Smart Remanufacturing

A special issue of Automation (ISSN 2673-4052).

Deadline for manuscript submissions: 31 July 2024 | Viewed by 890

Special Issue Editors

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School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China
Interests: network digital manufacturing; CNC technology; mechatronics
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Guest Editor
School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China
Interests: nonlinear systems theory; signal processing; industrial/rehabilitation robots

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Guest Editor
School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China
Interests: sustainable manufacturing; man-machine integration and collaborative manufacturing; manufacturing intelligence and manufacturing services; Information physics production system; sensor network; digital twin technology

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Guest Editor
School of Industrial Engineering, University of Castilla-La Mancha, Ciudad Real, Spain
Interests: optimization models for industrial processes; optimization of industrial processes for remanufacturing in the circular economy environment; techno-economic analysis of renewable energy generation plants, innovation, and sustainability

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Guest Editor
Dipartimento di Ingegneria—Università della Campania “Luigi Vanvitelli”, Via Roma, 29, 81031 Aversa, CE, Italy
Interests: industrial manufacturing system design and optimization; industrial production management and optimization
Special Issues, Collections and Topics in MDPI journals

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Department of Industrial Engineering, University of Salerno, 84084 Fisciano, Italy
Interests: remanufacturing; industrial system design and optimization; ergonomic
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Guest Editor
Chance Professor of Engineering, School of Engineering, The University of Birmingham, Birmingham B15 2TT, UK
Interests: micro manufacturing; control systems; robotics; intelligent systems

Special Issue Information

Dear Colleagues,

Remanufacturing is the process of returning a product that has reached the end of its service life to a condition at least as good as that of the original product. Remanufacturing is part of a circular economy aimed at minimising waste and conserving raw materials and energy, while also cutting greenhouse gas emissions and landfill space requirements. By saving input costs, remanufacturing can yield more affordable products and wider profit margins at the same time. Thus, remanufacturing is good for consumers and producers as well as for the environment; in this sense, remanufacturing is intrinsically smart manufacturing. However, from the technology point of view, the current state of much of the remanufacturing industry can be said to be relatively backward. While many original equipment manufacturers have embraced modern solutions such as digital twins, cyber–physical systems, artificial intelligence, smart sensors, big data and autonomous collaborative robots, remanufacturers tend to utilise tools and techniques from the last century.

This Special Issue will look at how smart manufacturing technologies or any other advanced technologies can be directly employed or adapted to make remanufacturing technologically smarter.  

Prof. Dr. Zude Zhou
Prof. Dr. Quan Liu
Prof. Dr. Wenjun Xu
Prof. Dr. F. Javier Ramírez
Dr. Marcello Fera
Dr. Mario Caterino
Prof. Dr. Duc Truong Pham
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Automation is an international peer-reviewed open access quarterly journal published by MDPI.

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Keywords

  • human–robot collaborative disassembly of cores
  • smart sorting and inspection of components
  • automated product re-assembly
  • flexible tooling for assembly and disassembly
  • intelligent disassembly planning and autonomous re-planning
  • product condition monitoring and remaining useful life prediction
  • digital twin modelling and control of remanufacturing operations
  • case studies in smart remanufacturing

Published Papers (1 paper)

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Research

18 pages, 16454 KiB  
Article
Robotic Disassembly Platform for Disassembly of a Plug-In Hybrid Electric Vehicle Battery: A Case Study
by Mo Qu, D. T. Pham, Faraj Altumi, Adeyemisi Gbadebo, Natalia Hartono, Kaiwen Jiang, Mairi Kerin, Feiying Lan, Marcel Micheli, Shuihao Xu and Yongjing Wang
Automation 2024, 5(2), 50-67; https://doi.org/10.3390/automation5020005 - 01 Apr 2024
Viewed by 522
Abstract
Efficient processing of end-of-life lithium-ion batteries in electric vehicles is an important and pressing challenge in a circular economy. Regardless of whether the processing strategy is recycling, repurposing, or remanufacturing, the first processing step will usually involve disassembly. As battery disassembly is a [...] Read more.
Efficient processing of end-of-life lithium-ion batteries in electric vehicles is an important and pressing challenge in a circular economy. Regardless of whether the processing strategy is recycling, repurposing, or remanufacturing, the first processing step will usually involve disassembly. As battery disassembly is a dangerous task, efforts have been made to robotise it. In this paper, a robotic disassembly platform using four industrial robots is proposed to automate the non-destructive disassembly of a plug-in hybrid electric vehicle battery pack into modules. This work was conducted as a case study to demonstrate the concept of the autonomous disassembly of an electric vehicle battery pack. A two-step object localisation method based on visual information is used to overcome positional uncertainties from different sources and is validated by experiments. Also, the unscrewing system is highlighted, and its functions, such as handling untightened fasteners, loosening jammed screws, and changing the nutrunner adapters with square drives, are detailed. Furthermore, the time required for each operation is compared with that taken by human operators. Finally, the limitations of the platform are reported, and future research directions are suggested. Full article
(This article belongs to the Special Issue Smart Remanufacturing)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Robotic Disassembly Platform for Disassembly of a Plug-In Hybrid Electric Vehicle Battery: a Case Study
Authors: Mo Qu, D. T. Pham, Faraj Altumi, Adeyemisi Gbadebo, Natalia Hartono, Kaiwen Jiang, Mairi Kerin, Feiying Lan, Marcel Micheli, Shuihao Xu, and Yongjing Wang
Affiliation: University of Birmingham
Abstract: Efficient processing of end-of-life lithium-ion batteries of electric vehicles is important and a pressing challenge for a circular economy. Regardless of whether the processing strategy is recycling, repurposing or remanufacturing, the first processing step would usually involve disassembly. As battery disassembly is a dangerous task, efforts have been made to robotise it. In this paper, a robotic disassembly platform using four industrial robots is proposed to automate the non-destructive disassembly of a plug-in hybrid electric vehicle battery pack into modules. The work was conducted as a case study to demonstrate the concept of autonomous disassembly of an electric vehicle battery pack. A two-step object localisation method based on visual information is used to overcome positional uncertainties from different sources and is validated by experiments. Also, the unscrewing system is highlighted, and its functions, such as handling untightened fasteners, loosening jammed screws, and changing the nutrunner adapters with square drives, are detailed. Furthermore, the time required for each operation is compared with that taken by human operators. Finally, the limitations of the platform are reported and future research directions are suggested.

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