Open AccessCost Estimation Process of Remote Sensing Satellites
Author(s) -
K K Dechamma,
AUTHOR_ID,
Chinni Mohith,
Suma Mirji,
Rahul Kumar,
Palani Murugan,
K. Subramanya,
AUTHOR_ID,
AUTHOR_ID,
AUTHOR_ID,
AUTHOR_ID,
AUTHOR_ID
Publication year - 2021
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f2997.1211221
Subject(s) - computer science , cost estimate , process (computing) , probabilistic logic , satellite , statistical model , path (computing) , estimation , operations research , basis (linear algebra) , industrial engineering , systems engineering , machine learning , engineering , artificial intelligence , mathematics , geometry , programming language , aerospace engineering , operating system
Forecasting cost of satellites is not a recent development in space agencies, they were in practice from the beginning using traditional methods. The attempt to make it simpler, quicker and accurate; established the path to build a model by incorporating statistics, technology and technical knowledge. Building relationships between satellite cost and the technical parameters affecting them directly or indirectly became the basis of the model. The building of the cost model is more vexing than it looks. It requires data to perform regression analysis, which can be linear or nonlinear along with transformations. This paper also specifies the significance of the uncertainty impacting the cost associated with the technical parameters and the method of estimation. The overall model is mapped into three parts; the manpower and facility cost model being the deterministic bottom-up model and the combination of probabilistic and deterministic model for satellite cost.