scholarly journals A Review on the Lifecycle Strategies Enhancing Remanufacturing

2021 ◽  
Vol 11 (13) ◽  
pp. 5937
Author(s):  
Raoul Fonkoua Fofou ◽  
Zhigang Jiang ◽  
Yan Wang
Keyword(s):  
Supply Chain ◽  
End Of Life ◽  
Circular Economy ◽  
Industrial Revolution ◽  
Life Stage ◽  
Remaining Useful Life ◽  
Research Papers ◽  
Design For Remanufacturing ◽  
Product Service ◽  
Useful Life

Remanufacturing is a domain that has increasingly been exploited during recent years due to its numerous advantages and the increasing need for society to promote a circular economy leading to sustainability. Remanufacturing is one of the main end-of-life (EoL) options that can lead to a circular economy. There is therefore a strong need to prioritize this option over other available options at the end-of-life stage of a product because it is the only recovery option that maintains the same quality as that of a new product. This review focuses on the different lifecycle strategies that can help improve remanufacturing; in other words, the various strategies prior to, during or after the end-of-life of a product that can increase the chances of that product being remanufactured rather than being recycled or disposed of after its end-of-use. The emergence of the fourth industrial revolution, also known as industry 4.0 (I4.0), will help enhance data acquisition and sharing between different stages in the supply chain, as well boost smart remanufacturing techniques. This review examines how strategies like design for remanufacturing (DfRem), remaining useful life (RUL), product service system (PSS), closed-loop supply chain (CLSC), smart remanufacturing, EoL product collection and reverse logistics (RL) can enhance remanufacturing. We should bear in mind that not all products can be remanufactured, so other options are also considered. This review mainly focuses on products that can be remanufactured. For this review, we used 181 research papers from three databases; Science Direct, Web of Science and Scopus.

scholarly journals Consumer’s Circular Behaviors in Relation to the Purchase, Extension of Life, and End of Life Management of Electrical and Electronic Products: A Review

2020 ◽  
Vol 12 (24) ◽  
pp. 10443
Author(s):  
Filippo Corsini ◽  
Natalia Marzia Gusmerotti ◽  
Marco Frey
Keyword(s):  
End Of Life ◽  
Circular Economy ◽  
Review Paper ◽  
Electronic Equipment ◽  
Electronic Products ◽  
Life Management ◽  
Weee Recycling ◽  
The World ◽  
Open Issue ◽  
Useful Life

Nowadays, management of electrical and electronic equipment (EEE) and the related waste electrical and electronic equipment (WEEE) is a growing concern around the world and clearly an open issue to tackle in order to move towards a more circular economy. The goal of this review paper is to analyze and summarize research conducted exploring behaviors connected with purchases, extension of useful life, and management of end of life of electrical and electronic equipment. The results highlight several research exploring the determinants of WEEE recycling behavior, also in relation with different practices (e.g., online recycling); on the other hand other typologies of behaviors are less analyzed in the literature (e.g., purchase of used EEE products, donation of EEE products, participation in WEEE takeback activities established by firm operating in this sector, etc.). Moreover, the results suggest that the theoretical model adopted in many studies reveals its usefulness to predict the determinist of such circular consumer’s behavior in relation to the purchase, extension of life, and end of life management of electrical and electronic products; however, in many cases, additional variables are needed to fully explain the behavior.

scholarly journals Survey on Deep Learning applied to predictive maintenance

2020 ◽  
Vol 10 (6) ◽  
pp. 5592
Author(s):  
Youssef Maher ◽  
Boujemaa Danouj
Keyword(s):  
Deep Learning ◽  
Industrial Revolution ◽  
State Of The Art ◽  
Remaining Useful Life ◽  
Predictive Maintenance ◽  
Traditional Learning ◽  
Maintenance Policy ◽  
Manufactured Products ◽  
Useful Life ◽  
Machine Health

Prognosis Health Monitoring (PHM) plays an increasingly important role in the management of machines and manufactured products in today’s industry, and deep learning plays an important part by establishing the optimal predictive maintenance policy. However, traditional learning methods such as unsupervised and supervised learning with standard architectures face numerous problems when exploiting existing data. Therefore, in this essay, we review the significant improvements in deep learning made by researchers over the last 3 years in solving these difficulties. We note that researchers are striving to achieve optimal performance in estimating the remaining useful life (RUL) of machine health by optimizing each step from data to predictive diagnostics. Specifically, we outline the challenges at each level with the type of improvement that has been made, and we feel that this is an opportunity to try to select a state-of-the-art architecture that incorporates these changes so each researcher can compare with his or her model. In addition, post-RUL reasoning and the use of distributed computing with cloud technology is presented, which will potentially improve the classification accuracy in maintenance activities. Deep learning will undoubtedly prove to have a major impact in upgrading companies at the lowest cost in the new industrial revolution, Industry 4.0.

scholarly journals Evaluating the Environmental Dimension of Material Efficiency Strategies Relating to the Circular Economy

2017 ◽  
Author(s):  
Stuart Walker ◽  
Nick Coleman ◽  
Peter Hodgson ◽  
Nicola Collins ◽  
Louis Brimacombe
Keyword(s):  
Supply Chain ◽  
Life Cycle ◽  
End Of Life ◽  
Circular Economy ◽  
Product Life Cycle ◽  
Life Cycle Management ◽  
Resource Scarcity ◽  
Environmental Benefits ◽  
Carbon Footprints ◽  
Material Efficiency

Material efficiency is a key element of new thinking to address the challenges of reducing impacts on the environment and of resource scarcity, whilst at the same time meeting service and functionality demands on materials. Directly related to material efficiency is the concept of the Circular Economy, which is based on the principle of optimising the utility embodied in materials and products through the life cycle. Whilst steel, as a result of high recycling rates, is one of the most ‘circular’ of all manufactured materials, significant opportunities for greater material efficiency exist, which are yet to be widely implemented. In the field of Life Cycle Management, Life Cycle Assessment (LCA) is commonly used to assess the environmental benefits of recovering and recycling materials through the manufacturing supply chain and at end-of-life. As well as containing information to calculate environmental impacts, LCA models also provide the flows of materials through the product life cycle and can also be used to quantify material efficiency and the circularity of a product system. Using an example taken from renewable energy generation, this paper explores the correlation between product circularity and the environmental case for strategies designed to improve material efficiency. An LCA-based methodology for accounting for the recovery and re-use of materials from the supply chain, and at end-of-life, is used as the basis for calculating the carbon footprint benefits of five material efficiency scenarios. Resulting carbon footprints were then compared with a number of proposed material circularity indicators. Two conclusions from this exercise were that i) LCA methodologies based around end-of-life approaches are well placed for quantifying the environmental benefits of material efficiency and circular economy strategies and ii) when applying indicators relating to the circularity of materials these should also be supported by LCA studies.

scholarly journals End-of-life modelling of buildings to support more informed decisions towards achieving circular economy targets

2020 ◽  
Vol 25 (11) ◽  
pp. 2122-2139 ◽  
Author(s):  
Sahar Mirzaie ◽  
Mihaela Thuring ◽  
Karen Allacker
Keyword(s):  
Life Cycle ◽  
End Of Life ◽  
Circular Economy ◽  
Life Stage ◽  
Life Cycle Stage ◽  
Construction Sector ◽  
Quality Factors ◽  
Product Environmental Footprint ◽  
Allocation Approach

Abstract Purpose Life cycle assessment (LCA) is an internationally accepted method to assess the environmental impacts of buildings. A major methodological challenge remains the modelling of the end-of-life stage of buildings and allocation of benefits and burdens between systems. Various approaches are hence applied in practice to date. This paper compares the two methods widely renowned in Europe—the EC product environmental footprint (PEF) method and the CEN standards: EN 15804+A1 and EN15978—and offers insights about their fitness for achieving circularity goals. Methods The EC PEF method and the CEN EN 15804/EN 15978 standards were methodologically analysed with a focus on the end-of-life modelling and allocation approach and were applied to a building case study. The EN 15804+A1 standard explains the guidelines but does not offer a modelling formula. Accordingly, this paper proposes a formula for the CEN standards using identical parameters as in the end-of-life circular footprint formula (CFF) of the EC PEF Guidance v6.3 to increase consistency among LCA studies. The calculation formulas were then applied to a newly constructed office building. A comparative analysis of both the implementation and results are described, and recommendations are formulated. Results In the absence of databases compatible with the two LCA methods and comprising all building products, the Ecoinvent datasets had to be remodelled to enable a comparative modular assessment. This proved to be a laborious process. The EC PEF method and CEN standards showed similar impacts and hotspots for the case study building. The module D in the CEN standards includes a significant share of positive impacts, but due to collective accounting, it does not clearly communicate these benefits. The summation of burdens and benefits in the EC PEF method reduces its transparency, while the allocation and quality factors enable this method to better capture the market realities and drive circular economy goals. Conclusions The construction sector and the LCI database developers are encouraged to create the missing LCA databases compatible with the modular and end-of-life allocation modelling requirements of both methods. More prescriptive and meticulous guidelines, with further harmonization between the EC PEF method and the CEN standards and their end-of-life allocation formula, would largely increase comparability and reliability of LCA studies and communications. To improve transparency, it is recommended to report the module D impacts per life cycle stage as per the CEN standards and the burdens and benefits separately for each life cycle stage as per the EC PEF method.

Dynamic Modeling and Wear-Based Remaining Useful Life Prediction of High Power Clutch Systems

2005 ◽  
Vol 48 (2) ◽  
pp. 208-217 ◽  
Author(s):  
Matthew Watson ◽  
Carl Byington ◽  
Douglas Edwards ◽  
Sanket Amin
Keyword(s):  
Dynamic Modeling ◽  
High Power ◽  
Life Prediction ◽  
Remaining Useful Life ◽  
Useful Life

Palliative care for end-of-life stage in oncologic disease

2018 ◽  
Vol 4 (45) ◽  
pp. 27
Author(s):  
Lucian MIRON ◽  
Alexandru C. Grigorescu
Keyword(s):  
Palliative Care ◽  
End Of Life ◽  
Life Stage

Remaining useful life estimation: a review on stochastic process-based approaches

2020 ◽  
Vol 14 ◽  
Author(s):  
Dangbo Du ◽  
Jianxun Zhang ◽  
Xiaosheng Si ◽  
Changhua Hu
Keyword(s):  
Stochastic Process ◽  
Health Management ◽  
Remaining Useful Life ◽  
Future Trends ◽  
Prognostics And Health Management ◽  
Inverse Gaussian ◽  
Life Estimation ◽  
Inverse Gaussian Process ◽  
Pros And Cons ◽  
Useful Life

Background: Remaining useful life (RUL) estimation is the central mission to the complex systems’ prognostics and health management. During last decades, numbers of developments and applications of the RUL estimation have proliferated. Objective: As one of the most popular approaches, stochastic process-based approach has been widely used for characterizing the degradation trajectories and estimating RULs. This paper aimed at reviewing the latest methods and patents on this topic. Methods: The review is concentrated on four common stochastic processes for degradation modelling and RUL estimation, i.e., Gamma process, Wiener process, inverse Gaussian process and Markov chain. Results: After a briefly review of these four models, we pointed out the pros and cons of them, as well as the improvement direction of each method. Conclusion: For better implementation, the applications of these four approaches on maintenance and decision-making are systematically introduced. Finally, the possible future trends are concluded tentatively.

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