9.6.1 On Trade Studies

This paper reports on a trade study of feasible concept alternatives for control and low voltage power distribution architecture for subsea process stations. Subsea gas compression is a new process station technology that is responding to the market need for extending the lifetime of existing subsea gas fields. These subsea process stations are deployed in deeper water, farther offshore and in harsher environments. The demand for a more efficient, less complex, and cheaper solution is pushing the technology development and screening for alternative concepts. The SPADE methodology has guided a trade study of concept opportunity exploration for alternative distribution architectures. The Pugh matrix demonstrated its ability to provide a simple overview of the multiple factors in a decisionmaking situation, with extensions for risk and opportunity assessment.

Section: Figure 3 -Spade Methodology/framework Graphical Representatimentioning

confidence: 99%

“…In concept selection, a set of selection criteria is needed to differentiate between the alternative solutions[5] [12] …”

mentioning

confidence: 99%

Trade Study of Alternative Controls and Power Distribution Architecture in Subsea Processing

Eide¹,

Haskins

2016

“…Often it remains unclear whether the trade-off study is effective or not in choosing a good alternative. Buede (2014) discusses challenges with trade studies: "The pitfalls of trade studies include missing important alternatives or objectives, and being overconfident about the future, especially the system's context, its usage, the various technologies to be employed in the system, or the architecture's capabilities" (Buede 2014, p. 8).…”

Section: Introductionmentioning

confidence: 99%

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

Honoré‐Livermore,

Rovik,

Haskins

2022

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).

“…Life cycle cost analysis, which is one of the key objectives that is considered in conceptual design and architecture trade studies (Buede, 2004), is particularly vulnerable to this problem as the actual hardware and software design represents only a very small part of the life cycle cost when compared with operating and disposal costs, which have significant uncertainty in early project stages. Some traditional cost risk assessment may be possible for the engineering and development costs that will be incurred in the near term, but generally it is not feasible for costs that will be incurred in later years of the project because specific risk drivers are hard to pin down and the project scope is frequently subject to change.…”

Section: Introductionmentioning

confidence: 99%

3.3.1 Quantifying Cost Risk Early in the Life Cycle

Kenley¹,

Nail

2005

A new method for analyzing life cycle cost risk on large programs is presented that responds to an increased emphasis on improving sustainability for long‐term programs. This method provides better long‐term risk assessment and risk management techniques. It combines standard Monte Carlo analysis of risk drivers and a new data‐driven method developed by the Hoy and Hudak (1994). The approach permits quantification of risks throughout the entire life cycle without resorting to difficult to support subjective methods. The Hoy‐Hudak methodology is shown to be relatively straightforward to apply to a specific component or process within a project using standard technical risk assessment methods. The total impact on system is obtained using the program WBS, which allows for the capture of correlated risks shared by multiple WBS items. Once the correlations and individual component risks are captured, a Monte Carlo simulation can be run using a modeling tool such as Analytica to produce the overall life cycle cost risk.