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Call for a Master’s Thesis

Thursday, 24 January 2019

Circular product design based on PLM data

Background:
The use of product life cycle data (PLCD) (e.g., from PLM systems, IoT sensors, data-mining or machine learning, …) can be considered as a major enabler for the circular economy transition [1]. Despite the acknowledged importance of such data management approaches, a considerable research gap exists regarding the connection of the collected information to the goals of the circular economy [2]. Most Big Data/data mining or sensor applications only focus on a single stage of the lifecycle. Little effort has been devoted to data and knowledge integration for the whole lifecycle [3].

Objective:
This thesis has the objective to investigate the potential of using PLCD as input for the sustainable design of products - a cornerstone for the circular economy transition. More specifically, potential data sources along the product life cycle shall be matched with socio-ecological aspects and indicators relevant to product design. The focus will lie on data available in Product Lifecycle Management (PLM) systems. First, a conceptual model linking data sources and indicators will be developed based on scientific literature and relevant standards and reports. Second, industry experts will be integrated into the research process to evaluate the model and to elaborate on it. 

Methods:
Literature review, conceptual modeling, interviews, …

Contact:
Prof. Rupert Baumgartner; rupert.baumgartner@uni-graz.at

Application: 
Until February 10th 2019

Funding is available for this thesis.

References:
[1]    C. J. C. Jabbour, A. B. L. de S. Jabbour, J. Sarkis, and M. G. Filho, “Unlocking the circular economy through new business models based on large-scale data: An integrative framework and research agenda,” Technological Forecasting and Social Change, 2017.
[2]    A. Pagoropoulos, D. C. A. Pigosso, and T. C. McAloone, “The Emergent Role of Digital Technologies in the Circular Economy: A Review,” in Procedia CIRP, 2017, vol. 64, pp. 19–24.
[3]    Y. Zhang, S. Ren, Y. Liu, T. Sakao, and D. Huisingh, “A framework for Big Data driven product lifecycle management,” J. Clean. Prod., vol. 159, pp. 229–240, 2017.
 

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