In the context of the sustainability transformation, manufacturing companies in the machinery and plant engineering industry are particularly in the spotlight due to their high energy and resource consumption. In order to remain competitive, there is increasing pressure to develop products with sustainability aspects in mind and to take responsibility for the entire product life cycle. 80 % of the environmental impact is defined during the planning and development of products, so creating transparency is a necessary prerequisite for reducing the environmental impact. There are already approaches for analyzing the ecology of products and companies, but they have not yet been successfully transferred to development due to a lack of functional orientation. At the same time, these methods are costly and time-consuming. Complex products in machinery and plant engineering in particular require clarity as to which aspects can be influenced by development decisions. Therefore, the aim of this thesis is to develop a methodology that enables a function oriented analysis of the ecology of products in machinery and plant engineering to identify fields of action for increasing product sustainability. For this purpose, the work is divided into five sub-models. The first step is to develop a generic description of products in machinery and plant engineering. The second step involves the identification and systematic structuring of process steps along the product life cycle that can be actively influenced by changes to the product. The third step identifies and structures ecological indicators relevant for product development and provides a framework for specific selection. The fourth step focuses on determining the relationships between the three dimensions of product, process and ecology. Finally, the fifth step presents a systematic procedure for the derivation of relevant fields of action with the objective of increasing product sustainability. Furthermore, it facilitates a methodology for evaluating the comparative impact of alternative improvement measures
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