Abstract
This chapter describes an approximate estimation method for the product life cycle cost (LCC), called an approximate LCC estimation method, which allows the designer to make comparative LCC estimation between the different product concepts. The proposed approach provides the approximate and rapid estimation of product LCC based on high-level information typically known in the conceptual phase. The product attributes at the conceptual design phase and LCC factors are identified and the significant product attributes are determined by statistical analysis. An artificial neural network (ANN) is trained on product attributes and the LCC data from pre-existing LCC studies. This approach does not require a new LCC model.
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Seo, KK. (2005). Neural Network Systems Technology and Applications in Product Life-Cycle Cost Estimates. In: Leondes, C.T. (eds) Intelligent Knowledge-Based Systems. Springer, Boston, MA. https://doi.org/10.1007/978-1-4020-7829-3_42
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DOI: https://doi.org/10.1007/978-1-4020-7829-3_42
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4020-7746-3
Online ISBN: 978-1-4020-7829-3
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