In recent years sustainable development became one of the most important topics to pursue economic activities development compatible with the environment in order to preserve it for future generations. Life Cycle Assessment (LCA) is used as a tool to assess the environmental impacts of a product, process, or activity throughout its life cycle providing support for product eco-design. The Life Cycle Inventory (LCI) is the second of the four phases of the LCA methodology regulated by the ISO 14040 and ISO 14044 series of international technical standards and represents the most energy and time-consuming phase of LCA. The complexity of the LCI is one of the factors that makes LCA studies difficult to carry out within the business because it requires specialists capable of conducting the analysis, a strong collaborative attitude of management, and a factory staff able to conduct the collection of primary data in an effective manner. In this context technologies involved in Industry 4.0 give a comprehensive view of how companies are organized and let acquire precise data on production activity. The analysis of these data, together with the development of new digital paradigms, represents an exploitable new focus to make production more efficient, profitable, and sustainable. The potentiality of this comprehensive data collection drove the present thesis project to integrate the Life Cycle Assessment and the availability of data provided by Industry 4.0 exploiting the framework presented by ISO 23247 on Digital twin for manufacturing. Production Life Cycle Assessment, Predictive Production Life Cycle Assessment, Environmental production efficiency algorithm, and eco-design support tool developed at the case study company FITT S.p.A. are the results obtained and discussed in the present master thesis.
In recent years sustainable development became one of the most important topics to pursue economic activities development compatible with the environment in order to preserve it for future generations. Life Cycle Assessment (LCA) is used as a tool to assess the environmental impacts of a product, process, or activity throughout its life cycle providing support for product eco-design. The Life Cycle Inventory (LCI) is the second of the four phases of the LCA methodology regulated by the ISO 14040 and ISO 14044 series of international technical standards and represents the most energy and time-consuming phase of LCA. The complexity of the LCI is one of the factors that makes LCA studies difficult to carry out within the business because it requires specialists capable of conducting the analysis, a strong collaborative attitude of management, and a factory staff able to conduct the collection of primary data in an effective manner. In this context technologies involved in Industry 4.0 give a comprehensive view of how companies are organized and let acquire precise data on production activity. The analysis of these data, together with the development of new digital paradigms, represents an exploitable new focus to make production more efficient, profitable, and sustainable. The potentiality of this comprehensive data collection drove the present thesis project to integrate the Life Cycle Assessment and the availability of data provided by Industry 4.0 exploiting the framework presented by ISO 23247 on Digital twin for manufacturing. Production Life Cycle Assessment, Predictive Production Life Cycle Assessment, Environmental production efficiency algorithm, and eco-design support tool developed at the case study company FITT S.p.A. are the results obtained and discussed in the present master thesis.
Development of a new dynamic LCA tool for the process virtualisation of plastic pipe production: the case of FITT S.p.A.
PAULON, MARTINA
2021/2022
Abstract
In recent years sustainable development became one of the most important topics to pursue economic activities development compatible with the environment in order to preserve it for future generations. Life Cycle Assessment (LCA) is used as a tool to assess the environmental impacts of a product, process, or activity throughout its life cycle providing support for product eco-design. The Life Cycle Inventory (LCI) is the second of the four phases of the LCA methodology regulated by the ISO 14040 and ISO 14044 series of international technical standards and represents the most energy and time-consuming phase of LCA. The complexity of the LCI is one of the factors that makes LCA studies difficult to carry out within the business because it requires specialists capable of conducting the analysis, a strong collaborative attitude of management, and a factory staff able to conduct the collection of primary data in an effective manner. In this context technologies involved in Industry 4.0 give a comprehensive view of how companies are organized and let acquire precise data on production activity. The analysis of these data, together with the development of new digital paradigms, represents an exploitable new focus to make production more efficient, profitable, and sustainable. The potentiality of this comprehensive data collection drove the present thesis project to integrate the Life Cycle Assessment and the availability of data provided by Industry 4.0 exploiting the framework presented by ISO 23247 on Digital twin for manufacturing. Production Life Cycle Assessment, Predictive Production Life Cycle Assessment, Environmental production efficiency algorithm, and eco-design support tool developed at the case study company FITT S.p.A. are the results obtained and discussed in the present master thesis.File | Dimensione | Formato | |
---|---|---|---|
Paulon_Martina.pdf
accesso riservato
Dimensione
10.4 MB
Formato
Adobe PDF
|
10.4 MB | Adobe PDF |
The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License
https://hdl.handle.net/20.500.12608/37075