Generalized growth decision based on cascaded failure information: Maximizing the value of retired mechanical products

Wang, Lei; Guo, Yuyao; Zhang, Zelin; Xia, Xuhui; Cao, Jin

doi:10.1016/j.jclepro.2020.122176

Cited by 9 publications

(9 citation statements)

References 25 publications

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“…The gearbox is one of the most common and typical types of industrial equipment. On the one hand, most failure types of splitter gearboxes are minor problems on one component, whereas the rest of the main components function well [ 55 ]. On the other hand, the connection mode of components in the gearbox is relatively simple, which theoretically allows complete disassembly without any destructive processes.…”

Section: Computational Experimentsmentioning

confidence: 99%

A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing

Liu

Zhang

et al. 2023

Sensors

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Remanufacturing prolongs the life cycle and increases the residual value of various end-of-life (EoL) products. As an inevitable process in remanufacturing, disassembly plays an essential role in retrieving the high-value and useable components of EoL products. To disassemble massive quantities and multi-types of EoL products, disassembly lines are introduced to improve the cost-effectiveness and efficiency of the disassembly processes. In this context, disassembly line balancing problem (DLBP) becomes a critical challenge that determines the overall performance of disassembly lines. Currently, the DLBP is mostly studied in straight disassembly lines using single-objective optimization methods, which cannot represent the actual disassembly environment. Therefore, in this paper, we extend the mathematical model of the basic DLBP to stochastic parallel complete disassembly line balancing problem (DLBP-SP). A novel simulated annealing-based hyper-heuristic algorithm (HH) is proposed for multi-objective optimization of the DLBP-SP, considering the number of workstations, working load index, and profits. The feasibility, superiority, stability, and robustness of the proposed HH algorithm are validated through computational experiments, including a set of comparison experiments and a case study of gearboxes disassembly. To the best of our knowledge, this research is the first to introduce gearboxes as a case study in DLBP which enriches the research on disassembly of industrial equipment.

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Section: Computational Experimentsmentioning

confidence: 99%

A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing

Liu

Zhang

et al. 2023

Sensors

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“…This paper takes the manual gearbox produced by an automobile factory as an example (see Figure 9). The RMS integration platform formulates based on the generalized decisionmaking method of [17], as shown in Table 2.…”

Section: A． Proposedmentioning

confidence: 99%

“…RMS is an integrated service method, which facilitates service providers to implement remanufacturing services according to service requirements. Recently, RMS-related research has achieved preliminary results, such as comprehensive benefits of remanufacturing services [13] [14], selection of RMS knowledge resources [15], acquisition of remanufacturing service demand [16], and generalized growth decision of remanufacturing services [17].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Remanufacturing Service Resource Allocation for Generalized Growth of Retired Mechanical Products: Maximizing Matching Efficiency

et al. 2021

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Maximizing the residual value of retired products and reducing process consumption and resource waste are vital for Generalized Growth-oriented Remanufacturing Services (GGRMS). Under the GGRMS, the traditional product-oriented remanufacturing methods need to be changed: the products in GGRMS should be divided into multiple parts and different parts are treated in different ways to maximize residual value. However, this significantly increases the number of remanufacturing service activities and the complexity of the service activities network. Because a service activity may correspond to multiple service resources, the difficulty of service resources allocating significantly increase as the number of service activities under GGRMS increases. To improve the efficiency of resource matching, we proposed to first merge the redundant service activities in the service activity network, and then allocate the corresponding service resources. Therefore, we first used rough-fuzzy number and structural entropy weighting method to perform a coupling analysis on all service activities in the generalized growth scheme set and to merge redundant service activities. We then considered the interests of both the service providers and integrators and added flexible impact factors to establish a service resource optimization configuration model, and solved it with the Non-Dominated Sorting Genetic Algorithm (NSGA-Ⅱ). Finally, we, taking a retired manual gearbox as an experiment, optimized the service resource allocation for its generalized growth scheme set. The experimental results shown that the overall matching efficiency was increased by 74.56% after merging redundant service activities, showing that the proposed method is effective for the resource allocation of the generalized growth for complex single mechanical products, and can offer guidelines to the development of the RMS.

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“…A sustainable approach to the development and use of materials [1], remanufacturing is considered an essential part of green manufacturing [2]. Currently, remanufacturing research mainly focuses on schemes design, economic applicability and environmental protection [3][4][5]. Few studies have been undertaken on the remanufacturing process itself, which is the basis for remanufacturing implementation.…”

Section: Introductionmentioning

confidence: 99%

Parameter Identification of the Yoshida-Uemori Hardening Model for Remanufacturing

Xia

Gong

Wang

et al. 2021

Metals

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The deformation of plastics during production and service means that retired parts often possess different mechanical states, and this can directly affect not only the properties of remanufactured mechanical parts, but also the design of the remanufacturing process itself. In this paper, we describe the stress-strain relationship for remanufacturing, in particular the cyclic deformation of parts, by using the particle swarm optimization (PSO) method to acquire the Yoshida-Uemori (Y-U) hardening model parameters. To achieve this, tension-compression experimental data of AA7075-O, standard PSO, oscillating second-order PSO (OS-PSO) and variable weight PSO (VW-PSO) were acquired separately. The influence of particle numbers on the inverse analysis efficiency was studied based on standard PSO. Comparing the results of PSO variations showed that: (1) standard PSO is able to avoid local solutions and obtain Y-U model parameters to the same degree of precision as the OS-PSO; (2) by adjusting section weight, the VW-PSO could improve local fitting accuracy and adapt to asymmetric deformation; (3) by reducing particle numbers to a certain extent, the efficiency of analysis can be improved while also maintaining accuracy.

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Generalized growth decision based on cascaded failure information: Maximizing the value of retired mechanical products

Cited by 9 publications

References 25 publications

A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing

A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing

Optimal Remanufacturing Service Resource Allocation for Generalized Growth of Retired Mechanical Products: Maximizing Matching Efficiency

Parameter Identification of the Yoshida-Uemori Hardening Model for Remanufacturing

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