Managing quality &amp; reliability with less information

Ganesh, N.; Lü, Yuan; Ouden, Elke den; Brombacher, Aarnout

doi:10.1109/rams.2005.1408392

Cited by 1 publication

(1 citation statement)

References 3 publications

(3 reference statements)

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“…Lu et al. have developed a useful tool, the reliability and quality matrix, to mitigate the effect of uncertainty through the fuzziness of the initial dataset 45,46 …”

Section: Literature Reviewmentioning

confidence: 99%

A new hybrid MCDM approach for RPN evaluation for a medical device prototype

Pintelon

Nardo

Murino

et al. 2021

Quality & Reliability Eng

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The Failure Mode and Effect Analysis (FMEA) is a useful instrument born in the aerospace industry and widely used to improve a process or product's efficiency. Over the years, this instrument has been adopted in increasingly different contexts, such as HealthCare. This paper proposes an approach aimed at improving the defects typical of the classic FMEA in the design phase, that is, in a scenario full of uncertainties and with little information available, using a new hybrid Multiple‐criteria decision‐making (MCDM) method in order to obtain a priority index more performant than Risk Priority Number (RPN). In the proposed method, the three assessment criteria have a different weighting in the index's final computation, differently from the classical RPN. These weights are obtained with a scientific technique, thus avoiding that excessive subjectivity influences the final result. A more efficient priority index is obtained through a new hybrid approach that solves some classical RPN gaps. A case study concerning an endoscope Ear Nose Throat Entropy (ENT) prototype is examined to illustrate the proposed method. FMEA analysis in HealthCare is increasingly used for its flexibility and reliability. This study focuses on using new techniques to eliminate certain defects or exploit some qualities better. The use of a robust and elastic innovative MCDM method to calculate a new priority index and a scientific technique to obtain the weight of the selection are the interesting insights proposed in this paper.

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“…Lu et al. have developed a useful tool, the reliability and quality matrix, to mitigate the effect of uncertainty through the fuzziness of the initial dataset 45,46 …”

Section: Literature Reviewmentioning

confidence: 99%