Since it first appeared in literature in the early nineties, the Circular Economy (CE) has grown in significance amongst academic, policymaking, and industry groups. The latest developments in the CE field have included the interrogation of CE as a paradigm, and its relationship with sustainability and other concepts, including iterative definitions. Research has also identified a significant opportunity to apply circular approaches to our rapidly changing industrial system, including manufacturing processes and Industry 4.0 (I4.0) which, with data, is enabling the latest advances in digital technologies (DT). Research which fuses these two areas has not been extensively explored. This is the first paper to provide a synergistic and integrative CE-DT framework which offers directions for policymakers and guidance for future research through a review of the integrated fields of CE and I4.0. To achieve this, a Systematic Literature Review (SLR; n = 174) of the empirical literature related to digital technologies, I4.0, and circular approaches is conducted. The SLR is based on peer-reviewed articles published between 2000 and early 2018. This paper also summarizes the current trends in CE research related to manufacturing. The findings confirm that while CE research has been on the increase, research on digital technologies to enable a CE is still relatively untouched. While the “interdisciplinarity” of CE research is well-known, the findings reveal that a substantial percentage is engineering-focused. The paper concludes by proposing a synergistic and integrative CE-DT framework for future research developed from the gaps in the current research landscape.

Pandemics and other forms of epidemic outbreaks are a unique case of manufacturing risk typified by high uncertainty, increasing propagation and long-term disruption to manufacturers, supply chain actors as well as the end-users and consumers. For manufacturing the COVID-19 disruption scope has been largely twofold ; an endogenous disruption of manufacturing processes and systems as well as extreme shifts in demand and supply caused by exogenous supply chain disruption. Existing literature on disruptions in manufacturing suggests that pandemics are qualitatively different from typical disruptions. There is no literature available to manufacturing practitioners that identify the barriers and enablers of manufacturing resilience, especially with regards to pivoting of the manufacturing sector in response to a pandemic. This study draws on an extensive survey collected during the COVID-19 pandemic. The respondents were employees of manufacturing firms in all regions of the world who had engaged in manufacturing during the pandemic or had opted out from manufacturing due to various identified reasons. By collating their responses, we offer to practitioners and policymakers an analysis for identifying a bestpractice framework for pivoting successfully as a response to major manufacturing disruptions.

This paper presents an investigation on how simulation informed by the latest advances in digital technologies such as the 4th Industrial Revolution (I4.0) and the Internet of Things (IoT) can provide digital intelligence to accelerate the implementation of more circular approaches in UK manufacturing. Through this research, a remanufacturing process was mapped and simulated using discrete event simulation (DES) to depict the decision-making process at the shop-floor level of a remanufacturing facility. To understand the challenge of using data in remanufacturing, a series of interviews were conducted finding that there was a significant variability in the condition of the returned product. To address this gap, the concept of certainty of product quality (CPQ) was developed and tested through a system dynamics (SD) and DES model to better understand the effects of CPQ on products awaiting remanufacture, including inspection, cleaning and disassembly times. The wider application of CPQ could be used to forecast remanufacturing and production processes, resulting in reduced costs by using an automatised process for inspection, thus allowing more detailed distinction between “go” or “no go” for remanufacture. Within the context of a circular economy, CPQ could be replicated to assess interventions in the product lifecycle, and therefore the identification of the optimal CE strategy and the time of intervention for the current life of a product—that is, when to upgrade, refurbish, remanufacture or recycle. The novelty of this research lies in investigating the application of simulation through the lens of a restorative circular economic model focusing on product life extension and its suitability at a particular point in a product’s life cycle.

The transition to a circular economy (CE) requires companies to evaluate their resource flows, supply chains, and business models and to question the ways in which value is created. In the high value manufacturing (HVM) sector, this evaluation is critical, as HVM enables value in nonconventional forms, beyond profit, including unique production processes, brand recognition, rapid delivery times, and highly customized services. We investigate the role of value, cost, and other factors of influence in the selection of a circular business model (CBM) for HVM. Explored through five case studies using a qualitative evaluation of circularity, we then contribute to the emerging field of CBMs by modifying the CBM canvas that can capture the nontraditional value, traditional value, cost, and other influencing factors enabled via CBM adoption in HVM. Finally, the important role of digital technologies for incentivizing and enabling CBM adoption, is clarified.

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Remanufacturing is a viable option to extend the useful life of an end-of-use product or its parts, ensuring sustainable competitive advantages under the current global economic climate. Challenges typical to remanufacturing still persist, despite its many benefits. According to the European Remanufacturing Network, a key challenge is the lack of accurate, timely and consistent product knowledge as highlighted in a 2015 survey of 188 European remanufacturers. With more data being produced by electric and hybrid vehicles, this adds to the information complexity challenge already experienced in remanufacturing. Therefore, it is difficult to implement real-time and accurate remanufacturing for the shop floor; there are no papers that focus on this within an electric and hybrid vehicle environment. To address this problem, this paper attempts to: (1) identify the required parameters/variables needed for fuel cell remanufacturing by means of interviews; (2) rank the variables by Pareto analysis; (3) develop a casual loop diagram for the identified parameters/variables to visualise their impact on remanufacturing; and (4) model a simple stock and flow diagram to simulate and understand data and information-driven schemes in remanufacturing.

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