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Licenciate seminar: Towards a framework for enabling sustainable production systems: a life-cycle perspective
2016-09-20 @ 14:00 - 16:00 CEST
Ilaria Barletta will present her licentiate thesis for the degree of licentiate of engineering at Chalmers University of Technology on the 20th of September at 14:00 PM in Virtual Development Laboratory, Chalmers Tvärgata 4C, Gothenburg. The thesis will be presented and discussed in English.
The discussion leader will be Dr Erik Sundin at the Division of Manufacturing Engineering at Linköping University.
This thesis contributes to scientific knowledge by offering the foundation of a framework that helps stakeholders such as managers and engineers to enable sustainability over the entire lifecycle of the production system, from planning to re-use. In this thesis sustainability can be assessed through performance indicators and is understood through its triple bottom line of: economic, environmental and social sustainability. Within the framework, the requirements for designing a sustainable production system drove the choice of methods and key performance indicators (KPIs) used to assess sustainability performances of the production system in object. The methods employed to assess sustainability were: novel energy KPIs, a set of social sustainability KPIs, life cycle assessment, and discrete event simulation. The framework has been applied to the case of an automatic piece of sorting equipment for electronic waste, with the aim of foreseeing the sustainability impacts of its implementation in a facility run by manual labor. For the case study of production systems using machine tools, the use of newly developed energy efficiency KPIs proved to enable more effective energy management and saving. Possible lack of commitment to sustainability from companies and lack of necessary data can hinder the applicability of the framework. All in all, the framework and the methods can offer decisional support for the stakeholders who want to foster sustainable production.
Keywords: sustainability, triple bottom line, manufacturing, e-waste, decision support, KPI, discrete event simulation, energy efficiency