Abstract
The core concept of this chapter is the total cost of ownership (TCO) of industrial asset and its relevance in supporting decision making, if properly evaluated through the analysis of the technical performances of the asset. The chapter is based on a framework that systematizes benefits and potential applications of TCO for different kind of stakeholders at different stages of the life cycle of the asset supporting different kind of decisions. The aim is to present an experimental case study that has been implemented in order to show the empirical evidence of what is in the framework by focusing on one of the primary companies in the chemical industry in Italy. The application proposes a modeling approach for trying to overcome one main gap that still subsists when referring to TCO models that is that most of the existing ones lack of the integration of technical performances evaluations into the cost models or are based on very limiting hypothesis. In this chapter a comprehensive methodology for the evaluation of Total Cost of Ownership of industrial assets that has being developed within a research activity carried out at the Department of Management, Economics and Industrial Engineering of Politecnico di Milano is presented.
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Notes
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The reliability oriented engineering software R-MES Project© (Reliability Maintenance Engineering System Project) is used for performing the above mentioned modelling and calculation steps from 4 to 6.
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Acknowledgements
This research work has taken advantage from the application of TCO modelling methodology in an industrial case-study, hosted in the production premises of ENI Versalis in Ravenna (Italy). Many thanks are due to Mr. Saverio Albanese for his trusting in this research topic and to the Versalis Ravenna crew for their kind and passionate support.
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Roda, I., Garetti, M. (2020). Application of a Performance-Driven Total Cost of Ownership (TCO) Evaluation Model for Physical Asset Management. In: Crespo Márquez, A., Macchi, M., Parlikad, A. (eds) Value Based and Intelligent Asset Management. Springer, Cham. https://doi.org/10.1007/978-3-030-20704-5_3
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