A bibliometric analysis of process system failure and reliability literature

Amin, Md. Tanjin; Khan, Faisal; Zuo, Ming J.

doi:10.1016/j.engfailanal.2019.104152

Cited by 23 publications

(8 citation statements)

References 167 publications

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“…To achieve robust validation, data from at least one (preferably more than one) industry partner are required. However, a recent review of process system failure and reliability literature reports that "collaborative works between industry and academia are observed to be rare" (Amin et al, 2019) and we have shown elsewhere that few published models in this field are validated using industry data (Webb et al, 2020). We suggest that datasharing in the field of EAM is sufficiently problematic as to be reducing the progress of the field by restricting researchers' access to data required to develop effective models for asset life prediction and to improve maintenance management practice.…”

Section: Introductionmentioning

confidence: 99%

DRAT: Data risk assessment tool for university–industry collaborations

Sikorska

Bradley

Hodkiewicz

et al. 2020

DCE

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For research in the fields of engineering asset management (EAM) and system health, relevant data resides in the information systems of the asset owners, typically industrial corporations or government bodies. For academics to access EAM data sets for research purposes can be a difficult and time-consuming task. To facilitate a more consistent approach toward releasing asset-related data, we have developed a data risk assessment tool (DRAT). This tool evaluates and suggests controls to manage, risks associated with the release of EAM datasets to academic entities for research purposes. Factors considered in developing the tool include issues such as where accountability for approval sits in organizations, what affects an individual manager’s willingness to approve release, and how trust between universities and industry can be established and damaged. This paper describes the design of the DRAT tool and demonstrates its use on case studies provided by EAM owners for past research projects. The DRAT tool is currently being used to manage the data release process in a government-industry-university research partnership.

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Section: Introductionmentioning

confidence: 99%

DRAT: Data risk assessment tool for university–industry collaborations

Sikorska

Bradley

Hodkiewicz

et al. 2020

DCE

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“…Reliability is a function which allows predicting the operating time of a system by calculating the failure probability of its subsystems or components [14], [15]. [16] mentions that reliability is an important property for all systems, as it allows to define how long an object can function during different operating conditions such as temperature, speed, loading and among others.…”

Section: B Reliabilitymentioning

confidence: 99%

“…[16] mentions that reliability is an important property for all systems, as it allows to define how long an object can function during different operating conditions such as temperature, speed, loading and among others. Based on this, if a good analysis of the product's reliability is performed, it is guaranteed that the components or systems will operate at the desired level during their life cycle [14], [17].…”

Section: B Reliabilitymentioning

confidence: 99%

“…Safety and reliability are connected because the failure of a component or of a subsystem can lead the failure to a complete system and it may put in risk the consumer's safety. Therefore, the low probability of failure and the long operation of a product are essential requirements in some products such as airplanes, for example [14], [17].…”

Section: B Reliabilitymentioning

confidence: 99%

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Evaluation of Qualitative Accelerated Tests Practices in Product Development Process: A Computer Simulation

Rocha

Oliveira

Veroneze

2021

EJENG

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— Reliability is an essential item for the product development phase, as it is from estimated values are obtained about how the product will behave and, consequently, about modes of design flaws and weaknesses. In short, these responses are important to offer to the market high quality products, in addition to providing safety to the customer. In this work, a product was proposed where its design was based on research on how its shape should be and three different raw materials were chosen to be applied to the product and, with the simulation, it was possible to discover the weaknesses and points of improvement and which material best suited the proposed product.

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“…Also, based on the bibliometric study of Ref. (39), most of the industrial documents are presented mainly in the conferences, and more collaboration between academia and industry is required in publishing industrial works. This paper is based on an industrial work and uses a multitude of exemplary SCS components to provide a SIL analysis in an academic way.…”

Section: Introductionmentioning

confidence: 99%

SIL analysis of subsea control system components based on a typical OREDA database

Mahmoudi

2021

Quality & Reliability Eng

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Proper performance evaluation of subsea system components is of high significance for reliable operation and remote monitoring or the replacement of the components before the occurrence of any failure. As a part of subsea systems, subsea control system (SCS) plays a key role in accomplishing a reliable performance. Hence, achieving knowledge of the components' failure rates is highly important in the safety analysis of SCS. To the author's knowledge, limited work is done on the safety analysis of SCS using failure rates for a multitude of components. Also, the number of research papers that are based on industrial works is restricted. Hence, this paper aims to provide a noticeable contribution in fulfilling the referred gap. For this purpose, a safety integrity-level (SIL) analysis is proposed based on a typical OREDA database. In the implementation of the proposed SIL, a failure mode classification table is provided for a selection of SCS components. This is followed by the estimation of several parameters, such as the total time in service, as well as obtaining the values of critical failure rates.The analysis indicates that signal failure is the failure mode occurring more than the other ones. Also, the subsea electronic module yields the highest value of critical failure rates. Besides, a comparison of parameter values is provided for two different versions of the utilized database.

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A bibliometric analysis of process system failure and reliability literature

Cited by 23 publications

References 167 publications

DRAT: Data risk assessment tool for university–industry collaborations

DRAT: Data risk assessment tool for university–industry collaborations

Evaluation of Qualitative Accelerated Tests Practices in Product Development Process: A Computer Simulation

SIL analysis of subsea control system components based on a typical OREDA database

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