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Circular Manufacturing Systems: Complex systems modelling and simulation for enhanced decision-making

Time: Fri 2022-12-09 09.00

Location: Kollegiesalen, Brinellvägen 8, Stockholm

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Language: English

Subject area: Production Engineering

Doctoral student: Malvina Roci , Tillverkning och mätsystem

Opponent: Professor Tomohiko Sakao, Linköping University

Supervisor: Professor Amir Rashid, Tillverkning och mätsystem; Dr Farazee Mohammad Abdullah Asif, Tillverkning och mätsystem; Professor Cali Nuur, Hållbarhet, Industriell dynamik & entreprenörskap

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A transition towards circular manufacturing systems (CMS) has brought awareness of untapped economic and environmental benefits for the manufacturing industry. Despite this increased interest, the implementation of CMS is still in its infancy stage. To support the manufacturing industry in implementing CMS in practice, this research seeks to (1) explore the main characteristics of CMS and their needs for a successful implementation in the context of the manufacturing industry, and (2) develop quantitative analysis tools to support decision-making in implementing CMS with a concurrent focus on economic and environmental performance. By viewing CMS as complex adaptive systems (CAS), this research proposes to exploit complex system modelling and simulation used in the study of CAS to characterise, model, and analyse CMS. In this regard, a multi-method simulation model architecture that combines features of agent-based, discrete-event, and system dynamics modelling methods is proposed to model and simulate CMS as different abstraction levels are needed to capture the complex and dynamic interactions among the elements of the system. The resulting multi-method simulation tool aims at providing systemic quantification of CMS in terms of economic performance (e.g., lifecycle costs, lifecycle revenues, and lifecycle profits), environmental performance (e.g., lifecycle environmental impact), and technical performance (e.g., quality, quantity and timing of product return flows), and therefore, facilitates decision-making for industrial organizations implementing CMS in practice.