Search Results (8)

Global ambitions for net-zero emissions and resource circularity are propelling industry from linear “make-use-dispose”models toward closed-loop value creation. Remanufacturing, which aims to restore end-of-life products to a “like-new” condition, plays a central role in this transition. However, its stochastic inputs and complex, multi-stage processes pose significant challenges to traditional production planning methods. This study delivers an integrated overview of remanufacturing scheduling by combining a systematic bibliometric review of 190 publications (2005–2025) with a critical synthesis of modelling approaches and enabling technologies. The bibliometric results reveal five thematic clusters and a 14% annual growth rate, highlighting a shift from deterministic, shop-floor-focused models to uncertainty-aware, sustainability-oriented frameworks. The scheduling problems are formalised to capture features arising from variable core quality, multi-phase precedence, and carbon reduction goals, in both centralised and cloud-based systems. Advances in human–robot disassembly, vision-based inspection, hybrid repair, and digital testing demonstrate feedback-rich environments that increasingly integrate planning and execution. A comparative analysis shows that, while mixed-integer programming and metaheuristics perform well in small static settings, dynamic and large-scale contexts benefit from reinforcement learning and hybrid decomposition models. Finally, future directions for dynamic, collaborative, carbon-conscious, and digital-twin-driven scheduling are outlined and investigated. Full article

Background: The global climate crisis has intensified the demand for sustainable solutions, positioning Reverse Logistics (RL) as a critical strategy for minimizing environmental impacts. Simultaneously, Industry 4.0 technologies are transforming RL operations by enhancing their collection, transportation, storage, sorting, remanufacturing, recycling, and disposal processes. Understanding the roles of these technologies is essential for improving efficiency and sustainability. Methods: This study employs a systematic literature review, following the PRISMA methodology, to identify key Industry 4.0 technologies applicable to RL. Publications from Scopus and Web of Science were analyzed, leading to the development of a theoretical framework linking these technologies to RL activities. Results: The findings highlight the fact that technologies like the Internet of Things (IoT), Artificial Intelligence (AI), Big Data Analytics, Cloud Computing, and Blockchain enhance RL by improving traceability, automation, and sustainability. Their application optimizes execution time, reduces operational costs, and mitigates environmental impacts. Conclusions: For the transportation and manufacturing sectors, integrating Industry 4.0 technologies into RL can streamline supply chains, enhance decision-making, and improve resource utilization. Smart tracking, predictive maintenance, and automated sorting systems reduce waste and improve operational resilience, reinforcing the transition toward a circular economy. By adopting these innovations, stakeholders can achieve economic and environmental benefits while ensuring regulatory compliance and long-term competitiveness. Full article

As additive manufacturing advances, it offers a cost-effective avenue for structurally repairing components. However, a challenge arises in the additive repair of suspended damaged surfaces, primarily due to gravitational forces. This can result in excessive deformation during the repair process, rendering the formation of proper repair impractical and leading to potential failure. In light of this rationale, conventional repair techniques are impractical for extensively damaged surfaces. Thus, this article proposes a novel repair methodology that is tailored to address large-area damage. Moreover, and departing from conventional practices involving the addition and subsequent subtraction of materials for precision machining, the proposed process endeavors to achieve more precise repair outcomes in a single operation. This paper introduces an innovative repair approach employing fused deposition modeling (FDM) to address the complexities associated with the repair of damaged polymer material parts. To mitigate geometric errors in the repaired structural components, beams with minimal deformation are printed using a compensation method. These beams then serve as supports for overlay printing. The paper outlines a methodology by which to determine the distribution of these supporting beams based on the shape of the damaged surface. A beam deformation model is established, and the printing trajectory of the compensated beam is calculated according to this model. Using the deformation model, the calculated deformation trajectories exhibit excellent fitting with the experimentally collected data, with an average difference between the two of less than 0.3 mm, validating the accuracy of the suspended beam deformation model. Based on the statistical findings, the maximum average deformation of the uncompensated sample is approximately 5.20 mm, whereas the maximum deformation of the sampled point after compensation measures around 0.15 mm. Consequently, the maximum deformation of the printed sample post-compensation is mitigated to roughly 3% of its pre-compensation magnitude. The proposed method in this paper was applied to the repair experiment of damaged curved surface components. A comparison was made between the point cloud data of the repaired surface and the ideal model of the component, with the average distance between them serving as the repair error metric. The mean distance between the point clouds of the repaired parts using the proposed repair strategy is 0.197 mm and the intact model surface is noticeably less than the mean distance corresponding to direct repair, at 0.830 mm. The repair error with compensatory support beams was found to be 76% lower than that without compensatory support beams. The surface without compensatory support beams exhibited gaps, while the surface with compensatory support beams appeared dense and complete. Experimental results demonstrate the effectiveness of the proposed method in significantly reducing the geometric errors in the repaired structural parts. The outcomes of the FDM repair method are validated through these experiments, affirming its practical efficacy. It is noteworthy that, although only PLA material was used in this study, the proposed method is general and effective for other polymer materials. This holds the potential to significantly reduce costs for the remanufacturing of widely used polymers. Full article

Sheet metal part manufacture is a precursor to various upstream assembly processes, including the manufacturing of mechanical and body parts of railcars, automobiles, ships, etc., in the transport manufacturing sector. The (re)manufacturing of railcars comprises a multi-tier manufacturing supply chain, mainly supported by local small and medium enterprises (SMEs), where siloed information leads to information disintegration between supplier and manufacturer. Technology spillovers in information technology (IT) and operational technology (OT) are disrupting traditional supply chains, leading to a sustainable digital economy, driven by new innovations and business models in manufacturing. This paper presents application of industrial DevOps by merging industry 4.0 technologies for collaborative and sustainable supply chains. A blockchain-based information system (IS) and a cloud manufacturing (CM) process system were integrated, for a supply chain management (SCM) system for the railcar manufacturer. A systems thinking methodology was used to identify the multi-hierarchical system, and a domain-driven design approach (DDD) was applied to develop the event-driven microservice architecture (MSA). The result is a blockchain-based cloud manufacturing as a service (BCMaaS) SCM system for outsourcing part production for boxed sheet metal parts. In conclusion, the BCMaaS system performs part provenance, traceability, and analytics in real time for improved quality control, inventory management, and audit reliability. Full article

While the Circular Economy in the built environment is often viewed in terms of recycling, more value can be obtained from buildings and physical components by their reuse, aided by stewardship and remanufacture, to ensure optimum performance capability. The use of cyber-physical information for online identification, examination and exchange of reusable components may improve their life-cycle management and circularity. To this end, a bi-directional data exchange system is established between physical building components and their virtual Building Information Modeling (BIM) counterparts, so that their life-cycle information—including history of ownership, maintenance record, technical specifications and physical condition—can be tracked, monitored and managed. The resultant prototype Cloud-based BIM platform is then adapted to support an ongoing product-service relationship between suppliers/providers and users/clients. A case study from a major new hospital, focusing upon an example of internal framed glazed systems, is presented for ”proof of concept” and to demonstrate the application of the proposed method. The result of the case study shows that, informed by the life-cycle data from the Cloud-BIM platform, a “lease with reuse” service option is able to deliver a lower total cost and less carbon intensity for each unit of frame-glazed module. This leads to a higher level of eco-efficiency, coupled with decreased consumption of material resources and reduced generation of waste. The research is expected to serve as a step forward in the era of Industry 4.0 and illuminate a more sophisticated way to manage building assets. Full article

Circular Economy is a means to ensure sustainable production and consumption patterns. However, it is still at an embryonic stage of implementation in manufacturing companies. Given its potential, the household appliance industry is a promising arena for the adoption of Circular Economy. Thus, this study aims to investigate and systematize how Circular Economy has been adopted in the household appliance industry, through a multiple case study research. Twenty cases are analyzed following a Research Framework, to map: (i) the Circular Economy 4R strategies of reduce, reuse, remanufacture and recycle; (ii) the Circular Economy levers, i.e., whether circular product design practices, servitized business models or supply chain management actions are undertaken; (iii) the role of digital 4.0 technologies as enablers; (iv) the benefits achieved. The analysis showed that servitized business models and supply chain management actions are widely used levers, while little attention is devoted to circular product design practices. Internet of Things (IoT), Big Data and Cloud emerged as powerful enablers of servitized business models. Two main patterns of Circular Economy adoption in the household appliance industry emerged from cases: incremental and radical adoption patterns. Incremental adoption patterns are based on design strategies focused on reduce and recycle, mainly led by manufacturers. Radical adoption patterns are instead focused on disruptive practices based on reuse, remanufacture, servitization and sharing, where digital 4.0 technologies serve as enablers. Overall, this exploratory research lays the foundation for a stronger and more systemic understanding of the adoption of Circular Economy in the household appliance industry. Full article

As an important energy conversion mechanism, centrifugal compressors play an important role in the national economy. The blade is one of the most critical components of the compressor. Damaged blades contain extremely high added value for remanufacturing. Thus, remanufacturing research on damaged and retired impeller/blade is getting more and more attention. Laser additive and milling subtractive composite remanufacturing technology is an effective means to achieve metal parts remanufacturing. In this paper, an advanced methodology for the remanufacturing of complex geometry and expensive components via reverse engineering, free-form surface modeling, laser additive repaired and machining is presented. The approach involves the integration of 3D non-contact digitization to obtain the point cloud data of damaged parts, adaptive free-form surface reconstruction to get the digital model of damage location, and laser additive manufacturing process containing slicing and path planning and subsequent multi-axis milling operation. The methodology has been successfully implemented on thin-curved centrifugal compressor blades. The results have shown that the composite remanufacturing method is an effective solution to realize the remanufacturing of damaged blades, and can be applied to the remanufacturing of other complicated parts. Full article

Reverse engineering (RE) is a powerful tool for generating a CAD model from the 3D scan data of a physical part that lacks documentation or has changed from the original CAD design of the part. The process of digitizing a part and creating a CAD model from 3D scan data is less time consuming and provides greater accuracy than manually measuring the part and designing the part from scratch in CAD. 3D optical scanning technology is one of the measurement methods which have evolved over the last few years and it is used in a wide range of areas from industrial applications to art and cultural heritage. It is also used extensively in the automotive industry for applications such as part inspections, scanning of tools without CAD definition, scanning the casting for definition of the stock (i.e. the amount of material to be removed from the surface of the castings) model for CAM programs and reverse engineering. In this study two scanning experiments of automotive applications are illustrated. The first one examines the processes from scanning to re-manufacturing the damaged sheet metal cutting die, using a 3D scanning technique and the second study compares the scanned point clouds data to 3D CAD data for inspection purposes. Furthermore, the deviations of the part holes are determined by using different lenses and scanning parameters. Full article