This paper proposes a three-step cost estimation methodology that dynamically adapts the focus of the analysis on the progress of the development phases and on the different levels of aggregation of the product architecture. At each step, different qualitative and quantitative techniques are progressively integrated according to the degree of data granularity required by the advancement of the product development. Moreover, a fixed set of cost drivers are identified to express the costs at different phases of the product lifecycle. The different levels of the product architecture are instead used as a framework to collect and bundle data for a cost analysis, which gradually increases the accuracy. Hence, the purpose of this research is to move the focus from merely estimating the structuring data and information for the cost analysis. The methodology is explicitly aimed at standardized assembled systems/products, characterized by a high number of parts and modules shared among different product versions. The approach was tested and validated at an automotive company that designs, produces, and markets measurement devices for engine development. Operatively, the approach can be used by the development team to evaluate the impact of different design alternatives, deriving the lifecycle costs of the product once the design choices are made. By tracking the development process at each aggregation level, designers can assess cost reduction by monitoring the impact of selected cost drivers while the product development process is in progress.
A Product Architecture-Based Framework for a Data-Driven Estimation of Lifecycle Cost
Manuscript received September 23, 2018; final manuscript received March 1, 2019; published online April 1, 2019. Assoc. Editor: Karl R. Haapala.
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Altavilla, S., and Montagna, F. (April 1, 2019). "A Product Architecture-Based Framework for a Data-Driven Estimation of Lifecycle Cost." ASME. J. Manuf. Sci. Eng. May 2019; 141(5): 051007. https://doi.org/10.1115/1.4043195
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