marine mechanical systems. The paper further gives an insight on what maintenance parameters, strategies and platforms are given preference in the shipping industry.

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Section: Maintenance Framework Methodologies and Tools For Marine Mechanical Systemsmentioning

confidence: 99%

Maintenance practices and parameters for marine mechanical systems: a review

Kimera

Nangolo

2019

JQME

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“…To optimize different maintenance actions and to decide maintenance strategies and to minimize the operational costs and cleaning costs of the biomass boiler, a dynamic programming algorithm is developed (Agarwal and Suhane, 2017;Karel et al, 2017). Kiran et al (2016) proposed and applied a model to form an optimum maintenance schedule for improving plant availability in the process plant. Arjunwadkar et al (2016) investigated several major operational and performance-related problems, such as agglomeration, gas refluxation, back-sifting, emission control and bed temperature control of circulating fluidized bed boiler (CFB) components.…”

Section: Literature Surveymentioning

confidence: 99%

Reliability analysis of a steam boiler system by expert judgment method and best-fit failure model method: a new approach

Patil¹,

Bewoor

2020

IJQRM

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PurposeIndia's textile industries play a vital role in the Indian economy. These industries consume the highest thermal energy (steam power). The demand of the steam in process industries is increasing rapidly, and this demand can be met by increasing the capacity utilization of steam boilers. The purpose of this paper is to present a new approach for reliability analysis by expert judgment method.Design/methodology/approachA lack of adequate life data is one of the biggest challenge in the reliability analysis of mechanical systems. This research provides an expert judgment approach for assessing the boiler's reliability characteristics. For this purpose, opinions of experts on time to failure and time to repair data were elicited in the form of statistical distributions. In this work, reliability analysis of the boiler system is carried out by expert judgment method and by using best-fit failure model. The system reliability along with preventive maintenance intervals of all components is also evaluated.FindingsIt is observed that the reliability analysis results obtained by expert judgment method and best-fit failure model method indicate that there are no significant differences. Therefore, in case when insufficient data are available, the expert judgment method can be effectively used. The analysis shows that the feedwater tank, feedwater pump, supply water temperature sensor, strainer, return water temperature sensor, condensate filter, mechanical dust collector, coal crusher and fusible plug are identified as critical components from a reliability perspective, and preventive maintenance strategy is suggested for these components.Originality/valueIn this research paper, a system reliability model by the expert judgment method is developed, and it can be effectively used where insufficient failure data are available. This paper is useful for the comparative evaluation of reliability characteristics of a boiler system by expert judgment method and best-fit failure model method.

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“…This is necessary for maintenance to take place at the right time, both technically, economically and safely. The expectation of maintenance is high reliability by maximizing the life of the systems/components and the effective utilization of maintenance costs [11][12][13][14][15] .…”

Section: Pendahuluanmentioning

confidence: 99%

“…Having known the exponential distribution parameter values λ, then the next step is to determine the functions of the distribution of da-mage, and reliability functions. Functionality of damage distribution and reliability functions for JE-01 (AP01-02) components [11][12] .…”

Section: Estimated Exponential Distribution Parametersmentioning

confidence: 99%

Reliability Analysis for Critical Components on the RSG-Gas Primary Cooling System

Hartini¹,

Susmikanti

2018

sigma

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RELIABILITY ANALYSIS FOR CRITICAL COMPONENTS IN PRIMARY RSG-GAS COOLING SYSTEM. Reliability is the probability that a system will function normally when it is used for the desired time period under specific operating conditions. This study aims to analyze the reliability, distribution function of damage and rate of damage by using the frequency data of damage, downtime and time data between the damage of each component on the primary cooling system RSG- GAS. The methodology used is the Test of damage distribution estimated as an exponential distribution. Test the exponential distribution using the Bartlett test. Further estimation of data distribution parameters. Based on the parameters of the data distribution, the reliability and rate of damage can be calculated for the critical component of the primary cooling system. Damage data is obtained from maintenance data for core 70 until 88 (2010-2015). The results showed that in the primary cooling system the highest failure occurred for component JE-01 (AP01-02) with downtime = 112 (day) and failure frequency presentation = 75%. The failure rate (λ) of 0.000215438 with the reliability value for the last year amounted to 99.83%. Keywords: Downtime, Damage frequency, Reliability, maintenance, RSG-GAS

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Reliability Evaluation and Risk Based Maintenance in a Process Plant

Cited by 29 publications

References 6 publications

Maintenance practices and parameters for marine mechanical systems: a review

Maintenance practices and parameters for marine mechanical systems: a review

Reliability analysis of a steam boiler system by expert judgment method and best-fit failure model method: a new approach

Reliability Analysis for Critical Components on the RSG-Gas Primary Cooling System

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