Life Cycle Cost Models and Associated Uncertainties

1983 ◽  
pp. 535-549 ◽  
Author(s):  
Yash P. Gupta
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Cost Models

scholarly journals Dimensioning reserve bus fleet using life cycle cost models and condition based/predictive maintenance: a case study

2017 ◽  
Vol 10 (1) ◽  
pp. 169-190 ◽  
Author(s):  
Hugo Raposo ◽  
José Torres Farinha ◽  
Luís Ferreira ◽  
Diego Galar
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Predictive Maintenance ◽  
Cost Models

scholarly journals Uncertainty estimation in railway track life-cycle cost: a case study from Swedish National Rail Administration

2008 ◽  
Vol 223 (3) ◽  
pp. 285-293 ◽  
Author(s):  
A P Patra ◽  
P Söderholm ◽  
U Kumar
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Cost Effective ◽  
Railway Track ◽  
Statistical Characteristics ◽  
Maintenance Cost ◽  
Cost Models ◽  
Effective Decision ◽  
Effective Decision Support

Life-cycle cost (LCC) is used as a cost-effective decision support for maintenance of railway track infrastructure. However, a fair degree of uncertainty associated with the estimation of LCC is due to the statistical characteristics of reliability and maintainability parameters. This paper presents a methodology for estimation of uncertainty linked with LCC, by a combination of design of experiment and Monte Carlo simulation. The proposed methodology is illustrated by a case study of Banverket (Swedish National Rail Administration). The paper also includes developed maintenance cost models for track.

Leveraging a design of experiments methodology to enhance impacts of modeling and simulations for engineered resilient systems

2018 ◽  
Vol 15 (4) ◽  
pp. 383-397 ◽  
Author(s):  
Alex D MacCalman ◽  
Simon R Goerger
Keyword(s):  
Life Cycle ◽  
Experimental Design ◽  
System Design ◽  
Life Cycle Cost ◽  
Computational Models ◽  
Functional Form ◽  
Response Surfaces ◽  
Cost Models ◽  
Multiple Perspectives ◽  
Domain Models

System engineers rely on a variety of models and simulations to help understand multiple perspectives in several domains throughout a system’s life-cycle. These domain models include operational simulations, life-cycle cost models, physics-based computational models, and many more. Currently, there is a technical gap with regard to our ability to untangle system design drivers within system life-cycle domains. This article provides a procedural workflow that addresses this technical gap by leveraging the methods of experimental design in order to clearly identify tradable variables and narrow the search for viable system variants. Our purpose is to illuminate trade decisions across several different viewpoints by integrating metamodels that approximate the behavior of multiple domain models; a metamodel is a statistical function that acts as a surrogate to a model. Model inputs often represent value properties that define a system alternative configuration or environmental conditions that represent uncertain factors within the system boundary. Model outputs represent measures of performance or effectiveness that allow us to compare alternatives and understand the tradeoffs among several objectives. In order to illuminate the tradeoffs that exist in a complex system design problem we propose an approach that approximates model input and output behavior using the functional form of statistical metamodels. After performing an experimental design, we can fit a metamodel with a functional form known as a response surface. We utilize contour profilers that show horizontal cross sections of multiple response surfaces to visualize where key trade decisions exist. Our research supports the tradespace analytics pillar for the development of the engineered resilient system (ERS) architecture. The article concludes with instructions on how to perform simulation experiments to construct a dynamic dashboard that illuminates system tradeoffs.

Techno-Economic Optimal Design and Application of SOFC Systems for Residential Micro-CHP Applications in the U.S.

2008 ◽  
Author(s):  
Robert J. Braun
Keyword(s):  
Life Cycle ◽  
Optimal Design ◽  
Life Cycle Cost ◽  
Operating Parameter ◽  
Cost Models ◽  
Economic Optimization ◽  
Single Family ◽  
Chp System ◽  
System Configurations ◽  
The U.S

A techno-economic optimization study investigating optimal design and operating strategies of solid oxide fuel cell (SOFC) micro-combined heat and power (CHP) systems for application in U.S. residential dwellings is carried out through modeling and simulation of various anode-supported planar SOFC-based system configurations. Five different SOFC system designs operating from either methane or hydrogen fuels are evaluated in terms of their energetic and economic performance and their overall suitability for meeting residential thermal-to-electric ratios. Life cycle cost models are developed and employed to generate optimization objective functions which are utilized to explore the sensitivity of the life cycle costs to various system design and economic parameters and to select optimal system configurations and operating parameters for eventual application in single-family, detached residential homes in the U.S. The study compares the results against a baseline SOFC-CHP system that employs primarily external steam reforming of methane. The results of the study indicate that system configurations and operating parameter selections that enable minimum life cycle cost while achieving maximum CHP system efficiency are possible. Life cycle cost reductions of over 30% and CHP efficiency improvements of nearly 20% from the baseline system are detailed.

Life cycle cost models for comparing computer family architectures

1977 ◽  
Author(s):  
John J. Cornyn ◽  
William R. Smith ◽  
Aaron H. Coleman ◽  
William R. Svirsky
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Cost Models
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