CubeSats in University: Using Systems Engineering Tools to Improve Reviews and Knowledge Management

Honoré‐Livermore, Evelyn

doi:10.1016/j.procs.2019.05.056

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…Currently, the miniaturization of electrical/electronic components and the use of off-the-shelf devices and equipment (COTS) enable CubeSats in operational missions that previously could only be performed by medium or large satellites 8 . However, for Cubesats to be used in operational missions, their development must minimally follow the SE 9 . The use of SE in CubeSats projects provides an approach that helps in conducting the project and ensures the validation and veri cation of system requirements 10 .…”

Section: Introductionmentioning

confidence: 99%

Proposal of Risk Tolerance Factor for Optimizing Risk Management, based on the system context - Nanosatellite Case Studies

Monteiro

Garbi

Vidal

et al. 2022

Preprint

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The paper present and implement a generic methodology for optimizing the risk management of low-cost systems with a lean schedule and brief operating time. Therefore, a proposed approach uses a correction factor (RTF – Risk Tolerance Factor) in the qualitative risk management stage. To analyze the application of the RTF approach, two case studies, ARMADILLO and CONASSAT, are presented. It was observed that the use of the RTF approach provided the mitigation of a minor number of risks in the planning stage of risk management in CubeSats projects. The advantage of the RTF approach is that the project team will carry out more straightforward mitigation plans for qualified risks. It is concluded that the approach met the objective of providing the team members with information about which risk scenario the mission is allocated in at the beginning of the mission design process. However, it does not exclude the possibility of later application of the tool.

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Section: Introductionmentioning

confidence: 99%

Proposal of Risk Tolerance Factor for Optimizing Risk Management, based on the system context - Nanosatellite Case Studies

Monteiro

Garbi

Vidal

et al. 2022

Preprint

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“…Knowledge Management (KM) has an important role in improving performance in various types of organizations, ranging from government [1] , education [2] - [4] , health [5] - [7] , etc. Among the KM processes that function to guarantee access to knowledge is knowledge sharing [8] .…”

Section: Introductionmentioning

confidence: 99%

Expertise Locator For Lecturers Based on Publication

Heroza

Putriani

Rifai

et al. 2021

Data Science: J. of Computing and Appl. Informatics

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Among the KM processes that function to guarantee access to knowledge is knowledge sharing. This process allows knowledge assets and experiences possessed by the organization to be accessed by anyone in the organization. Especially by using IT, this process can be done more optimally by capturing existing knowledge into a system so that this valuable information can be monitored anytime and anywhere. There are times when the knowledge possessed by experts is difficult to capture and represent in the system as in the case of tacit knowledgesuch as instincts, insights, and experiences of the experts. One of the challenges in inventorying these experts is the process of creating expert profiles automatically based on a particular approach. This research create an Expert Locator for lecturers who are considered as experts in their field of research using publication data produced by these lecturers as an indication of their expertise. The search feature is made as an implementation of the extraction results that can be used by other parties to find experts by entering keywords in the form of the desired expertise.

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Academic application of trade‐off studies to support a CubeSat project

Honoré‐Livermore,

Rovik,

Haskins

2022

INCOSE International Symp

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Academic CubeSat projects offer students and researchers hands-on engineering experience and can deliver cutting-edge research data. The CubeSat projects are highly multidisciplinary and require teamwork skills as well as engineering expertise. A challenge for academic CubeSat projects is the high turnover of graduating students, which makes knowledge management complicated. Model-Based Systems Engineering (MBSE) offers functionality that can address many of the challenges academic CubeSat teams experience. This paper presents a trade-off study using the Analytical Hierarchy Process (AHP) to select an MBSE software for use by students. Literature on academic application of formal trade-off studies in student teams is limited. The case study described here shows how tangible and intangible factors are addressed using the AHP method, and a discussion of the process and results is provided. and in the teamwork and interpersonal domains. Directions chosen to share information and generating knowledge in the team influence the design quality. In addition, the team members have different backgrounds and interests for the satellite project (the intervention system) and their role in the project team (realization system) (Martin 2004).Academic CubeSat projects are challenged by a high turnover of students because of graduation, and many students join without prior knowledge of aerospace engineering or teamwork experience. Having good on-boarding and off-boarding processes, and an approach to knowledge management is important. Previous research suggests that there are challenges related to project management, balancing school work and satellite project work, ensuring momentum and project success. Moreover, research shows that the failure of many university CubeSat missions can be attributed to a lack of system-level testing and ad-hoc processes (Langer and Bouwmeester 2016, Faure 2017). The work in this paper is based one of the author's 2021 master thesis. More details can be found in the thesis online (Rovik 2021).

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CubeSats in University: Using Systems Engineering Tools to Improve Reviews and Knowledge Management

Cited by 6 publications

References 9 publications

Proposal of Risk Tolerance Factor for Optimizing Risk Management, based on the system context - Nanosatellite Case Studies

Proposal of Risk Tolerance Factor for Optimizing Risk Management, based on the system context - Nanosatellite Case Studies

Expertise Locator For Lecturers Based on Publication

Academic application of trade‐off studies to support a CubeSat project

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