This chapter presents a guiding framework for circular economy implementation in supply chains. Closing the loop for resource efficiency is a well-known practice in the industry. To concretize the circular economy implementation strategies, closed-loop thinking requires innovation and adaptation. Circular supply chains (CSCs) are one of the key enablers in closing the loop by design or intention for value recovery and profit maximization. CSC is an emerging area, and the view of CSC where forward and reverse supply chain is seamlessly integrated with the overall aim to achieve system-wide circularity is missing in the academic debate. By offering a cross-functional and systemic perspective of circular supply chains, we present a guiding framework to structure and understand the underlying complexities and highlight the crucial elements of circular supply chain implementation. The framework categorizes the circular supply chain into four building blocks: systemic approach, main drivers, levels of decision making, and mechanisms to manage the full loop closure and minimize the inherent uncertainties of a complex system. We conclude the chapter by illustrating the applicability of the circular supply chain framework using two industrial cases that are transitioning toward the circular economy.

The transition to circular manufacturing systems (CMS) is crucial for achieving sustainable growth, addressing the environmental concerns and resource scarcity challenges. Shifting towards CMS requires a systemic approach that integrates value proposition models, product design, and supply chains (SCs). Circular supply chains (CSCs) emerge as a core pillar of CMS, incorporating value delivery, use, recovery, and reuse. CSCs are inherently more complex and dynamic than linear SCs requiring a holistic analysis approach to capture their complex and dynamic attributes. This research proposes an integrated analysis framework combining qualitative and quantitative approaches to explore the complexities and dynamics of CSCs and assess their economic, environmental, and technical performance. Through the lens of two different CMS implementation case studies, one in automotive parts remanufacturing and one in white goods manufacturing, this research illustrates the framework's applicability. In the automotive case, centralizing core management activities was found to improve economic performance by 50-54 %. However, the introduction of regional logistics hubs, while economically efficient, led to a 20 % increase in CO2-equivalent emissions. On the other hand, the white goods case study highlighted the trade-offs in centralizing end-of-life recovery facilities, where financial savings of up to 60 % were offset by increased transportation costs and increased CO2 emissions. The analysis of CSCs in these two distinct manufacturing sectors underscores the relevance and flexibility of the proposed framework, providing decision-makers with a tool to examine how different CSCs configurations and strategies impact overall performance. This guidance is crucial for developing optimal CSCs design and implementation strategies.

Circular business models are gaining traction in academia and industry as an instrument to deliver environmental benefits while being economically profitable. Despite this increased interest, studies that quantitatively assess the impact of circular business models are limited. This study provides researchers and practitioners with a quantitative analysis tool to assess the dynamics of circular business models from both an economic and environmental perspective. Using the case study of white goods-as-a-service, this study employs multi-method simulation modelling in combination with statistical design and analysis of simulation experiments to investigate the effect of different factors including payment schemes (i.e., fixed fee, pay-per-use, and hybrid) and subscription contract duration (i.e., long-term, mid-term, and short-term) on the economic and environmental performance of access-based models. In addition, as the adoption of access-based models is economically challenging for manufacturers due to a discrepancy between costs and revenue streams, this study analyses the effect of different levers to improve the liquidity performance of access-based business models including deposit schemes, cancellation and collection fees, as well as partnering with financial institutions to cover the initial revenue gap. 

Closing the loop for resource efficiency is a well‐known practice in the industry. To concretize the circular economy implementation strategies, closed‐loop thinking requires innovation and adaptation. Circular supply chains (CSCs) are one of the key enablers in closing the loop by design or intention for value recovery and profit maximization. CSC is an emerging area, and the view of CSC where forward and reverse supply chain is seamlessly integrated with the overall aim to achieve system‐wide circularity is missing in the academic debate. By offering a cross‐functional perspective of CSC, this paper presents a CSC guiding framework to structure and understand the underlying complexities and highlight the crucial elements of the CSC implementation. Thus, this framework lays the basis for CSC within the systemic implementation of CE by closing the loop by design or intention. The framework categorizes the CSC into four building blocks, namely, systemic approach, main drivers, levels of decision making, and mechanisms to manage the full loop closure and minimize the inherent uncertainties of a complex system. The building blocks of the framework are synthesized from various streams of supply chain literature and recurring concepts in the circular economy literature. The CSC framework applicability is illustrated using two industrial cases that are transitioning towards the circular economy.

Stretchable electronics is a new innovation and becoming popular in various fields, especially in the healthcare sector. Since stretchable electronics use less printed circuit boards (PCBs), it is expected that the environmental performance of a stretchable electronics-based device is better than a rigid electronics-based device that provides the same functionalities. Yet, such a study is rarely available. Thus, the main purpose of this research is to perform a comparative life cycle analysis of stretchable and rigid electronics-based devices. This research combines both the case study approach and the research review approach. For the case study, a cardiac monitoring device with both stretchable and rigid electronics is used. The ISO 14044:2006 standard's prescribed LCA approach and ReCiPe 2016 Midpoint (Hierarchist) are followed for the impact assessment using the SimaPro 9.1 software. The LCA results show that the stretchable cardiac monitoring device has better environmental performance in all eighteen impact categories. This research also shows that the manufacturing process of stretchable electronics has lower environmental impacts than those for rigid electronics. The main reasons for the improved environmental performance of stretchable electronics are lower consumption of raw material as well as decreased energy consumption during manufacturing. Based on the LCA results of a cardiac monitoring device, the study concludes that stretchable electronics and their manufacturing process have better environmental performance in comparison with the rigid electronics and their manufacturing process.

Since the introduction of the concept of learning curves in manufacturing, many articles have been applying the model to study learning phenomena. In assembly, several studies present a learning curve when an operator is trained over a new assembly task; however, when comparisons are made between learning curves corresponding to different training methods, unaware researchers can show misleading results. Often, these studies neglect either or both the stochastic nature of the learning curves produced by several operators under experimental conditions, and the high correlation of the experimental samples collected from each operator that constitute one learning curve. Furthermore, recent studies are testing newer technologies, such as assembly animations or augmented reality, to provide assembly aid, but they fail to observe deeper implications on how these digital training methods truly influence the learning curves of the operators. This article proposes a novel statistical study of the influence of expert video aid on the learning curves in terms of assembly time by means of functional analysis of variance (FANOVA). This method is better suited to compare learning curves than common analysis of variance (ANOVA), due to correlated data, or graphical comparisons, due to the stochastic nature of the aggregated learning curves. The results show that two main effects of the expert video aid influence the learning curves: one in the transient and another in the steady state of the learning curve. The transient effect of the expert video aid, where the statistical tests suffer from a high variance in the data, appears to be a reduction in terms of assembly time for the first assemblies: the operators seem to benefit from the expert video aid. As soon as the steady state is reached, a slower and statistically significant effect appears to favor the learning processes of the operators who do not receive any training aid. Since the steady state of the learning curves represents the long term production efficiency of the operators, the latter effect might require more attention from industry and researchers.

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.

En övergång till cirkulära tillverkningssystem (CMS) har skapat medvetenhet om outnyttjade ekonomiska och miljörelaterade fördelar för tillverkningsindustrin. Trots det ökade intresset är implementeringen av CMS fortfarande i sin linda. För att stödja tillverkningsindustrin med att implementera CMS i praktiken, strävar denna forskning efter att (1) utforska de viktigaste egenskaperna hos CMS och de behov som finns för att en framgångsrik implementering av CMS i tillverkningsindustrin ska kunna ske, och (2) utveckla kvantitativa analysverktyg som kan användas som beslutstöd vid implementering av CMS med samtidigt fokus på ekonomisk och miljömässig prestanda. Genom att behandla CMS som komplexa adaptiva system (CAS), föreslår denna forskning att utnyttja komplex systemmodellering och simulering som används i CAS för att karaktärisera, modellera och analysera CMS. I detta avseende föreslås en arkitektur för multimetodisk simuleringsmodell som kombinerar egenskaper från agentbaserade, diskret händelsestyrda, och systemdynamiska modelleringsmetoder för att modellera och simulera CMS. Denna kombination är nödvändig för att fånga de komplexa och ömsesidiga interaktionerna mellan delarna i systemet. Den resulterande multi-metodiska simuleringsmodellen syftar till att ge insikter om hur CMS beter sig i termer av ekonomi (t.ex. livscykelkostnader, livscykelintäkter och livscykelvinster), miljömässighet (t.ex. miljöpåverkan under livscykeln) och teknisk prestanda (t.ex. kvalitet, kvantitet och tidpunkt för produktreturflöden) och därigenom underlättar beslutsfattande för industriella organisationer som vill implementerar CMS.

Circular manufacturing systems (CMS) constitute complex value networks comprising a large and diverse set of stakeholders that collaborate to close the loop of products through multiple lifecycles. Complex systems modelling and simulation play a crucial role in providing quantitative and qualitative insights into the behaviour of such systems. In particular, multi-method simulation modelling that combines agent-based, discrete-event, and system dynamics simulation methods is considered more suitable to model and simulate CMS as it allows to capture their complex and dynamic nature. This paper provides a step-by-step approach on how to build a CMS multi-method simulation model in order to assess their economic, environmental, and technical performance for enhanced decision-making. To model and simulate CMS three main elements need to be considered: • A multi-method model architecture where the CMS stakeholders with heterogeneous characteristics are modelled individually as autonomous agents using agent-based, discrete-event, and system dynamics. • An agent environment defined by a Geographic Information System (GIS) to establish connections based on agents’ geographic location. • The product journey resulting from the product's interaction with various CMS stakeholders in the circular value network is traced throughout its multiple lifecycles.

A transition towards circular manufacturing systems (CMS) has brought awareness of untapped economic and environmental benefits for the manufacturing industry. Conventional manufacturing systems already present a high level of complexity in terms of physical flows of materials and products as well as information and financial flows linked to them. Closing the loop of materials and products through multiple lifecycles, as proposed in CMS, increases this complexity manifold. To support practitioners in implementing CMS through enhanced decision-making, this research studies CMS from a complex adaptive systems (CAS) perspective and proposes to exploit methods and tools used in the study of CAS to characterise, model and analyse CMS. By viewing CMS as CAS composed of autonomous, interacting agents, this research proposes a multi-method model architecture for modelling and simulating CMS. The different CMS stakeholders are modelled individually as autonomous agents by integrating agent-based, discrete-event, and/or system dynamics modules within each agent to capture their diverse and heterogeneous nature. The applicability of the proposed multi-method approach is illustrated through a case study of a white goods manufacturing company implementing CMS in practice. This case study shows the relevance and feasibility of the proposed multi-method approach as a decision support tool for the systemic exploration and quantification of CMS. It also shows how a transition towards CMS necessitates a lifecycle approach in terms of costs, revenues and environmental impacts to identify hotspots and, therefore, design circular systems that are viable in both economic and environmental terms. In fact, the analyses of the simulation results indicate how decisions in terms of business models, product design, and supply chain affected the CMS performance of the case company. For instance, implementing a service-based model led to a high number of usecycles (on average six usecycles per washing machine), which, in turn, led to high lifecycle costs and emissions due to more frequent transportation and recovery operations. Similarly, the deployment of long-lasting washing machines, which is a core principle of CMS, led to high manufacturing costs. Due to the high initial costs and a time mismatch between revenues and costs in the service-based model, it required a longer time for the company to reach the break-even point (approximately 23 months). Overall, the case study shows that multi-method simulation modelling can provide decision-making support for a successful implementation of CMS.

It is estimated that the adaptation of the Circular Economy approach can yield material cost savings of hundreds of billions of dollars per year for the EU and can result in huge environmental benefits. To tap this potential, the manufacturing industry needs to take a circular approach, where the products are designed intentionally to be used for multiple lifecycles. However, there is a lack of methodologies to date that can support such an approach. To fill this gap, this research has proposed a novel methodological approach that can support designing products for multiple lifecycles to keep the products as well as the components and the materials at their highest utility and value at all times. This research has identified that there is a strong synergy among the concepts of product design strategies, product obsolescence and product end-of-life options. Taking this synergy as the foundation and adopting modular architectures in the product design and development process, lifecycle planning can be performed for products that will sustain multiple lifecycles. This research is performed in two steps: first, the research review process is used to explore the knowledge base in the field of product design methodologies and based on the insights from the literature a novel methodological approach is proposed; second, a case example is used to demonstrate the applicability and effectiveness of the proposed methodological approach.