The manufacturing process for many large components of machines leads to a difference in their properties and performances based on changes in location. Functionally graded materials can meet these ...requirements and address the issue of generation and expansion of interface cracks. Ni204–dr60 gradient coatings were successfully fabricated using laser direct energy deposition (LDED). Microstructure mechanism evolution and microhardness of the gradient coating were comprehensively investigated. The change in the precipitated phase at the grain boundary and the intergranular zones resulted in a change in microstructural characteristics and also affected the microhardness distribution. The reinforced phase of the Ni204 → dr60 gradient zone from Ni204 to dr60 gradually precipitated and was rich in Mo and Nb phase, lath-shaped CrCsub.x phase, network-shaped CrCsub.x phase, block shape (Ni, Si) (C, B) phase, block CrCsub.x phase, and block Cr (B, C) phase. The gradient coating thus acts as a potential candidate to effectively solve the problem of crack generation at the interface of dr60 and the substrate.
Friction stir welding (FSW), a mature solid-state joining method, has become a revolutionary welding technique over the past two decades because of its energy efficiency, environmental friendliness ...and high-quality joints. FSW is highly efficient in the joining of Al alloys, Mg alloys, Ti alloys, polymers and other dissimilar materials. Recently, FSW has gained considerable scientific and technological attention in several fields, including aerospace, railway, renewable energy and automobile. To broaden the adoption of FSW in manufacturing fields, three inherent issues—back support, weld thinning and keyhole defects—must be addressed to ensure the structural integrity, safety and service life of the manufactured products. This review covers the recent progress on the control strategies for these inherent issues, which are basically divided into self-supported FSW, non-weld-thinning FSW and friction stir-based remanufacturing. Herein, the aim is to focus on the corresponding technical development, process parameters, metallurgical features and mechanical properties. Additionally, the challenges and future outlooks are emphasized systematically.
•Transition timed PN could simplify and clarify the modeling of remanufacturing.•The new rule in dynamic window search could improve the efficiency of A* algorithm.•The proposed heuristic would find ...optimal firing sequence while explore fewer nodes.•Cleaning process is the dominated contributor of the total energy consumption.
Scheduling has been extensively applied to remanufacturing for the organization of production activities, and it would directly influence the overall performance of the remanufacturing system. Since the conjunction of Petri net (PN) and artificial intelligence (AI) searching technique was demonstrated to be a promising approach to solve the scheduling problems in manufacturing systems, this study built a transition timed PN combined with heuristic A* algorithm to deal with the scheduling in remanufacturing. The PN was applied to the formulation of remanufacturing process, while the A* algorithm generated and searched for an optimal or near optimal feasible schedule through the reachability graph (RG). We took the high value-added cylinder block of engine as a research object to minimize the makespan of reprocessing a batch used components. This scheduling problem involved in batch and parallel processing machines, and the uncertain processing time and routes will complicate the scheduling problem. Three heuristics were designed to guide the search process through the RG in PN. To avoid state space explosion and select promising nodes, a new rule-based dynamic window was developed to improve the efficiency of the algorithm, and this rule was examined to outperform the conventional one. Under the determined scheduling strategy, the dynamic behavior of energy consumption rate during the processing time was simulated using PN tool, which would assist remanufacturers to develop potential strategies for energy efficiency improvement. Considering the uncertainty of processing time, the Monte Carlo simulation method was adopted to statistically analyze the distributions of makespan and total energy consumption, which would contribute to the comprehensive production scheduling and energy profile assessment for sustainable remanufacturing.
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.
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.
•The paper reviews the state-of-the-art of Industry 4.0 (I4.0) and remanufacturing.•Trends, gaps and findings in the application of I4.0 technologies are documented.•29 research areas are identified to optimise I4.0 technologies for remanufacturing.
Policy-makers are developing regulation policies to drive down carbon emissions from industries. Independent remanufacturers (IRs), which remanufacture recycled products/components/parts, must manage ...and evaluate economic costs generated by the production under future carbon emission regulations. We present three optimisation models to determine the remanufacturing quantity that maximises the total profits under three common carbon emission regulation policies: (a) mandatory carbon emissions capacity, (b) carbon tax and (c) cap and trade. These models include sales revenue, remanufacturing cost, disposal cost, inventory holding cost, shortage cost and carbon emission cost. The max-min approach is used to solve the models, which assume limited information on demand distribution. We investigate how the three regulation policies affect remanufacturing decision-making for IRs and we also solve some numerical examples where we vary the magnitudes of incentives, penalties and stringency of constraints to provide implications to policy-makers. The results indicate that remanufacturers should aim to improve yield rate to maximise the profit irrespective of the implemented carbon emissions policy. Policy-makers should prefer the carbon tax policy, if any of the other two policies must be performed, a remanufacturing discount such as a higher carbon emission cap or lower penalty should be implemented to better promote the development of remanufacturers.
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