Life cycle cost and function analysis in value based design decision

ABSTRACTThe early conceptual design (CD) phase of space access vehicles (SAVs) is the most abstract, innovative and technologically challenging phase of the entire aerospace design life cycle. Although the design decision-making during this phase influences around 80 percent of the overall life cycle cost, it is the most abstract and thus least understood phase of the entire design life cycle. The history of SAV design provides numerous examples of project failures that could have been avoided if the decision-maker had had the capability to forecast the potential risks and threats correctly ahead of time during the conceptual design phase. The present study addresses this crucial phase and demonstrates a best-practice synthesis methodology prototype to advance the current state of the art of CD as applied to SAV design. Developed by the Aerospace Vehicle Design (AVD) Laboratory at the University of Texas at Arlington (UTA), the Aerospace Vehicle Design Synthesis process and software (AVDS) is a prototype solution for a flight vehicle configuration–flexible (generic) design synthesis capability that can be applied to the primary categories of SAVs. This study focusses on introducing AVDS, followed by the demonstration and verification of the system’s capability through a sizing case study based on the data-rich Boeing X-20 Dyna-Soar spaceplane.

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Application Study on Complex Product Based DMU in Product Life Cycle

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.308-310.1365 ◽

2011 ◽

Vol 308-310 ◽

pp. 1365-1369

Author(s):

Yun Bing Yang ◽

Feng Jun Wang ◽

Li Fan Wei ◽

Liang Li He

Keyword(s):

Life Cycle ◽

Product Life Cycle ◽

Optimization Design ◽

Function Analysis ◽

Design Characteristic ◽

Application Study ◽

Product Life ◽

Complex Product ◽

Existent Problem ◽

And Function

The design characteristic and effect of DMU (Digital Mock-Up) are simply introduced. According as the design characteristic of complex product, the request for DMU platform in product life cycle is analyzed, and function analysis of DMU platform is finished. The whole frame and logic configuration are illuminated based function analysis, the realization method of design validation and optimization, design cooperation, maintenance support are emphatically analyzed, and some applied examples of DMU are displayed. The future imperative studies for DMU are discussed based the developed work and existent problem.

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Life Cycle Cost Method by Segregation of Safety and Function

Journal of The Korean Society of Agricultural Engineers ◽

10.5389/ksae.2008.50.6.061 ◽

2008 ◽

Vol 50 (6) ◽

pp. 61-71

Author(s):

Joon-Gu Lee ◽

Han-Jung Kim ◽

Seong-Su Yoon ◽

Won Choi ◽

Hyung-Jin Lee ◽

...

Keyword(s):

Life Cycle ◽

Life Cycle Cost ◽

And Function

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Harmonizing structural safety levels with life-quality objectives

Canadian Journal of Civil Engineering ◽

10.1139/l02-112 ◽

2003 ◽

Vol 30 (3) ◽

pp. 500-510 ◽

Cited By ~ 7

Author(s):

M A Maes ◽

M D Pandey ◽

J S Nathwani

Keyword(s):

Life Cycle ◽

Life Cycle Cost ◽

Human Life ◽

Limit State ◽

Life Quality ◽

Essential Element ◽

Structural Safety ◽

Human Consumption ◽

Design Decision ◽

Limit States

Life-quality objectives are identified as an essential element in design decision making. Of particular concern is the question of optimal safety levels that are consistent with reasonable expectations of individuals in a present-day society. Using sound principles of decision analysis and utility theory, a lifetime utility function is developed. It is shown to be related to human consumption, life duration including the cumulative effects of mortality and discounting, and the relative amount of time spent on work versus leisure. Questions regarding the acceptability and affordability of changes in life quality can be addressed using the utility functions developed. As an application, design safety levels for the Confederation Bridge are examined and discussed. Life-quality objectives can also be included in a life-cycle cost optimization. This allows us to perform a level IV probabilistic design approach including costs and consequences without having to estimate the value of human life, but instead including the effect of consequences on changes in life quality of individuals at risk. This results in a useful tool to determine optimal limit state design safety levels, as is illustrated in a parametric analysis in the case of a single limit state.Key words: lifetime utility, life-quality index, risk acceptance, limit states design, target reliability levels, risk reduction, minimum life-cycle cost, structural safety.

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Activity-Based Costing in Design for Product Retirement

20th Design Automation Conference: Volume 2 — Robust Design Applications; Decomposition and Design Optimization; Optimization Tools and Applications ◽

10.1115/detc1994-0146 ◽

1994 ◽

Author(s):

Jan Emblemsvåg ◽

Bert Bras

Keyword(s):

Decision Making ◽

Life Cycle ◽

Life Cycle Cost ◽

Product Life Cycle ◽

Design Decision ◽

Activity Based Costing ◽

Product Life ◽

The Cost ◽

Future Work

Abstract In this paper, an approach is presented to estimate the cost incurred by different designs based on Activity-Based Costing (ABC). The suitability of utilizing ABC in design is explored in the context of design for product retirement. A comparison is made with a number of approaches for estimating product life-cycle cost. In comparison to other costing schemes, ABC has the advantages that it can trace both direct and indirect (overhead) costs correctly back to where these costs actually were incurred. This ‘traceability’ facilitates the identification of the most cost inefficient parts of the design, which makes ABC much more suitable for design decision making than other costing schemes. In general, ABC is also more accurate. Although the costs related to any part of a product’s life-cycle can be estimated, an automobile product retirement example is used to illustrate the usage of the approach described. In the example, a decision has to be made whether to pursue a recyclable car or a non-recyclable car. Future work is identified, primarily related to the inclusion of uncertainty in the approach presented.

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