Implementation of FMEA to improve the reliability of GEO satellite payload

Mozaffari, Fatemeh; Eidi, A.; Mohammadi, Leila; Alavi, Zahrasadat

doi:10.1109/rams.2013.6517679

Cited by 7 publications

(2 citation statements)

References 2 publications

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“…(to Braglia et al (2003), FMEA characterize as an alternative multi-attribute decision-making approach for prioritizing risk. Mozaffari et al (2013) . failure modes and effects analysis (FMEA) has applied for the design of geo satellite application, which uploads FMEA techniques to analyze the risk.…”

Section: Literature Reviewmentioning

confidence: 99%

Case Study: Risk Assessment of Indian Pulse processing firms using FMEA Techniques – Evidence from selected states of India

Sahu¹,

Arora²

2022

Journal of Pharmaceutical Negative Results

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The pulse value chain played significant role in agriculture and other industry sector such as food , pharma industry. The pulse value chain consists of sequences of business activities that perform significant activities, from primary production transformation into the final product to marketing for final consumption to the consumer. Pulse value chain develops different framework structures for developing competitive business strategy development to identify the significant constraints in a compressive manner. However, pulse processing firms face many risks, i.e., production risk, operation risk, supply risk, etc., which hampers the growth of these firms. The paper aims to identify pulse processing firms' risk factors and measure the severity of the risk. The risk assessment of pulses processing firms creates the opportunity for continuous quality improvement of the pulse value chain, and their performance also develops quality up gradation of pulse processed food. The present study is based on 25 pulse processing firms selected firms from the states of Uttar Pradesh, Rajasthan, and Delhi/NCR. The study applied FMEA (Failure mode Effect Analysis) and Pareto Analysis to identify the potential risk and determine their severity index with the help of the Pareto analysis chart, and applied the ANOVA method to generate the frequency of F- the value of risk factors impact on pulse firms understand the level of significance of risk factors.

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Section: Literature Reviewmentioning

confidence: 99%

Case Study: Risk Assessment of Indian Pulse processing firms using FMEA Techniques – Evidence from selected states of India

Sahu¹,

Arora²

2022

Journal of Pharmaceutical Negative Results

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“…More formally, at the Goddard Space Flight Centre, the FMECA has been used for correlating mission parameters to risk management consequence definitions, by providing tools for their assessment and communication to decision-makers [19]. Furthermore, a FMECA-based approach prioritized items based on their criticality number, calculated by multiplying the scores assigned to severity and occurrence likelihood, under the assumption of exponentially distributed reliability [20], even with a specific interest in a typical satellite payload [21].…”

Section: Literature Reviewmentioning

confidence: 99%

A Reliability Engineering Approach for Managing Risks in CubeSats

et al. 2018

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Besides large-scale space missions, the spread of CubeSats for a variety of applications is increasingly requiring the development of systematic approaches for risk management. Being these applications are based on components with low TRL (Technology Readiness Level) or with limited performance data, it is required to define approaches which ensure a systematic perspective. This paper aims to present a reliability engineering approach based on FMECA (Failure Mode, Effects, and Criticality Analysis) to manage CubeSat reliability data and prioritize criticalities early in the design phase. The approach firstly proposes an alpha-numeric coding system to support the identification and labeling of failure modes for typical CubeSats’ items. Subsequently, each FMECA coefficient (i.e., Severity, Occurrence, Detectability) has been linked to the CubeSat’s structural properties, reducing subjectivity by means of techno-centric proxy indicators. The approach has been validated in the design phases of a 6-Units university CubeSat for the observation of M-Dwarf stars and binary systems. The performed analysis supported the design process and allowed to identify the major criticalities of the CubeSat design, as demonstrated in the extended case study included in the paper. The formalized method could be applied to design procedures for nano-satellites, as well as being expanded for research and development in a variety of space missions.

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