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The rapid development of technology and innovation has made the performance of the new-generation machinery generally better than that of retired machinery. Simply using remanufacturing technology to bring retired machinery back into specifications of previous life will lead to reduced demands from consumers because of the out-of-date functioning remanufactured products. This technology gap (TG) is rarely considered in existing researches. This paper proposes an emergy based sustainability assessment model for retired machinery to solve this problem. Firstly, the TG between retired and new-generation machinery is quantified as functional devaluation from the perspectives of energy, environment and society through emergy theory. Secondly, the added value of retired machinery is derived from the evaluation of remanufacturing cost. Among them, the remanufacturing cost is predicted based on the BP Neural Networks. Then, this paper combines the functional devaluation and added value of retired mechanery to calculate the sustainability indicator. Finally, the feasibility of this study was verified by the sustainability evaluation of the WD615.50 diesel engine, and the results show that the WD615.50 diesel engine has no potential for re-service.
Xugang Zhang; Lu Xu; Hua Zhang; Zhigang Jiang; Yan Wang. Emergy based sustainability evaluation model for retired machineries integrating energy, environmental and social factors. Energy 2021, 235, 121331 .
AMA StyleXugang Zhang, Lu Xu, Hua Zhang, Zhigang Jiang, Yan Wang. Emergy based sustainability evaluation model for retired machineries integrating energy, environmental and social factors. Energy. 2021; 235 ():121331.
Chicago/Turabian StyleXugang Zhang; Lu Xu; Hua Zhang; Zhigang Jiang; Yan Wang. 2021. "Emergy based sustainability evaluation model for retired machineries integrating energy, environmental and social factors." Energy 235, no. : 121331.
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.
Raoul Fofou; Zhigang Jiang; Yan Wang. A Review on the Lifecycle Strategies Enhancing Remanufacturing. Applied Sciences 2021, 11, 5937 .
AMA StyleRaoul Fofou, Zhigang Jiang, Yan Wang. A Review on the Lifecycle Strategies Enhancing Remanufacturing. Applied Sciences. 2021; 11 (13):5937.
Chicago/Turabian StyleRaoul Fofou; Zhigang Jiang; Yan Wang. 2021. "A Review on the Lifecycle Strategies Enhancing Remanufacturing." Applied Sciences 11, no. 13: 5937.
Numerous pathways and narratives have been developed to shed light on how society could transform its production systems in line with the aspirational targets of the Paris Agreement and Sustainable Development Goals
Wei Cai; Zhigang Jiang; Conghu Liu; Yan Wang. Special Issue on “Green Technologies for Production Processes”. Processes 2021, 9, 1022 .
AMA StyleWei Cai, Zhigang Jiang, Conghu Liu, Yan Wang. Special Issue on “Green Technologies for Production Processes”. Processes. 2021; 9 (6):1022.
Chicago/Turabian StyleWei Cai; Zhigang Jiang; Conghu Liu; Yan Wang. 2021. "Special Issue on “Green Technologies for Production Processes”." Processes 9, no. 6: 1022.
Reverse logistics (RL) is closely related to remanufacturing and could have a profound impact on the remanufacturing industry. Different from sustainable development which is focused on economy, environment and society, circular economy (CE) puts forward more requirements on the circularity and resource efficiency of manufacturing industry. In order to select the best reverse logistics provider for remanufacturing, a multicriteria decision-making (MCDM) method considering the circular economy is proposed. In this article, a circularity dimension is included in the evaluation criteria. Then, analytic hierarchy process (AHP) is used to calculate the global weights of each criterion, which are used as the parameters in selecting RL providers. Finally, technique for order of preference by similarity to ideal solution (TOPSIS) is applied to rank reverse logistics providers with three different modes. A medium-sized engine manufacturer in China is taken as a case study to validate the applicability and effectiveness of the proposed framework.
Xumei Zhang; Zhizhao Li; Yan Wang; Wei Yan. An Integrated Multicriteria Decision-Making Approach for Collection Modes Selection in Remanufacturing Reverse Logistics. Processes 2021, 9, 631 .
AMA StyleXumei Zhang, Zhizhao Li, Yan Wang, Wei Yan. An Integrated Multicriteria Decision-Making Approach for Collection Modes Selection in Remanufacturing Reverse Logistics. Processes. 2021; 9 (4):631.
Chicago/Turabian StyleXumei Zhang; Zhizhao Li; Yan Wang; Wei Yan. 2021. "An Integrated Multicriteria Decision-Making Approach for Collection Modes Selection in Remanufacturing Reverse Logistics." Processes 9, no. 4: 631.
Design for Remanufacturing (DfRem) plays an important role in remanufacturing, which promotes the product remanufacturability, and enhance the efficiency of remanufacturing processes. However, due to the large and fuzzy demand data, it is difficult to accurately extract DfRem targets from the customer demand data. Moreover, the process of DfRem scheme generation includes conceptual design, general design and detailed design. The remanufacturability of products needs be considered at the design process, which makes the DfRem scheme solution process very complicated. For the purpose of accurately extracting DfRem targets and shortening design cycle, it is necessary to apply intelligent technology for customer demand analysis and DfRem solution. To address this, an intelligent DfRem method based on vector space model (VSM) and case-based reasoning (CBR) is proposed. Firstly, for accurate extraction of DfRem targets, VSM is employed to extract customer demand data features from the mass customer demand data embedded with remanufacturing information, and K-means technique is applied to classify customer demand data features thus to extract DfRem targets. After extraction of DfRem targets, CBR is utilized to retrieve the case that is most similar to the DfRem targets from DfRem and remanufacturing process knowledge bases. In order to improve the accuracy of the retrieval, ontology is used to construct standard knowledge expression. Finally, this method has been evaluated utilizing the DfRem of clutch remanufacturing as case studies. The results show that the method can accurately generate design scheme to satisfy the customer demands. In this paper, the intelligent DfRem method has been developed by Visual Studio and Microsoft SQL Server, which can quickly generate the most suitable solution.
Chao Ke; Zhigang Jiang; Hua Zhang; Yan Wang; Shuo Zhu. An intelligent design for remanufacturing method based on vector space model and case-based reasoning. Journal of Cleaner Production 2020, 277, 123269 .
AMA StyleChao Ke, Zhigang Jiang, Hua Zhang, Yan Wang, Shuo Zhu. An intelligent design for remanufacturing method based on vector space model and case-based reasoning. Journal of Cleaner Production. 2020; 277 ():123269.
Chicago/Turabian StyleChao Ke; Zhigang Jiang; Hua Zhang; Yan Wang; Shuo Zhu. 2020. "An intelligent design for remanufacturing method based on vector space model and case-based reasoning." Journal of Cleaner Production 277, no. : 123269.
This article presents a literature review on reverse logistics (RL) supplier selection in terms of criteria and methods. A systematic view of past work published between 2008 and 2020 on Web of Science (WOS) databases is provided by reviewing, categorizing, and analyzing relevant papers. Based on the analyses of 41 articles, we propose a three-stage typology of decision-making frameworks to understanding RL supplier selection, including (a) establishment of the selection criteria; (b) calculation of the relative weights and ranking of the selection criteria; (c) ranking of alternatives (suppliers). The main discoveries of this review are as follows. (1) Attention to the field of RL supplier selection is increasing, as evidenced by the increasing number of papers in the field. With the adaption of circular economy legislation and the need resource and business resilience, it is expected that RL and RL supplier selection will be a hot topic in the near future. (2) A large number of papers take “sustainability” as the theoretical approach to carry out research and use it as the basis for determining the criteria. (3) Multi-criteria decision making (MCDM) methods have been widely used in RL supplier selection and have been constantly innovated. (4) Artificial intelligence methods are also gradually being applied. Finally, gaps in the literature are identified to provide directions for future research. (5) Value-added service is underrepresented in the current study and needs further attention.
Xumei Zhang; Zhizhao Li; Yan Wang. A Review of the Criteria and Methods of Reverse Logistics Supplier Selection. Processes 2020, 8, 705 .
AMA StyleXumei Zhang, Zhizhao Li, Yan Wang. A Review of the Criteria and Methods of Reverse Logistics Supplier Selection. Processes. 2020; 8 (6):705.
Chicago/Turabian StyleXumei Zhang; Zhizhao Li; Yan Wang. 2020. "A Review of the Criteria and Methods of Reverse Logistics Supplier Selection." Processes 8, no. 6: 705.
To train students’ practical ability in design, enterprise projects are often introduced into the industrial design courses of Chinese universities. However, such project-oriented learning activity (POA) is often not well designed. This not only makes it difficult to improve learning effectiveness, but also may bring the unpleasant learning experience to students. The learning experience and learning effectiveness are equally important, and they are mutually conditional and complementary. To consider both, POA needs to be elaborately designed. To this end, a variety of mature POA organization forms, such as project-based learning (PBL), design-based learning (DBL), and project-oriented design-based learning (PODBL), are discussed firstly. PODBL integrates and inherits the advantages of other learning models, and it has been preliminarily proved to improve the learning effectiveness of engineering design courses. Therefore, a cross-reference list was proposed for upgrading POA to PODBL. A lamp design course was developed based on this checklist and students were organized to study. The customer journey map tool was used to analyze the learning experience of students in the course journey, and the emotions and pain points were obtained, as well as some critical factors leading to a positive learning experience. Finally, to demonstrate the availability of the cross-reference list and critical factors, a baby strollers design project course was developed and participants were interviewed. The results show that the cross-reference list and critical factors could improve learning effectiveness and enhance the learning experience significantly.
Xianfeng Ai; Zhigang Jiang; Kang Hu; Siva Chandrasekaran; Yan Wang. Integrating a Cross-Reference List and Customer Journey Map to Improve Industrial Design Teaching and Learning in “Project-Oriented Design Based Learning”. Sustainability 2020, 12, 4672 .
AMA StyleXianfeng Ai, Zhigang Jiang, Kang Hu, Siva Chandrasekaran, Yan Wang. Integrating a Cross-Reference List and Customer Journey Map to Improve Industrial Design Teaching and Learning in “Project-Oriented Design Based Learning”. Sustainability. 2020; 12 (11):4672.
Chicago/Turabian StyleXianfeng Ai; Zhigang Jiang; Kang Hu; Siva Chandrasekaran; Yan Wang. 2020. "Integrating a Cross-Reference List and Customer Journey Map to Improve Industrial Design Teaching and Learning in “Project-Oriented Design Based Learning”." Sustainability 12, no. 11: 4672.
Temperature in the cutting zone during dry machining has a significant effect on the tool life and surface integrity of the workpiece. This paper describes a comprehensive research on the cutting temperature in dry machining of ball screw under whirling milling by using infrared imaging. The effects of tool parameter and geometric parameter of workpiece together with the cutting parameters on the maximum and average temperatures in the cutting zone were analyzed in full detail. The influencing degree of these parameters on the maximum and average temperatures was affected by the value ranges of the parameters. In addition, the regression model and back propagation (BP) neural network model were proposed for predicting the maximum and average temperatures in the cutting zone. The verification of the predictive models showed that compared to the regression model, BP neural network model could predict the cutting temperature with high precision. The R2 of BP neural network model for predicting the maximum and average cutting temperatures in the cutting zone was higher than 99.8%, and the mean relative error and root mean square error were less than 4% and 19%, respectively.
Chao Liu; Yan He; Yulin Wang; Yufeng Li; Shilong Wang; Lexiang Wang; Yan Wang. Effects of process parameters on cutting temperature in dry machining of ball screw. ISA Transactions 2020, 101, 493 -502.
AMA StyleChao Liu, Yan He, Yulin Wang, Yufeng Li, Shilong Wang, Lexiang Wang, Yan Wang. Effects of process parameters on cutting temperature in dry machining of ball screw. ISA Transactions. 2020; 101 ():493-502.
Chicago/Turabian StyleChao Liu; Yan He; Yulin Wang; Yufeng Li; Shilong Wang; Lexiang Wang; Yan Wang. 2020. "Effects of process parameters on cutting temperature in dry machining of ball screw." ISA Transactions 101, no. : 493-502.
Remanufacturing cost prediction is conducive to visually judging the remanufacturability of end-of-life (EOL) products from economic perspective. However, due to the randomness, non-linearity of remanufacturing cost and the lack of sufficient data samples. The general method for predicting the remanufacturing cost of EOL products is very low precision. To this end, a data-driven based decomposition–integration method is proposed to predict remanufacturing cost of EOL products. The approach is based on historical remanufacturing cost data to build a model for prediction. First of all, the remanufacturing cost of individual EOL product is arranged as a time series in reprocessing order. The Improved Local Mean Decomposition (ILMD) is employed to decompose remanufacturing cost time series data into several components with smooth, periodic fluctuation and use this as input. BP neural network based on Particle Swarm Optimization (PSO-BP) algorithm is utilized to predict the cost of each component. Finally, the predicted components are added to obtain the final prediction result. To illustrate and verify the feasibility of the proposed method, the remanufacturing cost of DH220 excavator is applied as the sample data, and empirical results show that the proposed model is statistically superior to other benchmark models owing to its high prediction accuracy and less computation time. And proposed method can be utilized as an effective tool to analyze and predict remanufacturing cost of EOL products.
Zhigang Jiang; Zhouyang Ding; Ying Liu; Yan Wang; Xiaoli Hu; Yihua Yang. A data-driven based decomposition–integration method for remanufacturing cost prediction of end-of-life products. Robotics and Computer-Integrated Manufacturing 2019, 61, 101838 .
AMA StyleZhigang Jiang, Zhouyang Ding, Ying Liu, Yan Wang, Xiaoli Hu, Yihua Yang. A data-driven based decomposition–integration method for remanufacturing cost prediction of end-of-life products. Robotics and Computer-Integrated Manufacturing. 2019; 61 ():101838.
Chicago/Turabian StyleZhigang Jiang; Zhouyang Ding; Ying Liu; Yan Wang; Xiaoli Hu; Yihua Yang. 2019. "A data-driven based decomposition–integration method for remanufacturing cost prediction of end-of-life products." Robotics and Computer-Integrated Manufacturing 61, no. : 101838.
Yan He; Chao Liu; Yulin Wang; Yufeng Li; Shilong Wang; Lexiang Wang; Yan Wang. Analytical modeling of temperature distribution in lead-screw whirling milling considering the transient un-deformed chip geometry. International Journal of Mechanical Sciences 2019, 157-158, 619 -632.
AMA StyleYan He, Chao Liu, Yulin Wang, Yufeng Li, Shilong Wang, Lexiang Wang, Yan Wang. Analytical modeling of temperature distribution in lead-screw whirling milling considering the transient un-deformed chip geometry. International Journal of Mechanical Sciences. 2019; 157-158 ():619-632.
Chicago/Turabian StyleYan He; Chao Liu; Yulin Wang; Yufeng Li; Shilong Wang; Lexiang Wang; Yan Wang. 2019. "Analytical modeling of temperature distribution in lead-screw whirling milling considering the transient un-deformed chip geometry." International Journal of Mechanical Sciences 157-158, no. : 619-632.
Specific cutting energy (SCE) is significant to manufacturing sustainability and directly relevant to energy efficient machining and quality of surface generation of machining processes. Whirling milling process has been widely used to produce precision transmission lead screw thread parts, however, the prediction and characteristics of SCE remain unknown. This paper presents an SCE model of whirling milling as a function of cutting parameters to predict SCE and analyze its relationship with cutting parameters. This study can provide valuable information and guidance for evaluating operation parameters, process plans and optimal selection of cutting parameters to minimize SCE for manufacturing sustainability.
Lexiang Wang; Yan He; Yufeng Li; Yulin Wang; Chao Liu; Xuehui Liu; Yan Wang. Modeling and analysis of specific cutting energy of whirling milling process based on cutting parameters. Procedia CIRP 2019, 80, 56 -61.
AMA StyleLexiang Wang, Yan He, Yufeng Li, Yulin Wang, Chao Liu, Xuehui Liu, Yan Wang. Modeling and analysis of specific cutting energy of whirling milling process based on cutting parameters. Procedia CIRP. 2019; 80 ():56-61.
Chicago/Turabian StyleLexiang Wang; Yan He; Yufeng Li; Yulin Wang; Chao Liu; Xuehui Liu; Yan Wang. 2019. "Modeling and analysis of specific cutting energy of whirling milling process based on cutting parameters." Procedia CIRP 80, no. : 56-61.
The intricate coupling relationship among the used parts make the reuse-oriented redesign process very complex, leading to the incompatible optimization between the used parts and used mechanical equipment. To this end, a dynamic information transfer and feedback method is proposed. In this method, the structure coupling model is established to characterize the relationship of parts. Remanufacturing cost, energy consumption and material consumption are taken as the redesign objectives. In accordance with these objectives and its constraints, a dynamic information transfer and feedback model (DITF) is adopted to achieve collaborative optimization between used mechanical equipment and used parts. An adaptive Teaching-Learning-Based Optimization (A-TLBO) algorithm is used to solve this model. Finally, a case in point is that a used machine tool (model C6132) is adopted to validate feasibility and effectiveness of the proposed method.
Han Wang; Zhigang Jiang; Hua Zhang; Yan Wang. A Dynamic Information Transfer and Feedback Model for Reuse-oriented Redesign of Used Mechanical Equipment. Procedia CIRP 2019, 80, 15 -20.
AMA StyleHan Wang, Zhigang Jiang, Hua Zhang, Yan Wang. A Dynamic Information Transfer and Feedback Model for Reuse-oriented Redesign of Used Mechanical Equipment. Procedia CIRP. 2019; 80 ():15-20.
Chicago/Turabian StyleHan Wang; Zhigang Jiang; Hua Zhang; Yan Wang. 2019. "A Dynamic Information Transfer and Feedback Model for Reuse-oriented Redesign of Used Mechanical Equipment." Procedia CIRP 80, no. : 15-20.
Several restoring technologies are employed in engine remanufacturing, such as brush electroplating, arc spraying and laser cladding, which could improve the quality and performance of the remanufactured product and the efficiency of remanufacturing processes. The primary objective of the present study is to analyze the environmental benefits of remanufacturing employing advanced restoring technologies (Scenario 3) in comparison to newly manufacturing (Scenario 1) and remanufacturing without using advanced restoring technologies (Scenario 2) based on Life Cycle Assessment (LCA) methodology. Resource and energy consumptions of each manufacturing and remanufacturing processes were collected along the production line and then the results of seven selected environmental impact categories are calculated. The results show that engine remanufacturing with advanced restoring technologies will achieve large environmental benefits. By using advanced restoring technologies, engine remanufacturing could be able to restore more damaged components and reduce the environmental impacts through reduced consumption of raw materials production and manufacturing process of production replacement parts.
Handong Zheng; Enzhong Li; Yan Wang; Peijing Shi; Binshi Xu; Shanlin Yang. Environmental life cycle assessment of remanufactured engines with advanced restoring technologies. Robotics and Computer-Integrated Manufacturing 2019, 59, 213 -221.
AMA StyleHandong Zheng, Enzhong Li, Yan Wang, Peijing Shi, Binshi Xu, Shanlin Yang. Environmental life cycle assessment of remanufactured engines with advanced restoring technologies. Robotics and Computer-Integrated Manufacturing. 2019; 59 ():213-221.
Chicago/Turabian StyleHandong Zheng; Enzhong Li; Yan Wang; Peijing Shi; Binshi Xu; Shanlin Yang. 2019. "Environmental life cycle assessment of remanufactured engines with advanced restoring technologies." Robotics and Computer-Integrated Manufacturing 59, no. : 213-221.
Optical coherence Tomography (OCT) relies on optical interferometry to provide non‐invasive imaging of living tissues. In addition to its 3D imaging capacity for medical diagnosis, its potential use for recovering optical parameters of biological tissues for biological and pathological analyses has also been explored by researchers, as pathological changes in tissue alter the micro‐structure of the tissue and therefore its optical properties. We aim to develop a new approach to OCT data analysis by estimating optical properties of tissues from OCT scans which are invisible in the scans. This is an inverse problem. Solving an inverse problem involves a forward modelling step to simulate OCT scans of the tissues with hypothesized optical parameter values, and an inverse step to estimate the real optical parameters values by matching the simulated scans to real scans. In this paper, we present a Monte Carlo (MC) based approach for simulating the frequency‐domain OCT. We incorporated a focusing Gaussian light beam rather than an infinitesimally thin light beam for accurate simulations. A new and more accurate photon detection scheme is also implemented. We compare our MC model to an analytical OCT model based on the extended Huygens‐Fresnel principle (EHF) to demonstrate the consistency between the two models. We show that the two models are in good agreement for tissues with high scattering and high anisotropy factors.
Yan Wang; Li Bai. Accurate Monte Carlo simulation of frequency‐domain optical coherence tomography. International Journal for Numerical Methods in Biomedical Engineering 2019, 35, e3177 .
AMA StyleYan Wang, Li Bai. Accurate Monte Carlo simulation of frequency‐domain optical coherence tomography. International Journal for Numerical Methods in Biomedical Engineering. 2019; 35 (4):e3177.
Chicago/Turabian StyleYan Wang; Li Bai. 2019. "Accurate Monte Carlo simulation of frequency‐domain optical coherence tomography." International Journal for Numerical Methods in Biomedical Engineering 35, no. 4: e3177.
Reverse logistics (RL) has been regarded as a key driving force for remanufacturing. However, there are great uncertainties in terms of quality and quantity of used components for RL. There are also complexities in suppliers and operations. These make decision-making of RL very complex. In order to identify the best collection mode for used components, a demand-matching oriented Multiple Criteria Decision Making (MCDM) method is established. In this method, the damage level and remaining service life are firstly incorporated into the evaluation criteria of reuse modes, then a hybrid method (AHP-EW) that integrates Analytic Hierarchy Process (AHP) and Entropy Weight (EW) method is applied to derive criteria weights and the grey Multi-Attributive Border Approximation Area Comparison (MABAC) is adopted to rank the collection modes. Finally, sensitivity analysis is implemented to test the stability of the proposed method, and a demands-matching method is proposed to validate and evaluate the feasibility of the optimal alternative. The collection of used pressurizers is taken as case study to validate the applicability of the proposed model. The results showed the effectiveness of the proposed method in MCDM of RL.
Han Wang; Zhigang Jiang; Hua Zhang; Yan Wang; Yihua Yang; Yi Li. An integrated MCDM approach considering demands-matching for reverse logistics. Journal of Cleaner Production 2018, 208, 199 -210.
AMA StyleHan Wang, Zhigang Jiang, Hua Zhang, Yan Wang, Yihua Yang, Yi Li. An integrated MCDM approach considering demands-matching for reverse logistics. Journal of Cleaner Production. 2018; 208 ():199-210.
Chicago/Turabian StyleHan Wang; Zhigang Jiang; Hua Zhang; Yan Wang; Yihua Yang; Yi Li. 2018. "An integrated MCDM approach considering demands-matching for reverse logistics." Journal of Cleaner Production 208, no. : 199-210.
The environmental impacts of manufacturing systems can be improved by reducing the energy consumption of machine tools. To meet the requirements for reducing energy consumption of machine tools, it is critical to monitor and analyze energy usage of machine tools. However, machine tools are composed of multiple energy consumers and the requirements towards monitoring energy of machine tools are different. This paper proposes a configurable on-line monitoring system to obtain energy data for the specific energy consumption components of machine tools, which can be used to analyze energy characteristics considering different energy monitoring requirements and different machine tools. The case study of the system implemented in lathe and machining center shows that the system can be used to monitor energy consumption of different types of machine tools and satisfy different monitoring requirements of energy consumption. The results can provide a better understanding of energy and support refined energy management in the manufacturing system.
Pengcheng Wu; Yan He; Ming K Lim; Yan Wang; Yulin Wang; Linming Hu. A Configurable On-Line Monitoring System Towards Energy Consumption of Machine Tools. Programmieren für Ingenieure und Naturwissenschaftler 2018, 139 -150.
AMA StylePengcheng Wu, Yan He, Ming K Lim, Yan Wang, Yulin Wang, Linming Hu. A Configurable On-Line Monitoring System Towards Energy Consumption of Machine Tools. Programmieren für Ingenieure und Naturwissenschaftler. 2018; ():139-150.
Chicago/Turabian StylePengcheng Wu; Yan He; Ming K Lim; Yan Wang; Yulin Wang; Linming Hu. 2018. "A Configurable On-Line Monitoring System Towards Energy Consumption of Machine Tools." Programmieren für Ingenieure und Naturwissenschaftler , no. : 139-150.
Heat source model is an important part when carrying out simulations of welding processes. The calibration process involves a great amount of numerical simulations or theoretical deductions with many simplifications. In this paper, an interaction finite element and optimization algorithm package is programmed to automatically calibrate heat source models. The results are then used to establish mathematical relationships between parameters of heat source and welding process variables. The models show that the absorption efficiency and depth of heat source are exponential functions of depth of focus and laser power, respectively while radius of heat source is determined by depth of focus quadratically.
Changrong Chen; Yueh-Jaw Lin; Hengan Ou; Yan Wang. Study of Heat Source Calibration and Modelling for Laser Welding Process. International Journal of Precision Engineering and Manufacturing 2018, 19, 1239 -1244.
AMA StyleChangrong Chen, Yueh-Jaw Lin, Hengan Ou, Yan Wang. Study of Heat Source Calibration and Modelling for Laser Welding Process. International Journal of Precision Engineering and Manufacturing. 2018; 19 (8):1239-1244.
Chicago/Turabian StyleChangrong Chen; Yueh-Jaw Lin; Hengan Ou; Yan Wang. 2018. "Study of Heat Source Calibration and Modelling for Laser Welding Process." International Journal of Precision Engineering and Manufacturing 19, no. 8: 1239-1244.
A demand matching oriented Multi-Criteria Decision-Making method is presented to identify the best collection mode for used components. In this method, the damage condition and remaining service life are incorporated into the evaluation criteria of reuse mode, then a hybrid method (AHP-EW) integrating Analytic Hierarchy Process (AHP) and Entropy Weight (EW) is used to derive the criteria weights and the grey Multi-Attributive Border Approximation Area Comparison (MABAC) is adopted to rank the collection modes. Finally, a sensitivity analysis is used to test the stability of the method and a demands-matching method is proposed to validate the feasibility of the optimal alternative. The method is validated using the collection of used pressurizers as case study. The results of which show the effectiveness of the proposed method.
Han Wang; Zhigang Jiang; Yan Wang; Ying Liu; Fei Li; Wei Yan; Hua Zhang. A Demands-Matching Multi-Criteria Decision-Making Method for Reverse Logistics. Procedia CIRP 2018, 72, 1398 -1403.
AMA StyleHan Wang, Zhigang Jiang, Yan Wang, Ying Liu, Fei Li, Wei Yan, Hua Zhang. A Demands-Matching Multi-Criteria Decision-Making Method for Reverse Logistics. Procedia CIRP. 2018; 72 ():1398-1403.
Chicago/Turabian StyleHan Wang; Zhigang Jiang; Yan Wang; Ying Liu; Fei Li; Wei Yan; Hua Zhang. 2018. "A Demands-Matching Multi-Criteria Decision-Making Method for Reverse Logistics." Procedia CIRP 72, no. : 1398-1403.
Remanufacturing is considered as an important industrial process to restore the performance and function of End-of-Life (EOL) products to a like-new state. In order to help enterprises effectively and precisely predict the cost of remanufacturing processes, a remanufacturing cost prediction model based on big data is developed. In this paper, a cost analysis framework is established by applying big data technologies to interpret the obtained data, identify the intricate relationship of obtained sensor data and its corresponding remanufacturing processes and associated costs. Then big data mining and particle swarm optimization Back Propagation (BP) neural network algorithm are utilized to implement the cost prediction. The application of presented model is verified by a case study, and the results demonstrates that the developed model can predict the cost of the remanufacturing accurately allowing early decision making for remanufacturability of the EOL products.
Zhouyang Ding; Zhigang Jiang; Ying Liu; Yan Wang; Congbo Li. A Big Data based Cost Prediction Method for Remanufacturing End-of-Life Products. Procedia CIRP 2018, 72, 1362 -1367.
AMA StyleZhouyang Ding, Zhigang Jiang, Ying Liu, Yan Wang, Congbo Li. A Big Data based Cost Prediction Method for Remanufacturing End-of-Life Products. Procedia CIRP. 2018; 72 ():1362-1367.
Chicago/Turabian StyleZhouyang Ding; Zhigang Jiang; Ying Liu; Yan Wang; Congbo Li. 2018. "A Big Data based Cost Prediction Method for Remanufacturing End-of-Life Products." Procedia CIRP 72, no. : 1362-1367.
Scheduling can have significant impacts on energy saving in manufacturing systems. The complex process constraints and dynamic manufacturing tasks in flexible manufacturing system make the scheduling a complicated nonlinear programming problem. To this end, this paper proposes a two-stage energy-saving optimization method for Flexible Job-Shop Scheduling Problems (FJSP). In this method, an operation-based integrated chart is firstly proposed to reveal the dynamic characteristics of the operations, enabling the energy-saving scheduling optimization. Then the optimization is conducted at two stages: the machine tool stage and the operation sequence stage. A Modified Genetic Algorithm (MGA) is applied at the first stage and a hybrid method that integrates Genetic Algorithm (GA) with Particle Swarm Optimization (PSO) is adopted at the second stage. Finally, a case study is employed to illustrate the applicability and validity of the proposed method. The results revealed that the proposed method can effectively optimize FJSP. This may provide a basis for decision makers to utilize a manufacturing scheduling that is optimized regarding its energy saving.
Han Wang; Zhigang Jiang; Yan Wang; Hua Zhang; Yanhong Wang. A two-stage optimization method for energy-saving flexible job-shop scheduling based on energy dynamic characterization. Journal of Cleaner Production 2018, 188, 575 -588.
AMA StyleHan Wang, Zhigang Jiang, Yan Wang, Hua Zhang, Yanhong Wang. A two-stage optimization method for energy-saving flexible job-shop scheduling based on energy dynamic characterization. Journal of Cleaner Production. 2018; 188 ():575-588.
Chicago/Turabian StyleHan Wang; Zhigang Jiang; Yan Wang; Hua Zhang; Yanhong Wang. 2018. "A two-stage optimization method for energy-saving flexible job-shop scheduling based on energy dynamic characterization." Journal of Cleaner Production 188, no. : 575-588.