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Sökning: WFRF:(Wang Lihui)

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1.
  • Li, Wei, et al. (författare)
  • Non-lab and semi-lab algorithms for screening undiagnosed diabetes : A cross-sectional study
  • 2018
  • Ingår i: EBioMedicine. - : ELSEVIER SCIENCE BV. - 2352-3964. ; 35, s. 307-316
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: The terrifying undiagnosed rate and high prevalence of diabetes have become a public emergency. A high efficiency and cost-effective early recognition method is urgently needed. We aimed to generate innovative, user-friendly nomograms that can be applied for diabetes screening in different ethnic groups in China using the non-lab or noninvasive semi-lab data. Methods: This multicenter, multi-ethnic, population-based, cross-sectional study was conducted in eight sites in China by enrolling subjects aged 20-70. Sociodemographic and anthropometric characteristics were collected. Blood and urine samples were obtained 2 h following a standard 75 g glucose solution. In the final analysis, 10,794 participants were included and randomized into model development (n - 8096) and model validation (n = 2698) group with a ratio of 3:1. Nomograms were developed by the stepwise binary logistic regression. The nomograms were validated internally by a bootstrap sampling method in the model development set and externally in the model validation set. The area under the receiver operating characteristic curve (AUC) was used to assess the screening performance of the nomograms. Decision curve analysis was applied to calculate the net benefit of the screening model. Results: The overall prevalence of undiagnosed diabetes was 9.8% (1059/10794) according to ADA criteria. The non-lab model revealed that gender, age, body mass index, waist circumference, hypertension, ethnicities, vegetable daily consumption and family history of diabetes were independent risk factors for diabetes. By adding 2 h post meal glycosuria qualitative to the non-lab model, the semi-lab model showed an improved Akaike information criterion (AIC: 4506 to 3580). The AUC of the semi-lab model was statistically larger than the non-lab model (0.868 vs 0.763, P < 0.001). The optimal cutoff probability in semi-lab and non-lab nomograms were 0.088 and 0.098, respectively. The sensitivity and specificity were 76.3% and 81.6%, respectively in semi-lab nomogram, and 72.1% and 673% in non-lab nomogram at the optimal cut off point. The decision curve analysis also revealed a bigger decrease of avoidable OGTT test (52 per 100 subjects) in the semi-lab model compared to the non-lab model (36 per 100 subjects) and the existed New Chinese Diabetes Risk Score (NCDRS, 35 per 100 subjects). Conclusion: The non-lab and semi-lab nomograms appear to be reliable tools for diabetes screening, especially in developing countries. However, the semi-lab model outperformed the non-lab model and NCDRS prediction systems and might be worth being adopted as decision support in diabetes screening in China.
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2.
  • Liu, Lihui, et al. (författare)
  • Ablation of ERO1A induces lethal endoplasmic reticulum stress responses and immunogenic cell death to activate anti-tumor immunity
  • 2023
  • Ingår i: Cell Reports Medicine. - : Cell Press. - 2666-3791. ; 4:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Immunophenotyping of the tumor microenvironment (TME) is essential for enhancing immunotherapy effi-cacy. However, strategies for characterizing the TME exhibit significant heterogeneity. Here, we show that endoplasmic reticular oxidoreductase-1a (ERO1A) mediates an immune-suppressive TME and attenuates the response to PD-1 blockade. Ablation of ERO1A in tumor cells substantially incites anti-tumor T cell im-munity and promotes the efficacy of aPD-1 in therapeutic models. Single-cell RNA-sequencing analyses confirm that ERO1A correlates with immunosuppression and dysfunction of CD8+ T cells along anti-PD-1 treatment. In human lung cancer, high ERO1A expression is associated with a higher risk of recurrence following neoadjuvant immunotherapy. Mechanistically, ERO1A ablation impairs the balance between IRE1a and PERK signaling activities and induces lethal unfolded protein responses in tumor cells undergoing endoplasmic reticulum stress, thereby enhancing anti-tumor immunity via immunogenic cell death. These findings reveal how tumor ERO1A induces immunosuppression, highlighting its potential as a therapeutic target for cancer immunotherapy.
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3.
  • Liu, Lihui, et al. (författare)
  • Dynamic toxicity landscape of immunotherapy for solid tumors across treatment lines
  • 2023
  • Ingår i: Journal of the National Cancer Center. - : Elsevier. - 2667-0054. ; 3:3, s. 186-196
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: Immune checkpoint inhibitors (ICIs) targeting programmed cell death-1/ligand-1 (PD-1/PD-L1), cytotoxic T lymphocyte antigen-4 (CTLA-4), and lymphocyte-activation gene-3 (LAG-3) have been widely studied and applied throughout the course of cancer treatment. This study aimed to provide a comprehensive profile of ICI-associated toxicity and elucidate the toxicity patterns of ICIs across different treatment lines. Methods: In total, 155 cohorts comprising 24 539 eligible patients were included in the safety analysis. Trial name, registration number, cancer type, trial phase, clinical setting, trial design, regimen, dosing schedule, age, sex and ethnicity distributions, number of patients, number of treatment-related adverse events (trAEs), and number of treatment-related death were extracted. We defined a timeline from the neoadjuvant setting to the third-line setting. We also introduced a synthesizing principle for adverse event rates (SPAER) of immunotherapy to ensure the comparability and reliability across different treatment lines. The study protocol was registered and approved by the PROSPERO protocol review committee (CRD42021242368). Results: After excluding the neoadjuvant setting group, we observed a distinct reduction in the incidence of treatment-related adverse events (trAEs) with an advancement of the line of ICI treatment. The incidence of trAEs was negatively correlated with the line of treatment, irrespective of whether monotherapy or dual-ICI combination therapy was administered. Sensitivity analyses also confirmed the coincident negative correlations. Conclusion: In summary, using a timeline-based concept centered around treatment lines, we revealed the dynamic landscape of ICI-associated toxicity and found that patients treated with ICIs during later lines of therapy may have a lower risk of trAEs.
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4.
  • Wang, Peng, et al. (författare)
  • Linking Emergence to the Complex Product System
  • 2020
  • Ingår i: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 8, s. 34286-34298
  • Tidskriftsartikel (refereegranskat)abstract
    • The increasing complexity of product calls for manufacturing integration, while in turn high integration brings the problems of system level complexity. This paper proposes that complex product system (CoPS) should be managed as a dynamical system. The dynamical characteristics of CoPS are discussed from the perspective of emergence. A conceptual model is established to analyze the cause, process and result of the CoPS emergence. The mechanism of inner state emergence in CoPS is interpreted by formal languages to provide a point view of state space. It is concluded that the behavior of CoPS, especially the complexity, exhibits the 'entity is greater than the sum of the parts' phenomena when satisfying given necessary conditions. A novel methodology is then established to evaluate this emergence-based complexity. The feasibility and application of the novel complexity measurement is verified by an example of turbine housing production process. Further discussions are made on how to manage the potential emerging complexity based on the proposed measurement.
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5.
  • Wang, Peng, et al. (författare)
  • The Existence of Autonomous Chaos in EDM Process
  • 2022
  • Ingår i: Machines. - : MDPI AG. - 2075-1702. ; 10:4
  • Tidskriftsartikel (refereegranskat)abstract
    • The dynamical evolution of electrical discharge machining (EDM) has drawn immense research interest. Previous research on mechanism analysis has discussed the deterministic nonlinearity of gap states at pulse-on discharging duration, while describing the pulse-off deionization process separately as a stochastic evolutionary process. In this case, the precise model describing a complete machining process, as well as the optimum performance parameters of EDM, can hardly be determined. The main purpose of this paper is to clarify whether the EDM system can maintain consistency in dynamic characteristics within a discharge interval. A nonlinear self-maintained equivalent model is first established, and two threshold conditions are obtained by the Shilnikov theory. The theoretical results prove that the EDM system could lead to chaos without external excitation. The time series of the deionization process recorded in the EDM experiments are then analyzed to further validate this theoretical conclusion. Qualitative chaotic analyses verify that the autonomous EDM process has chaotic characteristics. Quantitative methods are used to estimate the chaotic feature of the autonomous EDM process. By comparing the quantitative results of the autonomous EDM process with the non-autonomous EDM process, a deduction is further made that the EDM system will evolve towards steady chaos under an autonomous state.
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6.
  • Gao, Y., et al. (författare)
  • A Review on Recent Advances in Vision-based Defect Recognition towards Industrial Intelligence
  • 2021
  • Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642.
  • Tidskriftsartikel (refereegranskat)abstract
    • In modern manufacturing, vision-based defect recognition is an essential technology to guarantee product quality, and it plays an important role in industrial intelligence. With the developments of industrial big data, defect images can be captured by ubiquitous sensors. And, how to realize accuracy recognition has become a research hotspot. In the past several years, many vision-based defect recognition methods have been proposed, and some newly-emerged techniques, such as deep learning, have become increasingly popular and have addressed many challenging problems effectively. Hence, a comprehensive review is urgently needed, and it can promote the development and bring some insights in this area. This paper surveys the recent advances in vision-based defect recognition and presents a systematical review from a feature perspective. This review divides the recent methods into designed-feature based methods and learned-feature based methods, and summarizes the advantages, disadvantages and application scenarios. Furthermore, this paper also summarizes the performance metrics for vision-based defect recognition methods. And some challenges and development trends are also discussed. 
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7.
  • Li, Shufei, et al. (författare)
  • Proactive human-robot collaboration : Mutual-cognitive, predictable, and self-organising perspectives
  • 2023
  • Ingår i: Robotics and Computer-Integrated Manufacturing. - : Elsevier BV. - 0736-5845 .- 1879-2537. ; 81, s. 102510-
  • Forskningsöversikt (refereegranskat)abstract
    • Human-Robot Collaboration (HRC) has a pivotal role in smart manufacturing for strict requirements of human -centricity, sustainability, and resilience. However, existing HRC development mainly undertakes either a human-dominant or robot-dominant manner, where human and robotic agents reactively perform operations by following pre-defined instructions, thus far from an efficient integration of robotic automation and human cognition. The stiff human-robot relations fail to be qualified for complex manufacturing tasks and cannot ease the physical and psychological load of human operators. In response to these realistic needs, this paper presents our arguments on the obvious trend, concept, systematic architecture, and enabling technologies of Proactive HRC, serving as a prospective vision and research topic for future work in the human-centric smart manufacturing era. Human-robot symbiotic relation is evolving with a 5C intelligence - from Connection, Coordination, Cyber, Cognition to Coevolution, and finally embracing mutual-cognitive, predictable, and self -organising intelligent capabilities, i.e., the Proactive HRC. With proactive robot control, multiple human and robotic agents collaboratively operate manufacturing tasks, considering each others' operation needs, desired resources, and qualified complementary capabilities. This paper also highlights current challenges and future research directions, which deserve more research efforts for real-world applications of Proactive HRC. It is hoped that this work can attract more open discussions and provide useful insights to both academic and industrial practitioners in their exploration of human-robot flexible production.
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8.
  • Liu, Sichao, et al. (författare)
  • Energy-efficient trajectory planning for an industrial robot using a multi-objective optimisation approach
  • 2018
  • Ingår i: Procedia Manufacturing. - : Elsevier BV. - 2351-9789. ; , s. 517-525
  • Konferensbidrag (refereegranskat)abstract
    • This paper presents an approach for energy-efficient trajectory planning of an industrial robot. A model that can be used to formulate the energy consumption of the robot with the kinematics constraints is developed. Given the trajectory in the Cartesian space, the septuple B-spline is applied in joint space trajectory planning to make the velocities, accelerations, and jerks bounded and continuous, with constraints on the initial and ending values. Then, energy-efficient optimisation problem with nonlinear constraints is discussed. Simulation results show that, the proposed approach is effective solution to trajectory planning, with ensuring a good energy improvement and fluent movement for the robot manipulators.
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9.
  • Liu, Yongkui, et al. (författare)
  • Multi-agent-based scheduling in cloud manufacturing with dynamic task arrivals
  • 2018
  • Ingår i: Procedia CIRP. - : Elsevier. - 2212-8271. ; , s. 953-960
  • Konferensbidrag (refereegranskat)abstract
    • Scheduling is a critical means for providing on-demand manufacturing services in cloud manufacturing. Multi-agent technologies provide an effective approach for addressing scheduling issues in cloud manufacturing, which, however, have rarely been used for solving the issue. This paper addresses scheduling issues in cloud manufacturing using multi-agent technologies. A multi-agent architecture for scheduling in cloud manufacturing is proposed firstly. Then, a corresponding multi-agent model is presented, which incorporates many-to-many negotiations based on an extended contract net protocol and takes into account dynamic task arrivals. Simulation results indicate the feasibility of the model and approach proposed.
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10.
  • Pang, Shibao, et al. (författare)
  • Dual-Dimensional Manufacturing Service Collaboration Optimization Toward Industrial Internet Platforms
  • 2023
  • Ingår i: ENGINEERING. - : Elsevier BV. - 2095-8099. ; 22, s. 34-48
  • Tidskriftsartikel (refereegranskat)abstract
    • An Industrial Internet platform is acknowledged to be a requisite promoter for smart manufacturing, enabling physical manufacturing resources to be virtualized and permitting resources to collaborate in the form of services. As a central function of the platform, manufacturing service collaboration optimization is dedicated to establishing high-quality service collaboration solutions for manufacturing tasks. Such optimization is inseparable from the functional and amount requirements of a task, which must be satisfied when orchestrating services. However, existing manufacturing service collaboration optimization methods mainly focus on horizontal collaboration among services for functional demands and rarely consider vertical collaboration to cover the needed amounts. To address this gap, this paper proposes a dual-dimensional service collaboration methodology that combines functional and amount collaboration. First, a multi-granularity manufacturing service modeling method is presented to describe services. On this basis, a dual-dimensional manufacturing service collaboration optimization (DMSCO) model is formulated. In the vertical dimension, multiple functionally equivalent services form a service cluster to fulfill a subtask; in the horizontal dimension, complementary service clusters collaborate for the entire task. Service selection and amount distribution to the selected services are critical issues in the model. To solve the problem, a multi-objective memetic algorithm with multiple local search operators is tailored. The algorithm embeds a competition mechanism to dynamically adjust the selection probabilities of the local search operators. The experimental results demonstrate the superiority of the algorithm in terms of convergence, solution quality, and comprehensive metrics, in comparison with commonly used algorithms.
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11.
  • Wang, Baicun, et al. (författare)
  • Human-centric smart manufacturing
  • 2023
  • Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 69, s. 18-19
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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12.
  • Wang, Binbin, et al. (författare)
  • Towards the industry 5.0 frontier: Review and prospect of XR in product assembly
  • 2024
  • Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 74, s. 777-811
  • Forskningsöversikt (refereegranskat)abstract
    • As an emerging manufacturing paradigm, Industry 5.0 emphasizes human-centric intelligent manufacturing. XR technology (a general term of virtual reality, augmented reality and mixed reality) brings unprecedented opportunities for assembly in such manufacturing paradigm. We provide a comprehensive review, in-depth analysis, and prospect on XR in product intelligent assembly from two points of views of technology and application. Subsequently, the benefits and potential of XR in assembly are discussed from three perspectives of users, enterprises and industries. Finally, challenges and future research directions for XR are outlined from the perspectives of hardware issues and technological maturity. This review is expected to provide useful references for XR-related research and application in the future.
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13.
  • Wang, Tianyu, et al. (författare)
  • Data-efficient multimodal human action recognition for proactive human–robot collaborative assembly: A cross-domain few-shot learning approach
  • 2024
  • Ingår i: Robotics and Computer-Integrated Manufacturing. - : Elsevier BV. - 0736-5845 .- 1879-2537. ; 89
  • Tidskriftsartikel (refereegranskat)abstract
    • With the recent vision of Industry 5.0, the cognitive capability of robots plays a crucial role in advancing proactive human–robot collaborative assembly. As a basis of the mutual empathy, the understanding of a human operator's intention has been primarily studied through the technique of human action recognition. Existing deep learning-based methods demonstrate remarkable efficacy in handling information-rich data such as physiological measurements and videos, where the latter category represents a more natural perception input. However, deploying these methods in new unseen assembly scenarios requires first collecting abundant case-specific data. This leads to significant manual effort and poor flexibility. To deal with the issue, this paper proposes a novel cross-domain few-shot learning method for data-efficient multimodal human action recognition. A hierarchical data fusion mechanism is designed to jointly leverage the skeletons, RGB images and depth maps with complementary information. Then a temporal CrossTransformer is developed to enable the action recognition with very limited amount of data. Lightweight domain adapters are integrated to further improve the generalization with fast finetuning. Extensive experiments on a real car engine assembly case show the superior performance of proposed method over state-of-the-art regarding both accuracy and finetuning efficiency. Real-time demonstrations and ablation study further indicate the potential of early recognition, which is beneficial for the robot procedures generation in practical applications. In summary, this paper contributes to the rarely explored realm of data-efficient human action recognition for proactive human–robot collaboration.
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14.
  • Wang, Xi Vincent, Dr. 1985-, et al. (författare)
  • Robots in the industrial internet : A cloud-based approach based on gateways
  • 2019
  • Ingår i: Proceedings of ASME 2019 14th International Manufacturing Science and Engineering Conference, MSEC 2019.
  • Konferensbidrag (refereegranskat)abstract
    • In the context of Industrial Internet, connectivity is a must during system construction as it provides the possibility of sharing the hardware data with the network, and accessing the hardware from other systems or devices. An efficient communication approach is the highest priority to deploy a successful technology like Industry 4.0, Industrial Internet, Internet of Things, etc.. Thus in this research, a system integration method is presented using industrial robots as the test scenario. Cloud and gateway technologies are utilised to achieve high-performance connectivity, integration and security. Multiple deployment models are developed for public, private and hybrid cloud scenarios. During implementation, the Universal Robot 5 is utilised as the test robot integrating to the KTH cloud system in Sweden. The results are quantifiably evaluated and discussed. The proposed approach also contributes to the Cloud Robotics research by proposing novel system structures and integration methods.
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15.
  • Advanced human-robot collaboration in manufacturing
  • 2021
  • Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
    • This book presents state-of-the-art research, challenges and solutions in the area of human-robot collaboration (HRC) in manufacturing. It enables readers to better understand the dynamic behaviour of manufacturing processes, and gives more insight into on-demand adaptive control techniques for industrial robots. With increasing complexity and dynamism in today's manufacturing practice, more precise, robust and practical approaches are needed to support real-time shop-floor operations. This book presents a collection of recent developments and innovations in this area, relying on a wide range of research efforts. The book is divided into five parts. The first part presents a broad-based review of the key areas of HRC, establishing a common ground of understanding in key aspects. Subsequent chapters focus on selected areas of HRC subject to intense recent interest. The second part discusses human safety within HRC. The third, fourth and fifth parts provide in-depth views of relevant methodologies and algorithms. Discussing dynamic planning and monitoring, adaptive control and multi-modal decision making, the latter parts facilitate a better understanding of HRC in real situations. The balance between scope and depth, and theory and applications, means this book appeals to a wide readership, including academic researchers, graduate students, practicing engineers, and those within a variety of roles in manufacturing sectors.
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16.
  • Chen, Mo, et al. (författare)
  • Study on Efficient Fused Deposition Modelling of Thermoplastic Polyurethane Inflatable Wall Features for Airtightness
  • 2020
  • Ingår i: Swedish Production Symposium 2020.
  • Konferensbidrag (refereegranskat)abstract
    • The thermoplastic polyurethane (TPU) material is an elastomer that canbe used for inflatable products. Fused deposition modelling (FDM) is a widelyused additive manufacturing process for TPU material due to the capability ofgenerating complex structures with low cost. However, TPU is soft and thusdifficult to be extruded as continuously and uniformly as hard materials such aspolylactide by FDM. Inappropriate extruder structure and speed settings can leadto filament buckling problem, resulting in poor material filling quality, longprinting time and low printing success rate. This paper aims at improving the FDMprinting efficiency of TPU inflatable products by adding lateral support to thefilament and finding out the appropriate speed ranges for different wall featuresand thicknesses. Firstly, a filament guide sheet is designed as being inserted intothe gap between the drive gears and the bottom frame of the gear chamber in orderto prevent the soft TPU filament from buckling. Secondly, inflatable product wallfeatures are classified into floors, roofs and sidewalls and experiment for findingthe relationship between printing speed and airtightness is carried out. In order toverify the proposed solution, wall features are printed and the material fillingsobtained under different printing speeds are compared by measuring theairtightness of the wall features. Results show that the proposed filament guidesheet mitigates filament buckling, and the speed range that meets the airtightnessrequirement can be found for various wall features and thicknesses. In summary,the sealing of the filament feeding channel between the drive gears and the nozzle,as well as the speed optimisation according to product features, are essential forthe efficient printing of TPU inflatable products.
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17.
  • Chodnicki, Marek, et al. (författare)
  • Project-Based Collaborative Research and Training Roadmap for Manufacturing Based on Industry 4.0
  • 2024
  • Ingår i: Flexible Automation and Intelligent Manufacturing. - : Springer Nature. ; , s. 708-715
  • Konferensbidrag (refereegranskat)abstract
    • The importance of the economy being up to date with the latest developments, such as Industry 4.0, is more evident than ever before. Successful implementation of Industry 4.0 principles requires close cooperation of industry and state authorities with universities. A paradigm of such cooperation is described in this paper stemming from university partners with partly overlapping and partly complementary areas of expertise in manufacturing. Specific areas that are targeted include Additive Manufacturing, cloud computing and control, Virtual Reality, Digital Twins, and Artificial Intelligence. The manufacturing system domains that are served pertaining to process planning and optimization, process and system monitoring, and innovative / precision manufacturing. The described collaborative research and training framework involves a combination of pertinent targeted individual exploratory innovation projects as well as a synthetic multifaceted common research project. Based on these, the research and innovation project knowledge will be transferred to the industry by building a Cluster of Excellence, i.e., a network consisting of academic and industrial stakeholders.
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18.
  • Cui, Y., et al. (författare)
  • Research on milling temperature measuring tool embedded with NiCr/NiSi thin film thermocouple
  • 2018
  • Ingår i: 51st CIRP Conference on Manufacturing Systems. - : Elsevier. ; , s. 1457-1462
  • Konferensbidrag (refereegranskat)abstract
    • In order to measure the milling area temperature in-situ, the milling tool embedded with NiCr/NiSi thin film thermocouple (TFTC) is prepared. TFTC capable well temperature performance is embedded on the tool tip by successively depositing SiO2 insulating film, NiCr/NiSi thermoelectric film, and SiO2 protective film. Surface morphology and thin film properties are confirmed to achieve expectation by means of TEM and SEM. Imitation reflects that TFTC abrasion has minor effect on dynamic and static characteristic. The in-situ milling area temperature is successfully detected by TFTC temperature measuring tool in field test.
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19.
  • Fan, Wei, et al. (författare)
  • A review on cutting tool technology in machining of Ni-based superalloys
  • 2020
  • Ingår i: The International Journal of Advanced Manufacturing Technology. - : Springer Science and Business Media Deutschland GmbH. - 0268-3768 .- 1433-3015. ; 110:11-12, s. 2863-2879
  • Tidskriftsartikel (refereegranskat)abstract
    • In this paper, a state-of-the-art review on cutting tool technology in machining of Ni-based superalloys is presented to better understand the current status and to identify future directions of research and development of cutting tool technologies. First, past review articles related to the machining of Ni-based superalloys are summarized. Then machinability of superalloys is introduced, together with the reported methods used in cutting tool design. The current researches on cutting tools in the machining of superalloys are presented in different categories in terms of tool materials, i.e., carbide, ceramics, and Polycrystalline cubic boron nitride (PCBN). Moreover, a set of research issues are identified and highlighted to improve the machining of superalloys. Finally, discussions on the future development are presented, in the areas of new materials/geometries, functional surfaces on the cutting tool, and data-driven comprehensive optimization.
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20.
  • Fuoco, Tiziana, PhD, 1986-, et al. (författare)
  • Hydrogel Polyester Scaffolds via Direct-Ink-Writing of Ad Hoc Designed Photocurable Macromonomer
  • 2022
  • Ingår i: Polymers. - : MDPI. - 2073-4360. ; 14:4
  • Tidskriftsartikel (refereegranskat)abstract
    • Synthetic, degradable macromonomers have been developed to serve as ink for 3D printing technologies based on direct-ink-writing. The macromonomers are purposely designed to be cross-linkable under the radical mechanism, to impart hydrophilicity to the final material, and to have rheological properties matching the printer's requirements. The suitable viscosity enables the ink to be printed at room temperature, in absence of organic solvents, and to be cross-linked to manufacture soft 3D scaffolds that show no indirect cytotoxicity and have a hydration capacity of up to 100% their mass and a compressive modulus in the range of 0.4-2 MPa.
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21.
  • Gao, Robert X., et al. (författare)
  • Human motion recognition and prediction for robot control
  • 2021
  • Ingår i: Advanced Human-Robot Collaboration in Manufacturing. - Cham : Springer Nature. ; , s. 261-282
  • Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
    • The ever-increasing demand for higher productivity, lower cost and improved safety continues to drive the advancement of manufacturing technologies. As one of the key elements, human-robot collaboration (HRC) envisions a workspace where humans and robots can dynamically collaborate for improved operational efficiency while maintaining safety. As the effectiveness of HRC is affected by a robot's ability to sense, understand and forecast the state of the collaborating human worker, human action recognition and motion trajectory prediction have become a crucial part in realising HRC. In this chapter, deep-learning-based methods for accomplishing this goal, based on the in-situ sensing data from the workspace are presented. Specifically, to account for the variability and heterogeneity of human workers during assembly, a context-aware deep convolutional neural network (DCNN) has been developed to identify the task-associated context for inferencing human actions. To improve the accuracy and reliability of human motion trajectory prediction, a functional unit-incorporated recurrent neural network (RNN) has been developed to parse worker's motion patterns and forecast worker's future motion trajectories. Collectively, these techniques allow the robot to answer the question: "which tool or part should be delivered to which location next?", and enable online robot action planning and execution for the collaborative assembly operation. The methods developed are experimentally evaluated, with the collaborative assembly of an automotive engine as a case study.
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22.
  • Givehchi, Mohammad, et al. (författare)
  • Function block-enabled operation planning and machine control in Cloud-DPP
  • 2022
  • Ingår i: International Journal of Production Research. - : Informa UK Limited. - 0020-7543 .- 1366-588X. ; , s. 1-17
  • Tidskriftsartikel (refereegranskat)abstract
    • Today, due to shop-floor uncertainties and widespread cross-enterprise collaborations, manufacturing systems of enterprises are increasingly demanded to be agile, adaptive, flexible and interoperable. Process planning systems are mission-critical constituent components of manufacturing systems in machining job shops of small and medium-sized enterprises in the machining and metal cutting sector. Cloud-based adaptive distributed process planning, which includes global supervisory planning in the cloud and local operation planning based on function block and cloud technologies, provides an effective approach for enhancing agility, adaptability, flexibility and interoperability of manufacturing systems. 
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23.
  • Gu, Song, et al. (författare)
  • Gaze Estimation via a Differential Eyes' Appearances Network with a Reference Grid
  • 2021
  • Ingår i: ENGINEERING. - : Elsevier BV. - 2095-8099. ; 7:6, s. 777-786
  • Tidskriftsartikel (refereegranskat)abstract
    • A person's eye gaze can effectively express that person's intentions. Thus, gaze estimation is an important approach in intelligent manufacturing to analyze a person's intentions. Many gaze estimation methods regress the direction of the gaze by analyzing images of the eyes, also known as eye patches. However, it is very difficult to construct a person-independent model that can estimate an accurate gaze direction for every person due to individual differences. In this paper, we hypothesize that the difference in the appearance of each of a person's eyes is related to the difference in the corresponding gaze directions. Based on this hypothesis, a differential eyes' appearances network (DEANet) is trained on public datasets to predict the gaze differences of pairwise eye patches belonging to the same individual. Our proposed DEANet is based on a Siamese neural network (SNNet) framework which has two identical branches. A multi-stream architecture is fed into each branch of the SNNet. Both branches of the DEANet that share the same weights extract the features of the patches; then the features are concatenated to obtain the difference of the gaze directions. Once the differential gaze model is trained, a new person's gaze direction can be estimated when a few calibrated eye patches for that person are provided. Because person specific calibrated eye patches are involved in the testing stage, the estimation accuracy is improved. Furthermore, the problem of requiring a large amount of data when training a person-specific model is effectively avoided. A reference grid strategy is also proposed in order to select a few references as some of the DEANet's inputs directly based on the estimation values, further thereby improving the estimation accuracy. Experiments on public datasets show that our proposed approach outperforms the state-of-the-art methods.
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24.
  • Gu, Song, et al. (författare)
  • Online Video Object Segmentation via Boundary-Constrained Low-Rank Sparse Representation
  • 2019
  • Ingår i: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 7, s. 53520-53533
  • Tidskriftsartikel (refereegranskat)abstract
    • Graphcut-based algorithm is adopted in many video object segmentation systems because different terms can be probabilistically fused together in a framework. Constructing spatio-temporal coherences is an important stage in segmentation systems. However, many steps are involved when computing a key term with good discriminative power. If the cascade steps are adopted, the inaccurate output of the previous step will definitely affect the next step, leading to inaccurate segmentation. In this paper, a key term that is computed by a single framework referred to as boundary-constrained low-rank sparse representation (BCLRSR) is proposed to achieve the accurate segmentation. By treating the elements as linear combinations of dictionary templates, low-rank sparse optimization is adopted to achieve the spatio-temporal saliency. For adding the spatial information to the low-rank sparse model, a boundary constraint is adopted in the framework as a Laplacian regularization. A BCLRSR saliency is then obtained by the represented coefficients, which measure the similarity between the elements in the current frame and the ones in the dictionary. At last, the object is segmented by minimizing the energy function, which is formalized by the spatio-temporal coherences. The experiments on some public datasets show that our proposed algorithm outperforms the state-of-the-art methods.
  •  
25.
  • Guo, Zhengang, et al. (författare)
  • Exploring self-organization and self-adaption for smart manufacturing complex networks
  • 2023
  • Ingår i: Frontiers of Engineering Management. - : Springer Nature. - 2095-7513 .- 2096-0255. ; 10:2, s. 206-222
  • Tidskriftsartikel (refereegranskat)abstract
    • Trends toward the globalization of the manufacturing industry and the increasing demands for small-batch, short-cycle, and highly customized products result in complexities and fluctuations in both external and internal manufacturing environments, which poses great challenges to manufacturing enterprises. Fortunately, recent advances in the Industrial Internet of Things (IIoT) and the widespread use of embedded processors and sensors in factories enable collecting real-time manufacturing status data and building cyber—physical systems for smart, flexible, and resilient manufacturing systems. In this context, this paper investigates the mechanisms and methodology of self-organization and self-adaption to tackle exceptions and disturbances in discrete manufacturing processes. Specifically, a general model of smart manufacturing complex networks is constructed using scale-free networks to interconnect heterogeneous manufacturing resources represented by network vertices at multiple levels. Moreover, the capabilities of physical manufacturing resources are encapsulated into virtual manufacturing services using cloud technology, which can be added to or removed from the networks in a plug-and-play manner. Materials, information, and financial assets are passed through interactive links across the networks. Subsequently, analytical target cascading is used to formulate the processes of self-organizing optimal configuration and self-adaptive collaborative control for multilevel key manufacturing resources while particle swarm optimization is used to solve local problems on network vertices. Consequently, an industrial case based on a Chinese engine factory demonstrates the feasibility and efficiency of the proposed model and method in handling typical exceptions. The simulation results show that the proposed mechanism and method outperform the event-triggered rescheduling method, reducing manufacturing cost, manufacturing time, waiting time, and energy consumption, with reasonable computational time. This work potentially enables managers and practitioners to implement active perception, active response, self-organization, and self-adaption solutions in discrete manufacturing enterprises.
  •  
26.
  • Hu, Kaixiong, et al. (författare)
  • CNN-BiLSTM enabled prediction on molten pool width for thin-walled part fabrication using Laser Directed Energy Deposition
  • 2022
  • Ingår i: JOURNAL OF MANUFACTURING PROCESSES. - : Elsevier BV. - 1526-6125. ; 78, s. 32-45
  • Tidskriftsartikel (refereegranskat)abstract
    • Laser Directed Energy Deposition (LDED) is a promising metal Additive Manufacturing (AM) technology capable of fabricating thin-walled parts to support some high-value applications. Accurate and efficient prediction on the molten pool width is critical to support in-situ control of LDED for part quality assurance. Nevertheless, owing to the intricate physical mechanisms of the process, it is challenging to designing an effective approach to accomplish the prediction target. To tackle the issue, in this research, a new data model-driven predictive approach, which is enabled by a hybrid machine learning model namely CNN-BiLSTM, is presented. High prediction accuracy and efficiency are achievable through innovative measures in the research, that is, (i) the CNN-BiLSTM model is designed and configured by addressing the characteristics of the LDED process; (ii) process parameters related to the deposition and heat accumulation phenomena during the LDED process are extensively considered to strengthen the prediction accuracy. Experiments for thin-walled part fabrication were conducted to validate and benchmark the approach. In average, 4.286% of the mean absolute percentage error (MAPE) was acquired, and the prediction time took by the approach was only 0.04% of that by a finite element analysis (FEA) approach. Compared to the LSTM model, the BiLSTM model and the CNN-LSTM model, MAPEs of the CNN-BiLSTM model were improved by 27.0%, 17.3% and 12.6%, respectively. It demonstrates that the approach is competent in producing good-quality thin-walled parts using the LDED process.
  •  
27.
  • Huang, Sihan, et al. (författare)
  • Industry 5.0 and Society 5.0-Comparison, complementation and co-evolution
  • 2022
  • Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 64, s. 424-428
  • Tidskriftsartikel (refereegranskat)abstract
    • Recently, the futuristic industry and society have caught increasing attention, that is, on Industry 5.0 and Society 5.0. Industry 5.0 is announced by European Commission toward a sustainable, human-centric, and resilient European industry. Society 5.0 is proposed by Japan Cabinet to balance economic advancement with the reso-lution of social problems in Japanese society. Generally, the revolutions of industry and society have profoundly interacted with each other since the first industrial revolution. The coexistence of Industry 5.0 and Society 5.0 could raise varying confusions to be clarified and a series of questions to be answered. Therefore, we attempt to present the comparison, complementation, and co-evolution between Industry 5.0 and Society 5.0 to address the corresponding foundational arguments about Industry 5.0 and Society 5.0, which could be the basic inspiration for future investigation and discussion and accelerate the development of Industry 5.0 and Society 5.0.
  •  
28.
  • Jeong, Yongkuk, et al. (författare)
  • Digital Twin-Based Services and Data Visualization of Material Handling Equipment in Smart Production Logistics Environment
  • 2022
  • Ingår i: Advances in Production Management Systems. Smart Manufacturing and Logistics Systems. - Cham : Springer Nature. ; , s. 556-564
  • Konferensbidrag (refereegranskat)abstract
    • Smart production logistics has introduced in manufacturing industries with emerging technologies such as digital twin, industrial internet of things, and cyber-physical system. This technological innovation initiates the new way of working, working environment, and decision-making process. Especially the decision-making process has changed from experience and intuition to knowledge and data driven. In this paper, digital twin-based services, and data visualization of material handling equipment in smart production logistics environment are presented. There are several applications of digital twin in manufacturing industries already, however feedback from the virtual environment to physical environment and interactions between them which are the essential features of digital twin are very weak in many applications. Therefore, we have developed digital twin-based services in the laboratory scale including feedback and interaction. In addition, data visualization application of material handling equipment in automotive industry is presented to provide insights to the users. Both applications have developed based on the same framework including database and middleware, so it has possibilities to develop further in the future.
  •  
29.
  • Ji, Qinglei, et al. (författare)
  • A Flexible 4D Printing Service Platform for Smart Manufacturing
  • 2020
  • Ingår i: Swedish Production Symposium.
  • Konferensbidrag (refereegranskat)abstract
    • With the extensive application of 3D printing (3DP) in smartmanufacturing, 4D printing (4DP), which enhances 3D printed objects with shapemorphing ability by using smart materials, has shown significant industrial potentialand attracted tremendous attention. One key concern of 4DP is how to effectivelyand quickly meet different production and application requirements considering thecomplexity of materials and diversity of stimulus methods. In order to provide ageneral research platform for 4DP researchers, a flexible 4DP service platform isproposed. Components and modules for building 4DP and test systems are modeledand virtualized to form the different resources. These resources are then integratedvirtually or physically to provide some basic functions such as a 3D displacementstage or a visual monitoring system. According to different 4DP requirements, thesefunctions are then encapsulated into services to serve different research. Theplatform enables a variety of 4DP applications in smart manufacturing environmentssuch as 4D printed magnetic medical robots, test platform for studying the 4DPresponse, etc. A case study on designing a ferromagnetic 4DP platform based on theservice platform is performed to prove the feasibility of the method.
  •  
30.
  • Ji, Qinglei, et al. (författare)
  • Customized protective visors enabled by closed loop controlled 4D printing
  • 2022
  • Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 12:1
  • Tidskriftsartikel (refereegranskat)abstract
    • The COVID-19 pandemic makes protective visors important for protecting people in close contacts. However, the production of visors cannot be increased greatly in a short time, especially at the beginning of the pandemic. The 3D printing community contributed largely in fabricating the visor frames using the rapid and adaptive manufacturing ability. While there are many open source designs of face visors for affordable 3D printers, all these designs fabricate mono-sized frames without considering diverse users’ dimensions. Here, a new method of visor post-processing technology enabled by closed loop controlled 4D printing is proposed. The new process can further deform the printed visor to any customized size for a more comfortable user experience. FEM analysis of the customized visor also shows consistent wearing experience in different circumstances compared with the old visor design. The fabrication precision and time cost of the method is studied experimentally. A case study regarding the reducing, reusing and recycling (3R) of customized visors in classrooms is proposed to enable the customized visors manufactured in a more sustainable way.
  •  
31.
  • Ji, Qinglei, et al. (författare)
  • Design and calibration of 3D printed soft deformation sensors for soft actuator control
  • 2023
  • Ingår i: Mechatronics (Oxford). - : Elsevier BV. - 0957-4158 .- 1873-4006. ; 92, s. 102980-102980
  • Tidskriftsartikel (refereegranskat)abstract
    • Soft actuators made from compliant materials are superior to conventional rigid robots in terms of flexibility, adaptability and safety. However, an inherent drawback of soft actuator is the low actuation precision. Implementing closed loop control is a possible solution, but the soft actuator shape can hardly be measured directly by commercially available sensors, which either are too stiff for integration or cause performance degradation of the actuator. Although 3D printing has been applied to print bendable sensors from conductive materials, they either have larger stiffness than the soft actuator or are made from specially designed materials that are difficult to reproduce. In this study, easily accessible commercial soft conductive material is applied to directly 3D print soft sensors on soft actuators. Different configurations of the printed sensors are studied to investigate how the sensor design affects the performance. The best sensor configuration is selected to provide shape feedback using its changing resistance during deformation. Compared with a commercial flexible bending sensor, the printed sensor has less influences on the soft actuator performance and enjoys higher shape estimation accuracy. Closed loop shape control of the actuator using feedback from the 3D printed sensor is then designed, implemented and compared with the control results using image feedback. A gripper consisting of three individually controlled soft actuators demonstrates the applications of the soft sensor.
  •  
32.
  • Ji, Qinglei, et al. (författare)
  • Design and closed loop control of a 3D printed soft actuator
  • 2020
  • Ingår i: 2020 16th IEEE International Conference on Automation Science and Engineering (CASE). - : IEEE. ; , s. 842-848
  • Konferensbidrag (refereegranskat)abstract
    • Soft robots, made of soft materials such as di-electric elastomer or shape memory polymers, have receivedtremendous attentions due to its dexterousness, flexibility andsafety compared with rigid robots. However, wider applicationof soft robots is limited due to their complex fabrication processand poor controllability. Here, we introduce a closed loopcontrolled soft actuator that is fully 3D printed with flexiblematerial. The structure of the soft actuator is optimized withFinite Element Method (FEM) to acquire shortest fabricationtime and highest deformation for same stimulus input. A desk-top Fused Deposition Modeling (FDM) 3D printer is used forlow-cost fabrication of such actuators. A webcamera is used forthe image feedback which offers the real time shape monitoringof the soft actuator. An output feedback Proportional IntegralDerivative (PID) controller with lowpass filter is developed withpole placement design method based on a data-driven modelof the 3D printed soft actuator. The controller is implementedto regulate the input air pressure to ensure a fast-response, precise and robust shape changing for any work environments.
  •  
33.
  • Ji, Qinglei, et al. (författare)
  • Development of a 3D Printed Multi-Axial Force Sensor
  • 2022
  • Ingår i: Advances in Transdisciplinary Engineering. - : IOS Press.
  • Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
    • Sensors play a vital role in the industry transformation. Commercialsensors such as force sensors have limited options in shapes, stiffness, measuringranges, etc. Customized force sensors optimized for the production environmentcan greatly increase the integration workflow and avoid the trade-off in design freedomof using commercial sensors. 3D printing, as a rapid prototyping technology,offers great potential in fabricating force sensors customized to a specific application.However, most of the existing 3D printed force sensors are limited to onedirectionalsensing, while most of them use materials developed in-house. In thisstudy, a fully 3D printed force sensor using commercial conductive 3D printing materialsis presented. By utilizing the resistance change when under load, the sensorcan estimate the applied force in multiple directions. The resistive performance ofthe prototype 3D printed force sensor is first characterized and then validated in acase study.
  •  
34.
  • Ji, Qinglei, et al. (författare)
  • Feedback control for the precise shape morphing of 4D printed shape memory polymer
  • 2021
  • Ingår i: IEEE Transactions on Industrial Electronics. - : IEEE. - 0278-0046 .- 1557-9948. ; , s. 12698-12707
  • Tidskriftsartikel (refereegranskat)abstract
    • Four-dimensional printing (4DP) is a newly emerged technology that uses smart materials for additive manufacturing and thus enables shape and/or property change upon stimulus after the printing process. Present study on 4DP has been focused on open loop stimulus, which can hardly ensure high shape precision and predictable final states. In this paper, a new closed loop 4DP (CL4DP) process supplementing 4D printed actuation with closed loop control methods is proposed. Image feedback is used for enhancing the conventional open loop 4DP morphing process and a controller is implemented to regulate the intensity of the stimulus accordingly in real-time. To achieve precise control, a nonlinear affine system model is built by model identification with measurement data to describe the dynamic shape recovery process of the 4D printed Shape Memory Polymer (SMP). Precise shape control is achieved and the effects of controller parameters on the precision of CL4DP are studied. Traditionally, SMP has a discrete number of selected steady states. With CL4DP, such steady states can be continuous and arbitrary.
  •  
35.
  • Ji, Qinglei, 1993- (författare)
  • Learning-based Control for 4D Printing and Soft Robotics
  • 2022
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Exploiting novel sensors and actuators made of flexible and smart materials becomes a new trend in robotics research. The studies on the design, production, and control of the new type of robots motivate the research fields of soft robots and 4D printed robots. 3D Printing (3DP) is an additive manufacturing technology that is widely used in printing flexible materials to fabricate soft robots. 4D Printing (4DP) combines 3DP technologies with smart materials to produce transformable devices. 4DP first prints structures with specifically designed responsive materials. When external stimuli such as temperature, voltage, or magnetic field are applied to the printed structure, it changes shape in a programmable way. The shape morphing property of 4DP makes it a novel approach to the actuators of robots.The employment of these special materials empowers these new robots with better compliance and adaptability to the working environment. However, compared with the rigid counterparts, they also have complex dynamic properties such as substantial non-linearity and time-variance. These factors make the precise modeling and robust control of these new robots challenging and thus hinder their potential applications. Focusing on soft robotic systems enabled by 3DP and 4DP approaches, this dissertation studies both traditional and Machine Learning (ML)-based approaches to the modeling, perception, and control of soft, non-linear, and time-variant robotic systems. The main contributions of this dissertation are:The scheme of Closed-Loop (CL) controlled 4DP (CL4DP) using temperature stimulated Shape Memory Polymer (SMP) is designed and validated numerically and experimentally. The feedback control system increases the precision and robustness of the shape morphing process of 4D printed SMP. Applications of CL4DP are explored.Data-driven model identification methods are applied to learn the dynamic model of the shape morphing process of CL4DP and the learned model has good quality to support model-based control design. Model-free and adaptive Reinforcement Learning (RL) controllers are developed to deal with the non-linearity and time variance of 4D printed actuators. To improve the stability and quick adaptability, a concise basis function set is selected instead of blindly using Deep Neural Networks (DNNs).A quadruped robot enabled by soft actuators and its simulation model are developed. The computation efficiency and model accuracy of the simulator are studied and optimized by comparing different simulation methods such as Finite Element Method (FEM) and lumped parameter method.The optimal walking gait pattern of a soft-legged quadruped robot is found by grid parameter search and RL with a physics based simulation model. To speed up the RL training process, modeling tricks are used to reduce the simulation time of the model and curriculum learning is used to reduce the learning time.A soft sensor made by printable conductive materials and 3DP is designed and optimally calibrated to estimate the shape of a pneumatically driven soft actuator. The geometry of the soft sensor is optimally designed for the best linearity, hysteresis and drift properties. The online estimation is based on a linear regression model learned from experimental data.A pneumatically driven soft gripper is developed by 3DP, the printable soft sensor, and pole-placement control methods. The operation of the gripper does not require an external image feedback system to measure its shape, which is estimated by the integrated soft sensor. The position feedback by the soft sensor and the controller by the pole-placement method enable the soft gripper to perform complex tasks with high precision.
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36.
  • Ji, Qinglei, et al. (författare)
  • Omnidirectional walking of a quadruped robot enabled by compressible tendon-driven soft actuators
  • 2022
  • Ingår i: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (<em>IROS 2022</em>), Kyoto, October 23–27, 2022. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 11015-11022
  • Konferensbidrag (refereegranskat)abstract
    • Using soft actuators as legs, soft quadruped robots have shown great potential in traversing unstructured and complex terrains and environments. However, unlike rigid robots whose gaits can be generated using foot pattern design and kinematic model of the rigid legs, the gait generation of soft quadruped robots remains challenging due to the high DoFs of the soft actuators and the uncertain deformations during their contact with the ground. This study is based on a quadruped robot using four Compressible Tendon-driven Soft Actuators (CTSAs) as the legs, with the actuator's compression motion being utilized to improve the walking performance of the robot. For the gait design, an inverse kinematics model considering the compression of the CTSA is developed and validated in simulation. Based on this model, walking gaits realizing different motion speeds and directions are generated. Closed loop direction and speed controllers are developed for increasing the robustness and precision of the robot walking. Simulation and experimental results show that omnidirectional locomotion and complex walking tasks can be realized by tuning the gait parameters and the motions are resistant to external disturbances.
  •  
37.
  • Ji, Qinglei, et al. (författare)
  • Online reinforcement learning for the shape morphing adaptive control of 4D printed shape memory polymer
  • 2022
  • Ingår i: Control Engineering Practice. - : Elsevier. - 0967-0661 .- 1873-6939. ; 126, s. 105257-105257
  • Tidskriftsartikel (refereegranskat)abstract
    • Combining 3D printing and smart materials, 4D printing technologies enable the printed actuators to furtherchange their shapes or other properties after prototyping. However, the shape morphing of 4D printed actuatorssuffers from poor controllability and low precision. One of the main challenges is that the 4D printed actuatorsare hard to be modeled and it is difficult to develop an appropriate controller for them. In this study, variouspopular reinforcement learning (RL) methods are applied to address the problem of online and adaptive model-free control of 4D printed shape memory polymer (SMP). Their training efficiencies are compared and anadaptive LQR controller based on Q learning is developed to realize efficient online learning. The RL controllerachieves precise and quick shape control within 2 − −3 learning episodes and is adaptive to the changingproperties of SMP. The RL controller performance is then compared with a model-based LQR controller andshows high control precision and excellent adaptability to the varying control plant.
  •  
38.
  • Ji, Qinglei, et al. (författare)
  • Optimal shape morphing control of 4D printed shape memory polymer based on reinforcement learning
  • 2022
  • Ingår i: Robotics and Computer-Integrated Manufacturing. - : Elsevier. - 0736-5845 .- 1879-2537. ; 73
  • Tidskriftsartikel (refereegranskat)abstract
    • 4D printing technology, as a new generation of Additive Manufacturing methods, enables printed objectsto further change their shapes or other properties upon external stimuli. One main category of 4D printingresearch is 4D printed thermal Shape Memory Polymer (SMP). Its morphing process has large time delay, isnonlinear time variant, and susceptible to unpredictable disturbances. Reaching an arbitrary position with highprecision is an active research question. This paper applies the Reinforcement Learning (RL) method to developan optimal control method to perform closed loop control of the SMP actuation. Precise and prompt shapemorphing is achieved compared with previous control methods using a PI controller. The training efforts of RLare further reduced by simplifying the optimal control policy using the structural property of the prior trainedresults. Customized protective visors against COVID-19 are fabricated using the proposed control method.
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39.
  •  
40.
  • Ji, Qinglei, et al. (författare)
  • Synthesizing the optimal gait of a quadruped robot with soft actuators using deep reinforcement learning
  • 2022
  • Ingår i: Robotics and Computer-Integrated Manufacturing. - : Elsevier. - 0736-5845 .- 1879-2537. ; 78, s. 102382-102382
  • Tidskriftsartikel (refereegranskat)abstract
    • Quadruped robots have the advantages of traversing complex terrains that are difficult for wheeled robots. Most of the reported quadruped robots are built by rigid parts. This paper proposes a new design of quadruped robots using soft actuators driven by tendons as the four legs. Compared to the rigid robots, the proposed soft quadruped robot has inherent safety, less weight and simpler mechanism for fabrication and control, but the corresponding challenge is that the accurate mathematical model applicable to model-based control design of the soft robot is difficult to derive by dynamics. To synthesize the optimal gait controller of the soft-legged robot, the paper makes the following contributions. First, the flexible components of the quadruped robot are modeled with different finite element and lumped parameter methods. The model accuracy and computation efficiency are analyzed. Second, soft actor–critic methods and curriculum learning are applied to learn the optimal gaits for different walking tasks. Third, The learned gaits are implemented in an in-house robot to transport hand tools. Preliminary results show that the robot can walk forward and correct the walking directions.
  •  
41.
  • Ji, Wei, et al. (författare)
  • Interface architecture design for minimum programming in human-robot collaboration
  • 2018
  • Ingår i: 51st CIRP Conference on Manufacturing Systems. - : Elsevier. ; , s. 129-134
  • Konferensbidrag (refereegranskat)abstract
    • Many metal components, especially large-sized ones, need to be ground or deburred after turning or milling to improve the surface qualities, which heavily depends on human interventions. Robot arms, combining movable platforms, are applied to reduce the human work. However, robots and human should work together due to the fact that most of the large-sized parts belong to small-batch products, resulting in a large number of programming for operating a robot and movable platform. Targeting the problem, this paper proposes a new interface architecture towards minimum programming in human-robot collaboration. Within the context, a four-layer architecture is designed: user interface, function block (FB), functional modules and hardware. The user interface is associated with use cases. Then, FB, with embedded algorithms and knowledge and driven by events, is to provide a dynamic link to the relevant application interface (APIs) of the functional modules in terms of the case requirements. The functional modules are related to the hardware and software functions; and the hardware and humans are considered in terms of the conditions on shop floors. This method provides three-level applications based on the skills of users: (1) the operators on shop floors, can operate both robots and movable platforms programming-freely; (2) engineers are able to customise the functions and tasks by dragging/dropping and linking the relevant FBs with minimum programming; (3) the new functions can be added by importing the APIs through programming.
  •  
42.
  • Ji, W., et al. (författare)
  • Research on modelling of ball-nosed end mill with chamfered cutting edge for 5-axis grinding
  • 2016
  • Ingår i: The International Journal of Advanced Manufacturing Technology. - : Springer London. - 0268-3768 .- 1433-3015. ; 87:9-12
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper presents models related to the manufacturing of ball-nosed end mills of solid carbide (BEMSC) with a chamfered cutting edge (CCE). A parallel grinding wheel (PGW) is selected, and the relationship between CCE face and PGW working face is determined. Based on the geometry models of BEMSC established in our previous work, the centre and axis vectors of PGW are calculated for the grinding of CCE face on bath the ball-nosed end and the cylinder, which is validated through a numerical simulation. In order to produce the tool, a grinding machine, SAACKE UMIF, is chosen. Targeting the grinding data of BEMSC, the transformations are carried out between the coordinate systems of workpiece and the NC programme according to the structural features of the machine. An algorithm is derived for dispersing grinding paths. As a result, the centre data and axis vector are generated with respect to the grinding machine. The BEMSC with CCE is machined using the selected machine, which demonstrates the correctness of the established models. Finally, the performance of the machined cutting tool is validated in comparison with a common BEMSC without CCE in the milling of a mould of a multi-hardness joint structure.
  •  
43.
  • Kemény, Zsolt, et al. (författare)
  • Human-robot collaboration in manufacturing : A multi-agent view
  • 2021
  • Ingår i: Advanced Human-Robot Collaboration in Manufacturing. - Cham : Springer Nature. ; , s. 3-41
  • Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
    • Recent years have witnessed a growing interest in reintroducing the advantages of the human workforce into industrial production processes while keeping the benefits of machines already proven in production automation. Both industry and academia exhibit intense interest in the topic of combining human and robotic resources in collaborative production environments. Nevertheless, the domain of human-robot collaboration is still undergoing intense evolution-nothing proves it more than the diversity of fundamental approaches, world-views, and gaps in standardisation that all hint at the fact that even the overall understanding of the domain is yet to be consolidated. It is, thus, not realistic to expect that a single comprehensive morphological work would reconcile today's multitude of views on human-robot collaboration, and this is not the goal of this introductory chapter either. Instead, the chapter gives an overview of the domain relying on a single selected paradigm, namely, multi-agent systems. This choice is based on the assumption that this branch of distributed artificial intelligence, having matured over several decades of research and application, provides feasible perspectives and terminological waypoints for collaborative settings under the structured circumstances of industrial production. The chapter aims to outline structural properties and mechanisms of collaborative systems from an agent-oriented point of view, and aims to provide a reference of terms and concepts which make many different views of the domain comparable. Further chapters of this book, as well as numerous application examples, known industrial solutions and standards, are positioned within this framework to connect theoretical waypoints and practical findings.
  •  
44.
  • Lei, P., et al. (författare)
  • MTConnect compliant monitoring for finishing assembly interfaces of large-scale components : A vertical tail section application
  • 2017
  • Ingår i: Journal of manufacturing systems. - : Elsevier B.V.. - 0278-6125 .- 1878-6642. ; 45, s. 121-134
  • Tidskriftsartikel (refereegranskat)abstract
    • Monitoring is a significant issue for finishing the assembly interfaces of large-scale components before final assembly. Acquisition and supervision of the pivotal data is essential to ensure the security and reliability for machining the large and complicated components with high-value. This process is generally cumbersome and time-consuming because there are various types of data coming from different components and sensors. The problem becomes more serious when considering the whole shop floor. Recently, MTConnect has been proven to be an effective method to realize standardized data collection and monitoring process. However, MTConnect is still under development and cannot cover the whole finishing process such as on-machining measuring (OMM) and fixturing. To address the issue, an MTConnect compliant method with extended data models is proposed in this paper to implement a standardized monitoring system. Firstly, a finishing system for the assembly interfaces is introduced, including the framework, workflow and key procedures and data. Then extended MTConnect data models are proposed to represent the finishing system including on-machine touch-trigger probe and sensor-based intelligent fixturing related information. Based on the extended MTConnect data models, a web-based monitoring system is developed for data collection and monitoring by combining an MTConnect agent and an OPC adapter. The proposed approach is validated by collecting and monitoring the key process data using an airplane vertical tail as an application. The advantages of using MTConnect would be more significant when extended to the entire factory and implemented in cloud manufacturing in the future.
  •  
45.
  • Leng, Jiewu, et al. (författare)
  • Industry 5.0 : Prospect and retrospect
  • 2022
  • Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 65, s. 279-295
  • Tidskriftsartikel (refereegranskat)abstract
    • Industry 5.0 blows the whistle on global industrial transformation. It aims to place humans' well-being at the center of manufacturing systems, thereby achieving social goals beyond employment and growth to provide prosperity robustly for the sustainable development of all humanity. However, the current exploration of Industry 5.0 is still in its infancy where research findings are relatively scarce and little systematic. This paper first reviews the evolutionary vein of Industry 5.0 and three leading characteristics of Industry 5.0: human-centricity, sustainability, and resiliency. The connotation system of Industry 5.0 is discussed, and its diversified essence is analyzed. Then, this paper constructs a tri-dimension system architecture for implementing Industry 5.0, namely, the technical dimension, reality dimension, and application dimension. The paper further discusses key enablers, the future implementation path, potential applications, and challenges of realistic scenarios of Industry 5.0. Finally, the limitations of the current research are discussed with potential future research directions highlighted. It is expected that this review work will arouse lively discussions and debates, and bring together the strengths of all beings for building a comprehensive system of Industry 5.0.
  •  
46.
  • Leng, Jiewu, et al. (författare)
  • Unlocking the power of industrial artificial intelligence towards Industry 5.0: Insights, pathways, and challenges
  • 2024
  • Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 73, s. 349-363
  • Forskningsöversikt (refereegranskat)abstract
    • With the continuous development of human-centric, resilient, and sustainable manufacturing towards Industry 5.0, Artificial Intelligence (AI) has gradually unveiled new opportunities for additional functionalities, new features, and tendencies in the industrial landscape. On the other hand, the technology-driven Industry 4.0 paradigm is still in full swing. However, there exist many unreasonable designs, configurations, and implementations of Industrial Artificial Intelligence (IndAI) in practice before achieving either Industry 4.0 or Industry 5.0 vision, and a significant gap between the individualized requirement and actual implementation result still exists. To provide insights for designing appropriate models and algorithms in the upgrading process of the industry, this perspective article classifies IndAI by rating the intelligence levels and presents four principles of implementing IndAI. Three significant opportunities of IndAI, namely, collaborative intelligence, self-learning intelligence, and crowd intelligence, towards Industry 5.0 vision are identified to promote the transition from a technology-driven initiative in Industry 4.0 to the coexistence and interplay of Industry 4.0 and a value-oriented proposition in Industry 5.0. Then, pathways for implementing IndAI towards Industry 5.0 together with key empowering techniques are discussed. Social barriers, technology challenges, and future research directions of IndAI are concluded, respectively. We believe that our effort can lay a foundation for unlocking the power of IndAI in futuristic Industry 5.0 research and engineering practice.
  •  
47.
  • Li, Chengxi, et al. (författare)
  • Deep reinforcement learning in smart manufacturing : A review and prospects
  • 2023
  • Ingår i: CIRP - Journal of Manufacturing Science and Technology. - : Elsevier BV. - 1755-5817 .- 1878-0016. ; 40, s. 75-101
  • Forskningsöversikt (refereegranskat)abstract
    • To facilitate the personalized smart manufacturing paradigm with cognitive automation capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by offering an adaptive and flexible solution. DRL takes the advantages of both Deep Neural Networks (DNN) and Reinforcement Learning (RL), by embracing the power of representation learning, to make precise and fast decisions when facing dynamic and complex situations. Ever since the first paper of DRL was published in 2013, its applications have sprung up across the manufacturing field with exponential publication growth year by year. However, there still lacks any comprehensive review of the DRL in the field of smart manufacturing. To fill this gap, a systematic review process was conducted, with 261 relevant publications selected to date (20-Oct-2022), to gain a holistic understanding of the development, application, and challenges of DRL in smart manufacturing along the whole engineering lifecycle. First, the concept and development of DRL are summarized. Then, the typical DRL applications are analyzed in the four engineering lifecycle stages: design, manufacturing, dis-tribution, and maintenance. Finally, the challenges and future directions are illustrated, especially emerging DRL-related technologies and solutions that can improve the manufacturing system's deployment feasi-bility, cognitive capability, and learning efficiency, respectively. It is expected that this work can provide an insightful guide to the research of DRL in the smart manufacturing field and shed light on its future perspectives.
  •  
48.
  • Li, S., et al. (författare)
  • Dynamic Scene Graph for Mutual-Cognition Generation in Proactive Human-Robot Collaboration
  • 2022
  • Ingår i: Procedia CIRP. - : Elsevier B.V.. - 2212-8271. ; , s. 943-948
  • Konferensbidrag (refereegranskat)abstract
    • Human-robot collaboration (HRC) plays a crucial role in agile, flexible, and human-centric manufacturing towards the mass personalization transition. Nevertheless, in today's HRC tasks, either humans or robots need to follow the partners' commands and instructions along collaborative activities progressing, instead of proactive, mutual engagement. The non-semantic perception of HRC scenarios impedes mutually needed, proactive planning and high-cognitive capabilities in existing HRC systems. To overcome the bottleneck, this research explores a dynamic scene graph-based method for mutual-cognition generation in Proactive HRC applications. Firstly, a spatial-attention object detector is utilized to dynamically perceive objects in industrial settings. Secondly, a linking prediction module is leveraged to construct HRC scene graphs. An attentional graph convolutional network (GCN) is utilized to capture relations between industrial parts, human operators, and robot operations and reason structural connections of human-robot collaborative processing as graph embedding, which links to mutual planners for human operation supports and robot proactive instructions. Lastly, the Proactive HRC implementation is demonstrated on disassembly tasks of aging electronic vehicle batteries (EVBs) and evaluate its mutual-cognition capabilities. 
  •  
49.
  • Li, Shufei, et al. (författare)
  • Self-organising multiple human-robot collaboration : A temporal subgraph reasoning-based method
  • 2023
  • Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 68, s. 304-312
  • Tidskriftsartikel (refereegranskat)abstract
    • Multiple Human-Robot Collaboration (HRC) requires self-organising task allocation to adapt to varying operation goals and workspace changes. However, nowadays an HRC system relies on predefined task arrangements for human and robot agents, which fails to accomplish complicated manufacturing tasks consisting of various operation sequences and different mechanical parts. To overcome the bottleneck, this paper proposes a temporal subgraph reasoning-based method for self-organising HRC task planning between multiple agents. Firstly, a tri-layer Knowledge Graph (KG) is defined to depict task-agent-operation relations in HRC tasks. Then, a subgraph mechanism is introduced to learn node embeddings from subregions of the HRC KG, which distills implicit information from local object sets. Thirdly, a temporal reasoning module is leveraged to integrate features from previous records and update the HRC KG for forecasting humans' and robots' subsequent operations. Finally, a car engine assembly task is demonstrated to evaluate the effectiveness of the proposed method, which outperforms other benchmarks in experimental results.
  •  
50.
  • Li, Shufei, et al. (författare)
  • Towards Mutual-Cognitive Human-Robot Collaboration : A Zero-Shot Visual Reasoning Method
  • 2023
  • Ingår i: 2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023. - : Institute of Electrical and Electronics Engineers (IEEE).
  • Konferensbidrag (refereegranskat)abstract
    • Human-Robot Collaboration (HRC) is showing the potential of widespread application in today's human-centric smart manufacturing, as prescribed by Industry 5.0. To enable safe and efficient collaboration, numerous visual perception methods have been explored, which allows the robot to perceive surroundings and plan collision-free, reactive manipulations. However, current visual perception approaches can only convey basic information between robots and humans, falling short of semantic knowledge. With this limitation, HRC cannot guarantee smooth operation when confronted with similar yet unseen situations in real-world applications. Therefore, a mutual-cognitive HRC architecture is proposed to plan human and robot operations based on the learning of knowledge representation of onsite situations and task structures. A zero-shot visual reasoning approach is introduced to derive suitable teamwork strategies in the mutual-cognitive HRC from perceived results, including human actions and detected objects. It assigns adaptive robot path planning and knowledge support for humans by incorporating perception components into a knowledge graph, even when dealing with a new but similar HRC task. Lastly, the significance of the proposed mutual-cognitive HRC system is revealed through its evaluation in collaborative disassembly tasks of aging electric vehicle batteries.
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