This paper reviews the literature on the emerging digital technologies of Industry 4.0 (I4.0) focussed on the applicability of the Internet of Things (IoT), Virtual Reality (VR) and Augmented Reality (AR) in remanufacturing. Inspired by the frameworks developed to support exploration and realisation of I4.0 technologies for disassembly, the paper discusses the same emerging technologies in the wider context of remanufacturing. Trends and gaps have been identified from a value-creation perspective that encompasses the product to be remanufactured, the remanufacturing equipment and processes adopted and related organisation issues. Findings suggest there is a need to explore the connection of cyber-physical systems to the IoT to support smart remanufacturing, whilst aligning with evolving information and communication infrastructures and circular economy business models. The review highlights twenty-nine research topics that require attention to support this field.

PurposeTo 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.Design/methodology/approachThe 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.FindingsChanges 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.Originality/valueRemanufacturing 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.

Disassembly is a core procedure in remanufacturing. Disassembly is currently carried out mainly by human operators. It is important to reduce the labor content of dis-assembly through automation, to make remanufacturing more economically attractive. Threaded fastener removal is one of the most difficult disassembly tasks to be fully automated. This article presents a new method developed for automating the unfastening of screws. An electric nutrunner spindle with a geared offset adapter was fitted to the end of a collaborative robot. The position of a hexagonal headed screw in a fitted stage was known only approximately, and its orientation in the hole was unknown. The robot was programed to perform a spiral search motion to engage the tool onto the screw. A control strategy combining torque and position monitoring with active compliance was implemented. An existing robot cell was modified and utilized to demonstrate the concept and to assess the feasibility of the solution using a turbocharger as a disassembly case study. Note to Practitioners-Remanufacturing is known to generate substantial economic, social, and environmental benefits. Disassembly is the first operation in a remanufacturing process chain. Unfastening threaded parts ("unscrewing") is a common disassembly task accounting for approximately 40% of all disassembly activity. Like other disassembly tasks, often, unscrewing has to be carried out manually in remanufacturing due to difficulties caused by the variable and unpredictable condition of the end-of-life (EoL) products to be remanufactured. Automating unscrewing operations should reduce the labor content of disassembly, thus lowering remanufacturing costs and promoting the adoption of remanufacturing. This article proposes the use

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A digital twin is a “live” virtual replica of a sensorised component, product, process, human, or system. It accurately copies the entity being modelled by capturing information in real time, or near real time, from the entity, through embedded sensors and the Internet-of-Things. Many applications of digital twins in the manufacturing industry have been investigated. This article focuses on, and contributes to, the development of product digital twins to reduce the impact of quantity, quality, and demand uncertainties in remanufacturing. Starting from issues specific to remanufacturing, the article derives the functional requirements for a product digital twin for remanufacturing and proposes a Unified Modelling Language (UML) model of a generic asset to be remanufactured. The model is used in an example which highlights the need to translate existing knowledge and data into an integrated system to realise a product digital twin, capable of supporting remanufacturing process planning.

Remanufacturing is widely recognised as a key contributor to the circular economy (CE) as it extends the in-use life of products, but its synergy with Industry 4.0 (I4.0) has received little attention when compared to manufacturing. An agglomeration of I4.0 technologies and methodologies is reflected in the emerging digital twin (DT) concept, which has been identified as a life-extending enabler. This article captures the design and demonstration of a DT model that optimises remanufacturing planning using data from different instances in a product’s life cycle. The model uses a neural network for remaining useful life predictions and the Bees Algorithm for decision making within a DT. The model is validated using a real case study. The findings support the idea that intelligent tools within a DT can enhance decision-making if they have visibility and access to the product’s current status and reliable remanufacturing process information.

Multi-point forming uses forces applied to a tool, comprising of multiple pins set at different heights, to form sheet metal for panelling in white goods, automotive bodywork, aircraft frames and so on. The use of multiple pins allows for rapid change over and flexibility in the tool making it suitable for small-batch and prototype component manufacture. To explore the relationship between ‘springback’ of the sheet metal on release from the tool, and the applied pin force, it is first necessary to understand and measure the forming forces. This article presents a novel method of measuring forming forces on individual pins in a multi-point forming tool using fibre Bragg grating sensors, monitoring the elastic strain on the selected pins during the forming process. The operating principles behind forming force measurements using fibre Bragg gratings are introduced and a relationship is developed between springback in the formed part after the final unloading and the forming force as measured on selected individual pins under different compression ratios (30%, 40%, 50% and 60%) of the elastic cushion between the tips of the pins and the workpiece. Experiments were performed to validate the proposed measuring method, and results indicate that forming forces detected by the proposed method correlated well with the results obtained by numerical simulation. This suggests the proposed method has good potential for real-time measurement and monitoring of forming force distribution in multi-point forming tools during the forming process.

A digital twin is a “live” virtual replica of a sensorised component, product, process, human, or system. It accurately copies the entity being modelled by capturing information in real time or near real time from the entity through embedded sensors and the Internet-of-Things. Many applications of digital twins in manufacturing industry have been investigated. This article focuses on the development of product digital twins to reduce the impact of quantity, quality, and demand uncertainties in remanufacturing. Starting from issues specific to remanufacturing, the article derives the functional requirements for a product digital twin for remanufacturing and proposes a UML model of a generic asset to be remanufactured. The model has been demonstrated in a case study which highlights the need to translate existing knowledge and data into an integrated system to realise a product digital twin, capable of supporting remanufacturing process planning.