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Titlebook: Data-Driven Decision Making for Product Service Systems; Giuditta Pezzotta,Roberto Sala,Fabiana Pirola Book 2024 The Editor(s) (if applica

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發(fā)表于 2025-3-21 18:38:35 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Data-Driven Decision Making for Product Service Systems
編輯Giuditta Pezzotta,Roberto Sala,Fabiana Pirola
視頻videohttp://file.papertrans.cn/285/284464/284464.mp4
概述Provides a comprehensive review of data-driven decision-making tools for PSS.Includes an in-depth discussion on practical implications of the adoptions of data-driven decision-making tools.Presents an
圖書封面Titlebook: Data-Driven Decision Making for Product Service Systems;  Giuditta Pezzotta,Roberto Sala,Fabiana Pirola Book 2024 The Editor(s) (if applica
描述.This book is a compilation of theoretical and practical contributions aimed at facilitating the servitization of manufacturing companies, specifically focusing on data-driven decision-making within the context of Product-Service Systems (PSS). Providing a comprehensive overview, it discusses the latest breakthroughs in operational, tactical, and strategic decision-making for PSS, leveraging data-driven processes, methodologies, and tools. Therefore, the book significantly contributes to strengthening the knowledge on the use of data-driven decision-making methods and tools all the phases of the PSS lifecycle..From extended warranties and leasing to pay-per-use and other innovative configurations, manufacturing companies are increasingly adopting servitized business models and PSS to create additional value for their customers and users and create robust relationships with them, ensuring more reliable cash flows. In this setting, effective information management and the utilization of aggregated operational data have become essential for guiding strategic, tactical, and operational decisions..This book not only consolidates theoretical frameworks but also offers practical insights
出版日期Book 2024
關(guān)鍵詞Data Driven Decision Making; Servitization; Digitalization; PSS Lifecycle; Product Service System
版次1
doihttps://doi.org/10.1007/978-3-031-60082-1
isbn_softcover978-3-031-60084-5
isbn_ebook978-3-031-60082-1
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Role of Ontology in Data-Driven PSS Engineering and Design and Lifecycle Managementore, there is a need for a structural approach in data management. A PSS semantic framework in the form of ontology representing generic PSS entities and their relations brings not only benefits to PSS engineering and design phases, but also enhancements of the whole PSS lifecycle management. This c
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Multi Criteria Decision Making for PSS Design models for Multi-Criteria Decision Making (MCDM) are proposed in the literature to augment the ability of the design team to identify, early on in the process, the most valuable solution option(s). The aim of this chapter is to review how MCDM is applied today to guide design concept selection acti
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Using Operational Data to Represent Machine Components Health and Derive Data-Driven Servicesficantly increased prices, as well as long and uncertain delivery times. As a consequence, they consider potential alternatives to meet material requirements. One of these alternative approaches is to extend the useful life of required technical components based on an assessment of their current con
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Defining the Smartness of Data-Driven PSS in Decision-Makingen we analyse the papers presented at the Smart Services Summit 2022 to shed light on the characteristics a smart PSS should have to enable more effective business decisions. In doing this, we specifically explore who are the purposes and beneficiaries of data-driven decisions in smart PSS. We devel
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