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To review the state-of-the-art in smart remanufacturing, highlighting key elements of an Industry 4.0 (I4.0) future that supports circular economy (CE) principles and offer a conceptual framework and research agenda to accelerate digitalisation in this sector.

The Scopus, Web of Science and ScienceDirect databases and search terms “Industry 4.0”, “Internet of things”, “Smart manufacturing” and “Remanufacturing” were used to identify and select publications that had evidence of a relationship between those keywords. The 329 selected papers were reviewed with respect to the triple bottom line (economic, social and environmental). The study benefited from advanced text quantitative processing using NVivo software and a complete manual qualitative assessment.

Changes in product ownership models will affect the remanufacturing industry, with the growth of product-service-systems seen as an opportunity to re-circulate resources and create value. This is being supported by changes in society, user expectations and workforce attributes. Key to the success of remanufacturing in an I4.0 future is the uptake of existing and emerging digital technologies to shorten and strengthen links between product manufacturers, users and remanufacturers.

Remanufacturing is recognised as a key CE strategy, which in turn is an important research area for development in our society. This article is the first to study “smart remanufacturing” for the CE. Its uniqueness lies in its focus on the remanufacturing industry and the sustainable application of I4.0 enablers. The findings are used to create a framework that links to the research agenda needed to realise smart remanufacturing.

The application of digital twins to optimise operations and supply chain management functions is a bourgeoning practice. Scholars have attempted to keep pace with this development initiating a fast-evolving research agenda. The purpose of this paper is to take stock of the emerging research stream identifying trends and capture the value potential of digital twins to the field of operations and supply chain management.

In this work we employ a bibliometric literature review supported by bibliographic coupling and keyword co-occurrence network analysis to examine current trends in the research field regarding the value-added potential of digital twin in operations and supply chain management.

The main findings of this work are the identification of four value clusters and one enabler cluster. Value clusters are comprised of articles that describe how the application of digital twin can enhance supply chain activities at the level of business processes as well as the level of supply chain capabilities. Value clusters of production flow management and product development operate at the business processes level and are maturing communities. The supply chain resilience and risk management value cluster operates at the capability level, it is just emerging, and is positioned at the periphery of the main network.

This is the first study that attempts to conceptualise digital twin as a dynamic capability and employs bibliometric and network analysis on the research stream of digital twin in operations and supply chain management to capture evolutionary trends, literature communities and value-creation dynamics in a digital-twin-enabled supply chain.

This paper aims to assess the feasibility of a hybrid manufacturing and remanufacturing system (HMRS) for essential commodities in the context of COVID-19. Specifically, it emphasises using HMRS based on costs associated with various manufacturing activities.

The combination of mathematical model and system dynamics is used to model the HMRS system. The model was tried on sanitiser bottle manufacturing to generalise the result.

The remanufacturing cost is higher because of reverse logistics, inspection and holding costs. Ultimately remanufacturing costs turn out to be lesser than the original manufacturing the moment system attains stability.

The study put forth the reason to encourage remanufacturing towards sustainability through government incentives.

The study put forth the feasibility of the HMRS system for an essential commodity in the context of a covid pandemic. The research implemented system dynamics for modelling and validation.

In the past two decades, manufacturing has witnessed significant transformations alongside ecological challenges. Meanwhile, industrial 4.0 digital technologies have accelerated industrialisation with potentials of innovation in the context of circular economy. However, current concepts and models are fragmented and impractical. This paper aims to develop a holistic view integrating the three bodies of knowledge – industrialisation, ecologicalisation and digitalisation (IED) – in order to achieve sustainable development.

Critical literature review is conducted across three bodies of knowledge. Key themes are summarised with the identification of research gaps. A theoretical framework is synthesised and developed aiming to achieve synergy from IED with the modules, integration architecture, mechanism and dynamic paths.

First, the authors review and develop three conceptual models of ecologicalised industrialisation (IE3), industrial system digitalisation (D1) and digital technology industrialisation (D2) separately. Second, the authors propose a theoretical framework seeking to synthesise the above three conceptual models together to form the IED. Third, the authors design a process orientated abductive approach to improve and validate the IED framework.

This study contributes to the limited literature addressing the linkage of IED by integration different perspectives to develop theory in a novel way. Practically, it provides important tools for organisations to consider resource cascading in combination with digitalisation during the industrial system design.

As manufacturing technology has developed, digital models from advanced measuring devices have been widely used in manufacturing sectors. To speed up the production cycle and reduce extra errors introduced in surface reconstruction processes, directly machining digital models in the polygonal stereolithographyformat has been considered as an effective approach in rapid digital manufacturing. In machining processes, Cutter Location (CL) data for numerical control (NC) machining is generated usually from an offset model. This model is created by offsetting each vertex of the original model along its vertex vector. However, this method has the drawback of overcut to the offset model. The purpose of this paper is to solve the overcut problem through an error compensation algorithm to the vertex offset model.

Based on the analysis of the vertex offset method and the offset model generated, the authors developed and implemented an error compensation method to correct the offset models and generated the accurate CL data for the subsequent machining process. This error compensation method is verified through three polygonal models and the tool paths generated were used for a real part machining.

Based on the analysis of the vertex offset method and the offset model generated, the authors developed an error compensation method to correct the offset models and generated the accurate CL data for the subsequent machining process. The developed error compensation algorithm can effectively solve the overcut drawback of the vertex offset method.

The error compensation method to the vertex offset model is used for generating the CL data with the using of a ball-end cutter.

On the study of CL data generation for a STL model, most of the current studies are focused on the determination of the offset vectors of the vertexes. The offset distance is usually fixed to the radius of the cutter used. Thus, the overcut problem to the offset model is inevitable and has not been much studied. The authors propose an effective approach to compensate the insufficient distance of the offset vertex and solve the overcut problem.

The directly tool paths generation from a STL model can reduce the error of surface reconstruction and speed up the machining progress.

The authors investigate the overcut problem occurred in vertex offset for CL data generation and present a new error compensation algorithm for generating the CL data that can effectively solve the overcut problem.

This paper aims to investigate the theoretical and practical links between digital twin (DT) application in heritage facilities management (HFM) from a life cycle management perspective and to signpost the future development directions of DT in HFM.

This state-of-the-art review was conducted using a systematic literature review method. Inclusive and exclusive criteria were identified and used to retrieve relevant literature from renowned literature databases. Shortlisted publications were analysed using the VOSviewer software and then critically reviewed to reveal the status quo of research in the subject area.

The review results show that DT has been mainly adopted to support decision-making on conservation approach and method selection, performance monitoring and prediction, maintenance strategies design and development, and energy evaluation and management. Although many researchers attempted to develop DT models for part of a heritage building at component or system level and test the models using real-life cases, their works were constrained by availability of empirical data. Furthermore, data capture approaches, data acquisition methods and modelling with multi-source data are found to be the existing challenges of DT application in HFM.

In a broader sense, this study contributes to the field of engineering, construction and architectural management by providing an overview of how DT has been applied to support management activities throughout the building life cycle. For the HFM practice, a DT-cum-heritage building information modelling (HBIM) framework was developed to illustrate how DT can be integrated with HBIM to facilitate future DT application in HFM. The overall implication of this study is that it reveals the potential of heritage DT in facilitating HFM in the urban development context.

The authors posit that one of the key enablers of the circular economy will be the digital transformation – in other words, “digitalization.” In this study, the authors examine and visualize the interaction of the circular economy and digitalization by using scientific publications. They explore possible synergies and future research avenues at this junction.

The authors first apply bibliometrics to explore and visualize the relationships between the circular economy and digitalization in the academic literature. Following the clustering of topics, they define key emerging factors for each cluster. Based on this analysis, they suggest future research avenues.

The authors find that there are four main clusters at the junction of circular economy and digitalization, including (1) sharing economy, (2) additive manufacturing, (3) business models and (4) industrial ecology and remanufacturing. They then dig deeper into these topics to better understand what factors would shape the future of the clusters. They conclude that sharing economy perspective and additive manufacturing may be enhanced by regulation-based and behavioral change-based approaches. Circular business models should be developed to maintain circularity in industry. Finally, digital manufacturing should be implemented within the framework of industrial ecology and remanufacturing principles to increase efficiency, productivity and traceability in the circular economy.

Digitalization offers significant potentials toward breakthrough sustainability by creating a circular economy. Hence, understanding the relationship between circular economy and digitalization is important to achieve sustainable development goals.

The study investigated the effect of big data analytics capabilities (BDACs) on reverse logistics (strategic and tactical) decisions and finally on remanufacturing performance.

The primary data were collected using a structured questionnaire and an online survey sent to South African manufacturing companies. The data were analysed using partial least squares based structural equation modelling (PLS–SEM) based WarpPLS 6.0 software.

The results indicate that data generation capabilities (DGCs) have a strong association with strategic reverse logistics decisions (SRLDs). Data integration and management capabilities (DIMCs) show a positive relationship with tactical reverse logistics decisions (TRLDs). Advanced analytics capabilities (AACs), data visualisation capabilities (DVCs) and data-driven culture (DDC) show a positive association with both SRLDs and TRLDs. SRLDs and TRLDs were found to have a positive link with remanufacturing performance.

The theoretical guided results can help managers to understand the value of big data analytics (BDA) in making better quality judgement of reverse logistics and enhance remanufacturing processes for achieving sustainability.

This research explored the relationship between BDA, reverse logistics decisions and remanufacturing performance. The study was practice oriented, and according to the authors’ knowledge, it is the first study to be conducted in the South African context.

The construction industry, being one of the main activities in the ever-demanding need for technology developments, sometimes falls short of other industries in terms of implementation. The adoption of Big Data (BD) in industries such as health and retail has had positive impacts in aspects such as decision-making processes and forecasting trends that allow planning some future business movements. Hence, the question of whether these results can be imitated in the construction industry. Therefore, this paper aims to address the level of awareness identified as a first step towards implementation of the BD concept within the construction industry in the Dominican Republic (DR).

As little to no information exist on the subject; the selected approach to perform this research was qualitative methodology; 21 semi-structured interviews were studied using situational awareness. Four levels of awareness were developed based on the Endsley’s Situation Awareness model.

The results showed that nearly 95% of the interviewees had either no knowledge or very basic awareness of the BD requirements or intermediate awareness, but only 5% had applied BD concepts in the construction industry.

This study shows the gaps that exist in the understanding and implementation of BD concepts in the DR construction industry. This paper establishes the need to develop continuous professional development programmes for construction professionals and a need to update curriculum in construction-related education.

This study reviews scholarly work in sustainable green logistics and remanufacturing (SGLR) and their subdisciplines, in combination with bibliometric, thematic and content analyses that provide a viewpoint on categorization and a future research agenda. This paper provides insight into current research trends in the subjects of interest by examining the most essential and most referenced articles promoting sustainability and climate-neutral logistics.

For the literature review, the authors extracted and sifted 2180 research and review papers for the period 2008–2023 from the Scopus database. The authors performed bibliometric and content analyses using multiple software programs such as Gephi, VOSviewer and R programming.

The SGLR papers can be grouped into seven clusters: (1) The circular economy facets; (2) Decarbonization of operations to nurture a climate-neutral business; (3) Green sustainable supply chain management; (4) Drivers and barriers of reverse logistics and the circular economy; (5) Business models for sustainable logistics and the circular economy; (6) Transportation problems in sustainable green logistics and (7) Digitalization of logistics and supply chain management.

In this review, fundamental ideas are established, research gaps are identified and multiple future research subjects are proposed. These propositions are categorized into three main research streams, i.e. (1) Digitalization of SGLR, (2) Enhancing scopes, sectors and industries in the context of SGLR and (3) Developing more efficient and effective climate-neutral and climate change-related solutions and promoting more environmental-related and sustainability research concerning SGLR. In addition, two conceptual models concerning SGLR and climate-neutral strategies are developed and presented for managers and practitioners to consider when adopting green and sustainability principles in supply chains. This review also highlights the need for academics to go beyond frameworks and build new techniques and instruments for monitoring SGLR performance in the real world.

This study provides an overview of the evolution of SGLR; it also clarifies concepts, environmental concerns and climate change practices, particularly those directed to supply chain management.