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学者姓名：刘碧玉
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Abstract ：
In a manufacturing/remanufacturing leasing system, quality of collected end-of-life leased products is uncertain due to lessees-differentiated demands. Quality affects remanufacturing cost and degradation level of remanufacturing equipment, which in turn affects production and maintenance decisions of equipment and carbon emissions during manufacturing/remanufacturing. A production and maintenance decision-making model is proposed to maximise lessor's profit by considering production, maintenance, carbon emission costs of manufacturing/remanufacturing equipment, inventory and maintenance costs of leased products. The optimal production quantity and preventive maintenance (PM) period for manufacturing/remanufacturing equipment, and remanufacturing cost threshold of leased products are obtained by solving the model with particle swarm optimisation algorithm. The impacts of lease period and PM period for leased products on the decision-makings, lessor's profit and carbon emissions are analysed. The results show: (1) as remanufacturing cost threshold rises, more remanufactured products shall replace new products, and PM period for remanufacturing equipment is significantly shortened; (2) lessor's profit increases first and then decreases as remanufacturing cost threshold increases, while carbon emissions during manufacturing/remanufacturing always decrease; (3) remanufacturing cost threshold shall be set within a moderate range to balance the production and maintenance costs of manufacturing/remanufacturing equipment; (4) extending the lease period and adopting the optimal PM period for the leased products can improve lessor's profit. Strengthening PM for manufacturing/remanufacturing equipment can reduce carbon emissions.
Keyword ：
Carbon emission Carbon emission Leasing Leasing Production and maintenance Production and maintenance Quality uncertainty Quality uncertainty Remanufacturing Remanufacturing
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| GB/T 7714 | Liu, Yanping , Liu, Biyu , Yang, Haidong et al. Optimal production and maintenance strategies for manufacturing/ remanufacturing leasing system considering uncertain quality and carbon emission [J]. | INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS , 2025 , 280 . |
| MLA | Liu, Yanping et al. "Optimal production and maintenance strategies for manufacturing/ remanufacturing leasing system considering uncertain quality and carbon emission" . | INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 280 (2025) . |
| APA | Liu, Yanping , Liu, Biyu , Yang, Haidong , Luo, Kai . Optimal production and maintenance strategies for manufacturing/ remanufacturing leasing system considering uncertain quality and carbon emission . | INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS , 2025 , 280 . |
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Evaluating and improving the performance of green development (GD) is essential for the government to formulate sustainable development policies. This study first analyzes the connotation and structures of GD from systemic perspective. Secondly, based on the two-stage eco-inefficiency (TE) model, non-cooperative theory, the correlation coefficient and standard deviation, and fuzzy set qualitative comparative analysis method (fsQCA), an improved integrated method, i.e., ITNE-fsQCA, is proposed. Thirdly, the validity and accuracy of ITNE-fsQCA are verified using the data from 30 Chinese provinces in 2020, and the results are compared with those obtained from TE and two-stage non-cooperative eco-inefficiency (TNE). Finally, the driving types and configuration pathway are discussed based on ITNE-fsQCA. The results show that: (1) compared to TE and TNE, ITNE-fsQCA helps to avoid the overestimation/underestimation of inefficiency in complex systems; (2) there are 8 configuration pathways that can effectively improve GD performance in 30 Chinese provinces in 2020, and these pathways are categorized into 4 driving types; (3) the enhancement of green technology innovation plays a crucial role in provincial sustainable development; and (4) the provincial GD inefficiencies in China are manifest various combinatorial forms. These findings provide the government with innovative ideas and methodologies for formulating sustainable development policies.
Keyword ：
Fuzzy set qualitative comparative analysis method Fuzzy set qualitative comparative analysis method Green development Green development Green technology innovation Green technology innovation Non-cooperative theory Non-cooperative theory Two-stage eco-inefficiency model Two-stage eco-inefficiency model
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| GB/T 7714 | Yang, Haidong , Zhang, Xiangle , Lao, Quanchu et al. How to accurately evaluate and effectively improve the performance of provincial green development in China? An improved integrated method [J]. | ENERGY POLICY , 2025 , 198 . |
| MLA | Yang, Haidong et al. "How to accurately evaluate and effectively improve the performance of provincial green development in China? An improved integrated method" . | ENERGY POLICY 198 (2025) . |
| APA | Yang, Haidong , Zhang, Xiangle , Lao, Quanchu , Liu, Biyu . How to accurately evaluate and effectively improve the performance of provincial green development in China? An improved integrated method . | ENERGY POLICY , 2025 , 198 . |
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After the expiration of each lease, lessees may return leased equipment on schedule, renew the lease or purchase it according to the equipment status and their demands. By considering lessees' uncertain options and equipment status difference, the pricing and inventory decision-makings of leased equipment are explored. A mixed-integer nonlinear programming model by maximising the net present value of lessor's profit is presented with respect to constraints like rental revenue, manufacturing, lessees' credit check, transportation, maintenance, upgrade and inventory costs. The rental price and inventory decisions are obtained by solving the problem with a particle swarm optimisation algorithm. We also analyse the impacts of purchasing cost of old equipment from a third-party supplier on lessor's inventory, renewal price or purchasing price of leased equipment on lessees' options and lessor's profit. The results show: (1) with the extension of lease period, the rental price increases while the growth rate decreases; (2) the maintenance cost accounts for about 20% of total cost, and the preventive maintenance strategy can reduce excess maintenance cost as lease period increases; (3) the lessor shall set moderate renewal price discount coefficient and purchasing price coefficient, and analyse purchasing cost of old equipment to manage inventory timely.
Keyword ：
leasing leasing lessees' options lessees' options particle swarm optimisation algorithm particle swarm optimisation algorithm preventive maintenance preventive maintenance Pricing and inventory Pricing and inventory
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| GB/T 7714 | Liu, Yanping , Liu, Biyu , Yang, Haidong et al. Optimal pricing and inventory strategies for leased equipment considering lessees' options [J]. | INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH , 2024 , 62 (19) : 7261-7278 . |
| MLA | Liu, Yanping et al. "Optimal pricing and inventory strategies for leased equipment considering lessees' options" . | INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 62 . 19 (2024) : 7261-7278 . |
| APA | Liu, Yanping , Liu, Biyu , Yang, Haidong , Luo, Kai . Optimal pricing and inventory strategies for leased equipment considering lessees' options . | INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH , 2024 , 62 (19) , 7261-7278 . |
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Periodic payment for leased equipment may lead to capital constraint for lessors. In view of preventive maintenance (PM) strategy and lessees' options, the impact of different financing modes on lessor's pricing decisionmaking for leased equipment is studied. By considering the impact of age and usage on PM strategy and lessees' revenue, and lessees -different options to return, renew or purchase leased equipment after the lease expires, a game -theoretic model with respect to advance payment, bank loan and mixed financing modes is presented. The lessor's optimal pricing and financing strategies, as well as lessees' options are obtained by using noncooperative game, cooperative game and transfer -payment contract. The results show: (1) with the increase of bargaining level, the periodic rental price decreases; Under non -cooperative game, lessees renew the equipment first and then purchase it, while under cooperative game lessees always renew the lease. The lessor can motivate lessees to participate in cooperation through appropriate transfer -payment contract; (2) as the advance payment discount increases, the lessor shifts from advance payment to bank loan financing mode under non -cooperative game, while always adopts a financing mode including advance payment under cooperative game. Both leasing parties accept the advance payment financing mode only when the advance payment discount is within a certain range; (3) the increased usage of leased equipment brings larger PM and corrective maintenance (CM) burden to the lessor, which affects lessees' options and both leasing parties' profits. The lessor shall measure the PM and CM costs of leased equipment to maximize the profit.
Keyword ：
Game-theoretic Game-theoretic Leasing Leasing Lessees' options Lessees' options Preventive maintenance Preventive maintenance Pricing and financing Pricing and financing
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| GB/T 7714 | Liu, Yanping , Liu, Biyu , Yang, Haidong . Optimal pricing and financing strategies for leased equipment considering maintenance and lessees' options [J]. | INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS , 2024 , 269 . |
| MLA | Liu, Yanping et al. "Optimal pricing and financing strategies for leased equipment considering maintenance and lessees' options" . | INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 269 (2024) . |
| APA | Liu, Yanping , Liu, Biyu , Yang, Haidong . Optimal pricing and financing strategies for leased equipment considering maintenance and lessees' options . | INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS , 2024 , 269 . |
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For a capital-constrained manufacturer, in the context of carbon reduction, whether products should be sold or leased and which financing mode is more beneficial are usually debated. By considering Carbon Emission Permits Repurchase Financing (CEPRF) and Green Credit Financing (GCF), the optimal decision-making models with different strategies are presented. The Karush-Kuhn-Tucker theorem is applied and the results are compared. Meanwhile, the influence of initial capital and interest rates on the manufacturer's decision-makings, profits, and environment are explored. The results show that: under the selling strategy, when the initial capital is small, GCF is better for the manufacturer; otherwise, CEPRF is better; under the leasing strategy, both optimal production and carbon reduction investment with CEPRF are lower than that with GCF, but their profits are higher. With CEPRF, the leasing strategy would bring more economic and environmental benefits to the manufacturer; with GCF, the selling strategy would result in more economic and environment benefits.
Keyword ：
capital constraint capital constraint carbon reduction investment decision carbon reduction investment decision financing mode financing mode leasing and selling leasing and selling production decision production decision
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| GB/T 7714 | Liu, Biyu , Shi, Yaling , Yang, Haidong . Optimal production and carbon reduction investment decision for manufacturers with leasing-selling strategies considering financing [J]. | INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH , 2024 , 32 (5) : 3168-3196 . |
| MLA | Liu, Biyu et al. "Optimal production and carbon reduction investment decision for manufacturers with leasing-selling strategies considering financing" . | INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 32 . 5 (2024) : 3168-3196 . |
| APA | Liu, Biyu , Shi, Yaling , Yang, Haidong . Optimal production and carbon reduction investment decision for manufacturers with leasing-selling strategies considering financing . | INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH , 2024 , 32 (5) , 3168-3196 . |
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The burgeoning field of the Industrial Internet of Things (IIoT) necessitates advanced fault diagnosis methods capable of navigating the dual challenges of high-predictive accuracy and the constraints of edge computing environments. Our study introduces Wave-ConvNeXt, a novel fault diagnosis model that seamlessly integrates the state-of-the-art ConvNeXt architecture with Wavelet Transform. This innovative model stands out for its lightweight design yet delivers exceptional accuracy in fault diagnosis. In Wave-ConvNeXt, we re-engineer the ConvNeXt model for IIoT applications by adopting 1-D convolution, tailored for processing high-frequency, nonperiodic inputs. This adaptation is complemented by replacing the traditional "patchify" layer with a Wavelet transform layer, which simplifies input signals into subsignals, thereby easing learning complexities and diminishing the dependence on elaborate deep architectures. Further enhancing this model, we incorporate a squeeze-and-excitation module, enriching its ability to prioritize channelwise feature relevance, akin to self-attention mechanisms. This integration is rigorously validated through an ablation study. Wave-ConvNeXt epitomizes a holistic approach, enabling an end-to-end optimization of feature learning and fault classification. Our empirical analysis on two real-world IIoT data sets demonstrates Wave-ConvNeXt's superiority over existing models. It not only elevates prediction accuracy but also significantly curtails computational complexity. Additionally, our exploration into the impact of various mother wavelets reveals the effectiveness of using wavelet basis functions with smaller support, bolstering diagnostic precision. The source code of Wave-ConvNeXt is available at https://github.com/leviszhang/waveConvNeXt.
Keyword ：
Computational efficiency Computational efficiency ConvNeXt architecture ConvNeXt architecture fault diagnosis fault diagnosis Industrial Internet of Things (IIoT) Industrial Internet of Things (IIoT) wavelet transform wavelet transform
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| GB/T 7714 | Zhang, Liangwei , Lin, Jing , Yang, Zhe et al. Wave-ConvNeXt: An Efficient and Precise Fault Diagnosis Method for IIoT Leveraging Tailored ConvNeXt and Wavelet Transform [J]. | IEEE INTERNET OF THINGS JOURNAL , 2024 , 11 (13) : 23096-23109 . |
| MLA | Zhang, Liangwei et al. "Wave-ConvNeXt: An Efficient and Precise Fault Diagnosis Method for IIoT Leveraging Tailored ConvNeXt and Wavelet Transform" . | IEEE INTERNET OF THINGS JOURNAL 11 . 13 (2024) : 23096-23109 . |
| APA | Zhang, Liangwei , Lin, Jing , Yang, Zhe , Shao, Haidong , Liu, Biyu , Li, Chuan . Wave-ConvNeXt: An Efficient and Precise Fault Diagnosis Method for IIoT Leveraging Tailored ConvNeXt and Wavelet Transform . | IEEE INTERNET OF THINGS JOURNAL , 2024 , 11 (13) , 23096-23109 . |
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Flood susceptibility assessment is the premise and foundation to prevent flood disaster events effectively. To accurately assess urban flood susceptibility (UFS), this study first analyzes the advantages and disadvantages of multi-layer perceptron (MLP), and light gradient boosting machine (LightGBM), and designs a new integrated machine learning method by combining logistic regression (LR) method, i.e., LG-MLP-LR. Then, we verify the performance of LG-MLP-LR by taking the flood disaster events in Fuzhou from 2013 to 2016 as example and analyze the contribution of flood conditioning factors by calculating the SHapley Additive exPlanations values. Finally, the assessment results are compared with MLP, LightGBM, XG-MLP-LR, and CB-MLP-LR. The results show that (1) the selected flood conditioning factors can accurately depict the UFS of the study area; (2) compared with MLP, LightGBM, XG-MLP-LR, and CB-MLP-LR, the assessment results by LG-MLP-LR have higher average accuracy (94.950%) and higher average AUC (98.813%); (3) the factors affecting the occurrence and damage degree of flood disaster events in Fuzhou from 2013 to 2016 were elevation, topographic wetness index, maximum one-day rainfall, and stream power index, respectively. This study provides a new idea and method for the effective prevention and control of flood disasters in cities.
Keyword ：
Light gradient boosting machine Light gradient boosting machine Logistic regression Logistic regression Multi-layer perceptron Multi-layer perceptron Shapley Additive exPlanations Shapley Additive exPlanations Urban flood susceptibility Urban flood susceptibility
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| GB/T 7714 | Yang, Haidong , Zou, Ting , Liu, Biyu . Assessment of urban flood susceptibility based on a novel integrated machine learning method [J]. | ENVIRONMENTAL MONITORING AND ASSESSMENT , 2024 , 197 (1) . |
| MLA | Yang, Haidong et al. "Assessment of urban flood susceptibility based on a novel integrated machine learning method" . | ENVIRONMENTAL MONITORING AND ASSESSMENT 197 . 1 (2024) . |
| APA | Yang, Haidong , Zou, Ting , Liu, Biyu . Assessment of urban flood susceptibility based on a novel integrated machine learning method . | ENVIRONMENTAL MONITORING AND ASSESSMENT , 2024 , 197 (1) . |
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Fault detection in 3D printers is crucial for safety and quality assurance, emphasizing proactive prediction over reactive rectification based on manufacturing factors. Presently, most detection techniques rely on shallow models with limited representational capabilities, necessitating manual feature extraction from the captured signals. This manual process is not only cumbersome and potentially costly but often requires intricate domain specific knowledge. Additionally, these handcrafted features might not optimally distinguish between normal and faulty samples, potentially reducing prediction accuracy. In this study, we introduce an end-to-end approach using the Deep Support Vector Data Description model for fault detection in 3D printers. This design inherently facilitates automatic feature learning, where the features are synergistically optimized for fault detection. Our experiments leverage magnetic field signals for fault detection in 3D printers, using 1D convolutional layers to discern temporal signal patterns and wide kernels in the initial layer to mitigate high-frequency noise. Furthermore, our model can be easily adapted to integrate multi-channel signals for enhanced accuracy. Evaluations on real-world data from a delta 3D printer underscore the superiority of our method compared to existing alternatives.
Keyword ：
3D printers 3D printers Deep learning Deep learning End-to-end learning End-to-end learning Fault detection Fault detection Product quality assurance Product quality assurance Support Vector Data Description Support Vector Data Description
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| GB/T 7714 | Zhang, Liangwei , Lin, Jing , Shao, Haidong et al. An unsupervised end-to-end approach to fault detection in delta 3D printers using deep support vector data description [J]. | JOURNAL OF MANUFACTURING SYSTEMS , 2023 , 72 : 214-228 . |
| MLA | Zhang, Liangwei et al. "An unsupervised end-to-end approach to fault detection in delta 3D printers using deep support vector data description" . | JOURNAL OF MANUFACTURING SYSTEMS 72 (2023) : 214-228 . |
| APA | Zhang, Liangwei , Lin, Jing , Shao, Haidong , Yang, Zhe , Liu, Biyu , Li, Chuan . An unsupervised end-to-end approach to fault detection in delta 3D printers using deep support vector data description . | JOURNAL OF MANUFACTURING SYSTEMS , 2023 , 72 , 214-228 . |
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Lessors are responsible for equipment maintenance during the lease period. The usage rate of these equipment affects their failures, reliability and decision-making on maintenance strategy. For some leased equipment, such as those producing seasonal products, the usage rate varies. However, conventional approaches usually set usage rate as a constant. Different from the existing literature, this work considers the variation of usage rate, and proposes a multi-phase preventive maintenance (PM) decision model to determine the PM times and degrees at different phases. The goal is to minimize lessors' lease service cost by balancing corrective maintenance (CM) cost, PM cost and penalty cost during the lease period. In this model, an age correspondence framework is applied to characterize the variation of usage rate at different phases. An accelerated failure time model and an age reduction model are adopted to capture the effect of variable usage rate and imperfect PM on the equipment's reliability. To verify the effectiveness of the proposed model, it is contrasted with a PM decision model with average usage rate. The impact of unit PM cost, CM cost, and penalty cost on maintenance strategy is discussed by numerical examples. Managerial insights for maintenance strategy are provided for lessors. The results indicate that the proposed approach considering varied usage rate can change the optimal PM times and degrees, and consequently lead to a lower lease service cost than conventional approaches using average usage rate; lessors need to enhance PM capability and reduce PM cost.
Keyword ：
Failure penalty Failure penalty Leased equipment Leased equipment Multi -phase Multi -phase Preventive maintenance Preventive maintenance Usage rate variation Usage rate variation
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| GB/T 7714 | Liu, Biyu , Chen, Ting , Yang, Haidong et al. Multi-phase preventive maintenance strategy for leased equipment considering usage rate variation [J]. | COMPUTERS & INDUSTRIAL ENGINEERING , 2023 , 185 . |
| MLA | Liu, Biyu et al. "Multi-phase preventive maintenance strategy for leased equipment considering usage rate variation" . | COMPUTERS & INDUSTRIAL ENGINEERING 185 (2023) . |
| APA | Liu, Biyu , Chen, Ting , Yang, Haidong , Zhang, Liangwei . Multi-phase preventive maintenance strategy for leased equipment considering usage rate variation . | COMPUTERS & INDUSTRIAL ENGINEERING , 2023 , 185 . |
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Innovations in technology have made the structure of leased equipment more complex, which poses a challenge for lessors to develop maintenance policies. In view of the situation that the single periodic preventive maintenance (PM) policy during leasing activities may cause excessive or insufficient maintenance on the leased equipment, a condition-based maintenance (CBM) policy considering hybrid preventive maintenance (HPM) and periodic inspections is proposed. This policy contains imperfect preventive maintenance (IPM), preventive replacement (PR) and corrective maintenance (CM). The lessor can decide to take maintenance actions depending on whether the state of the equipment reaches the corresponding maintenance threshold. The warranty period of the leased equipment is also considered. To seal the deal, the lessor will give a discount on the rental to cover the CM costs and penalties out of the warranty period. To minimize the lessor's costs, we propose a CBM decision model to determine the optimal inspection period, PM threshold and PR period. The results show that the HPM policy can reduce leasing costs by about 5 -15 % for the lessor compared to that of the single PM policy.
Keyword ：
Condition-based maintenance Condition-based maintenance Hybrid preventive maintenance Hybrid preventive maintenance Leased equipment Leased equipment Periodic inspection Periodic inspection Warranty period Warranty period
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| GB/T 7714 | Liu, Biyu , Pang, Jie , Yang, Haidong et al. Optimal condition-based maintenance policy for leased equipment considering hybrid preventive maintenance and periodic inspection [J]. | RELIABILITY ENGINEERING & SYSTEM SAFETY , 2023 , 242 . |
| MLA | Liu, Biyu et al. "Optimal condition-based maintenance policy for leased equipment considering hybrid preventive maintenance and periodic inspection" . | RELIABILITY ENGINEERING & SYSTEM SAFETY 242 (2023) . |
| APA | Liu, Biyu , Pang, Jie , Yang, Haidong , Zhao, Yilin . Optimal condition-based maintenance policy for leased equipment considering hybrid preventive maintenance and periodic inspection . | RELIABILITY ENGINEERING & SYSTEM SAFETY , 2023 , 242 . |
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