Review
Computer Science, Interdisciplinary Applications
Angela Carrera-Rivera, Felix Larrinaga, Ganix Lasa
Summary: Smart-Product Service Systems (S-PSS) are a novel strategy that integrates smart products and their related e-services to fulfill user's needs in context-dependent environments. S-PSS has the potential to promote economically, ecologically, and socially sustainable practices and business models. However, the utilization of the digital capabilities of smart products and their services in design and enhancing user experience is currently limited. This study focuses on the Context-awareness capability and contributes to the research on S-PSS by conducting a systematic literature review and analyzing case studies.
COMPUTERS IN INDUSTRY
(2022)
Article
Computer Science, Interdisciplinary Applications
Zuoxu Wang, Chun-Hsien Chen, Pai Zheng, Xinyu Li, Wenyan Song
Summary: Smart product-service system is a heterogeneous and integrated system that allows manufacturers/service providers to deliver integrated and customized product-service bundles in a sustainable manner. This paper proposes a novel hypergraph-based Smart PSS configuration framework to address the issues of inaccurate user-provided technical attributes and limitations of existing PSS configurators.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Tongtong Zhou, Zhihua Chen, Yong Cao, Rui Miao, Xinguo Ming
Summary: This paper proposes a framework for user experience-oriented smart service requirement analysis in the development of smart PSS. The framework integrates factors such as user personas and activity journey to conceptualize the user experience in smart PSS. A four-phase model is introduced to identify user experience requirements, and a novel evaluation approach is developed to assess the priority of these requirements.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Engineering, Industrial
Zuoxu Wang, Chun-Hsien Chen, Pai Zheng, Xinyu Li, Li Pheng Khoo
Summary: The paradigm of Smart product-service systems (Smart PSS) utilizes cutting-edge ICT and AI techniques to enable smart and data-driven design. A graph-based context-aware requirement elicitation approach is proposed, leveraging ontologies and Deepwalk technique. An example of smart bike share system is used to demonstrate the feasibility and effectiveness of the approach.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Xinyu Li, Zuoxu Wang, Chun-Hsien Chen, Pai Zheng
Summary: The pursuit of higher sustainability and extended product lifecycle in companies' design/development efforts has led to the introduction of concepts like the smart circular system and Smart PSS. However, existing studies often overlook cyber-physical resources in the sustainability discussion, highlighting the need for an integrated strategy for Sustainable Smart PSS. This paper proposes a data-driven reversible framework to exploit information/knowledge for Sustainable Smart PSS development, with a focus on context-aware processes to support decision-making and optimization. The framework is illustrated with the sustainable development of a 3D printer, showcasing the feasibility and advantages of this approach for Smart PSS development in a cyber-physical environment.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Green & Sustainable Science & Technology
Lingguo Bu, Chun-Hsien Chen, Kam K. H. Ng, Pai Zheng, Guijun Dong, Heshan Liu
Summary: This study aims to explore how to develop value-added smart PSS based on VR, verify feasibility through a case study, and consider user performance and experience by simultaneously considering user-generated and VR system-generated data. The results of the study show that the smart VR rowing machine significantly enhances user experience, providing value-added services and real-time data feedback.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Computer Science, Information Systems
Ako A. Jaafar, Dayang N. A. Jawawi, Mohd Adham Isa, Nor Azizah Saadon
Summary: This study proposes a model for service selection based on user intentions and context, which evaluates user preferences for services by calculating QoS importance based on user behavior history and context. It utilizes a dynamic K-Skyline method and a multi-criteria decision-making technique to efficiently select and rank services. A case study and experiment validate the effectiveness and robustness of the proposed model.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Jingchen Cong, Chun-Hsien Chen, Xuan Meng, Zhongxia Xiang, Liang Dong
Summary: As an emerging IT-driven business paradigm, smart product-service system (Smart PSS) offers both smart, connected products and generated services, making it a significant research topic. This study proposes a conceptual design method for Smart PSS by analyzing user-generated emotions/feelings. Traditional products are identified, and their public review data is used to analyze user emotions/feelings. An interactive emotion board is introduced as a design tool to organize user-generated emotions/feelings and potential design points. The AHP is utilized for evaluating the improved solution.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Jingchen Cong, Pai Zheng, Yuan Bian, Chun-Hsien Chen, Jianmin Li, Xinyu Li
Summary: Smart product-service system (Smart PSS) leverages smart, connected products to improve user satisfaction. An iterative design method is proposed to enhance user experience and automate user satisfaction prediction using machine learning. The case study demonstrates the effectiveness of the proposed approach.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Danni Chang, Fan Li, Jiao Xue, Liqun Zhang
Summary: With the advancement of information and communication technologies, the research on smart product-service system (PSS) has gained attention. However, there are still uncertainties in identifying multi-source requirements, defining innovative smart connected products (SCPs) features, and specifying functional and data service configuration solutions.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Engineering, Industrial
Yupeng Li, Mengting Zhang, Na Zhang, Hongyan Jiang
Summary: In the field of engineering design, design for evolution is an economic and effective approach to address changing customer requirements. This study establishes an evolution model to quantify the product evolution degree and applies it to a case study of iPhone, demonstrating its effectiveness in forecasting future trends.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Xianyu Zhang, LuCheng Chen, GuoJun Sheng, XiaoPing Lu, Xinguo Ming
Summary: This paper studies the innovation service system for Customer-product Interaction Life Cycle (CILC) in Smart Product Service System (SPSS) under the new model of mass personalization. Firstly, a comprehension service system for CILC in SPSS is proposed to provide the framework and decision-making for enterprises. Secondly, a personalized service recommendation for CILC in SPSS based on improved collaborative filtering algorithm is proposed to expand and enhance the service resources for enterprises. Thirdly, a calculation example of personalized service recommendation for CILC in SPSS is given. The research of this paper extends and complements the theory of SPSS, and provides a reference for enterprises to plan, set, select, carry out, and maintain service items for CILC in SPSS.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Interdisciplinary Applications
Wenyan Song, Zixuan Niu, Pai Zheng
Summary: This paper introduces an integrated method that combines subjective and objective weights to improve the accuracy of evaluation. By integrating the Best Worst Method and Criteria Importance Though Inter-criteria Correlation method, as well as utilizing Rough Set Theory to flexibly deal with decision-making vagueness, a new method for Smart PSS design concept selection is proposed.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Business
Lucas Santos Dalenogare, Marie-Anne Le Dain, Guilherme B. Benitez, Nestor F. Ayala, Alejandro G. Frank
Summary: This study aims to understand how multichannel digital services can be supported by the integration of real-time data from service ecosystems to provide Smart PSS business models. Using the organizational information-processing theory, the study considers the integration of data from ecosystem actors (other business units, suppliers, and customers). Through a survey of 92 manufacturers, the study provides a typology of different Smart PSS business models and reveals the flow of data in the ecosystem.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Computer Science, Artificial Intelligence
Tongtong Zhou, Xinguo Ming, Ting Han, Yuguang Bao, Xiaoqiang Liao, Qingfei Tong, Shangwen Liu, Hao Guan, Zhihua Chen
Summary: Smart product service system (PSS) is crucial for manufacturing companies to transform towards digital servitization. The paper proposes a methodology to elicit and analyze diverse and inter-related smart experience-oriented customer requirements (SEO-CRs) in smart PSS context. A two-dimensional SEO-CR system and a HFLC-DEMATEL method are introduced to effectively evaluate the priority and interaction of SEO-CRs. The proposed method is validated through a real case of smart vehicle service system (SVSS).
ADVANCED ENGINEERING INFORMATICS
(2023)
Review
Engineering, Industrial
Chao Liu, Pai Zheng, Xun Xu
Summary: This paper presents a systematic literature review on the digitalisation and servitisation of machine tools in the context of Industry 4.0. The review provides a comprehensive understanding of recent advancements in this field, including key technologies, methods, standards, architectures, and applications. Additionally, a novel conceptual framework called Cyber-Physical Machine Tool (CPMT) is proposed as a systematic approach to achieving digitalisation and servitisation of next-generation machine tools. The paper also discusses major research issues, challenges, and future research directions.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Geng Zhang, Chun-Hsien Chen, Bufan Liu, Xinyu Li, Zuoxu Wang
Summary: With the rapid development of information technologies, shared manufacturing is facing a growing need for monitoring and maintenance. Existing research primarily focuses on a resource-centric strategy for management, overlooking the experience data from users/customers. To fill this gap, a hybrid sensing-based approach is proposed for monitoring and maintenance of shared manufacturing resources.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Editorial Material
Engineering, Multidisciplinary
Xinyu Li, Pai Zheng, Jinsong Bao, Liang Gao, Xun Xu
Article
Computer Science, Artificial Intelligence
Yongshi Liang, Pai Zheng, Liqiao Xia
Summary: Enabled by advanced data analytics and intelligent computing, this study proposes a visual reasoning-based approach to present drivers with perceptual, predictive, and reasoning information onto augmented reality head-up displays (AR-HUDs) toward cognitive intelligence. A driving scenario knowledge graph is established, and the driving scene is comprehensively perceived through analyzing video streams and images collected by an in-car visual camera. A graph-based driving scenario reasoning model is built for driving strategy recommendations. The analyzed information is intuitively shown on the HUDs via pre-defined AR graphics. A case study is provided to prove its feasibility.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Engineering, Industrial
Qinge Xiao, Zhile Yang, Yingfeng Zhang, Pai Zheng
Summary: Batch machining systems are crucial for productivity and quality improvement but consume significant energy due to continuous interaction with machine tools, workpieces, and cutting tools. This study focuses on adaptive process control considering time-varying tool wear using reinforcement learning (RL). An energy-efficient decision model is developed using the Markov decision process, and an actor-critic RL framework is proposed for dynamic process control. Experimental results show that the RL method can reduce energy consumption by over 20% compared to optimization ignoring tool wear effects and has three times faster learning efficiency than metaheuristic methods.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Review
Engineering, Industrial
Shimin Liu, Jinsong Bao, Pai Zheng
Summary: Digital twin (DT) technology is becoming a hot topic in intelligent machining as it enables quality control of the dynamic cutting process through the establishment of high-fidelity DT models. However, there is a lack of clear and systematic analysis of DT-driven machining. This study conducted a state-of-the-art survey, classifying the concepts, analyzing the characteristics and processes, and proposing future research directions to promote further discussions and research in this field.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Tianyuan Liu, Pai Zheng, Jinsong Bao, Huabin Chen
Summary: This paper provides a comprehensive review and discussion of WRIA, including the challenges faced, the evolutionary paths, and specific application tasks. It also explores potential future perspectives for WRIA, offering useful insights to both academic researchers and industrial practitioners.
Article
Computer Science, Interdisciplinary Applications
Chengxi Li, Pai Zheng, Yue Yin, Yat Ming Pang, Shengzeng Huo
Summary: With the emergence of Industry 5.0, there is a need for human workers and manufacturing equipment, such as robots, to interact in dealing with dynamic and complex production tasks. This study proposes a mutual-cognitive safe human-robot interaction approach to address the safety requirements. The approach includes worker visual augmentation, robot velocity control, Digital Twin-enabled motion preview and collision detection, and Deep Reinforcement Learning-based robot collision avoidance motion planning in an Augmented Reality-assisted manner.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Computer Science, Interdisciplinary Applications
Peng Zhou, Pai Zheng, Jiaming Qi, Chengxi Li, Anqing Duan, Maggie Xu, Victor Wu, David Navarro-Alarcon
Summary: Silicone sealing, with its excellent chemical and mechanical properties, is commonly used in various industries. Due to labor shortages, there is a need for automated solutions for sealing tasks. This paper presents a new method that uses vision-guided robotic systems to automate silicone sealing, utilizing a neural path planning framework and a Riemannian motion policy.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Review
Computer Science, Interdisciplinary Applications
Shufei Li, Pai Zheng, Sichao Liu, Zuoxu Wang, Xi Vincent Wang, Lianyu Zheng, Lihui Wang
Summary: This paper discusses the importance of human-robot collaboration in smart manufacturing. Existing development in this area is either human-dominant or robot-dominant, lacking efficient integration of robotic automation and human cognition. Proactive human-robot collaboration is proposed as a solution, allowing multiple agents to collaboratively operate based on each other's needs and capabilities. The paper also highlights current challenges and future research directions in this field.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Materials Science, Characterization & Testing
Tianyuan Liu, Pai Zheng, Xiaojia Liu
Summary: This study proposes a multiple scale spaces segmentation method to address the complexity of scale variability and contextual relationships in welding defect segmentation. By constructing multi-scale feature space, semantic space, and relational space, it effectively segments complex welding defects.
NDT & E INTERNATIONAL
(2023)
Article
Automation & Control Systems
Liqiao Xia, Pai Zheng, Jinjie Li, Xiao Huang, Robert X. Gao
Summary: Data-driven approaches are widely used in fault diagnosis, but the lack of sufficient labels and data privacy protection remain challenges in real-world manufacturing scenarios. This study proposes a federated learning model using histogram-based gradient boosting tree, which protects data privacy by only communicating relevant local model parameter updates and introduces a data compensation mechanism to address data volume disparity.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Engineering, Industrial
Kendrik Yan Hong Lim, Theresia Stefanny Yosal, Chun-Hsien Chen, Pai Zheng, Lihui Wang, Xun Xu
Summary: The increasing complexity of industrial systems requires more effective and intelligent maintenance approaches to address manufacturing defects. This paper introduces a cognitive digital twin system that leverages industrial knowledge graphs to support maintenance planning and operations. The system can manage interconnected systems, facilitate cross-domain analysis, and generate feasible solutions validated through simulation. It can also identify potential disruptions in new product designs.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Review
Engineering, Industrial
Jiewu Leng, Yuanwei Zhong, Zisheng Lin, Kailin Xu, Dimitris Mourtzis, Xueliang Zhou, Pai Zheng, Qiang Liu, J. Leon Zhao, Weiming Shen
Summary: Manufacturers are realizing the importance of system resilience and considering the use of Decentralized Autonomous Organization (DAO) to achieve decentralized autonomous manufacturing and resilient Industry 5.0 vision. This paper reviews the literature on Decentralized Manufacturing (DM) and Autonomous Manufacturing (AM), and proposes a manufacturing paradigm called Decentralized Autonomous Manufacturing (DAM). Future research directions and challenges of DAM are highlighted.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Fangyu Chen, Yongchang Wei, Hongchang Ji, Gangyan Xu
Summary: This paper introduces a dual-layer network analytical framework for evaluating standard systems in construction safety management and validates its effectiveness through a case study. The research findings suggest that key standards often encompass a wider array of risks, providing suggestions for revising construction standards.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Minghao Li, Qiubing Ren, Mingchao Li, Ting Kong, Heng Li, Huijing Tian, Shiyuan Liu
Summary: This study proposes a method using digital twin technology to construct a collision early warning system for marine piling. The system utilizes a five-dimensional model and four independently maintainable development modules to maximize its effectiveness. The pile positioning algorithm and collision early warning algorithm are capable of providing warnings for complex pile groups.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Seokhyun Ryu, Sungjoo Lee
Summary: This study proposes the use of patent information to develop a robust technology tree and applies it to the furniture manufacturing process. Through methods such as clustering analysis, semantic analysis, and association-rule mining, technological attributes and their relationships are extracted and analyzed. This approach provides meaningful information to improve the understanding of a target technology and supports research and development planning.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Shuai Ma, Kechen Song, Menghui Niu, Hongkun Tian, Yanyan Wang, Yunhui Yan
Summary: This paper proposes a feature-based domain disentanglement and randomization (FDDR) framework to improve the generalization of deep models in unseen datasets. The framework successfully addresses the appearance difference issue between training and test images by decomposing the defect image into domain-invariant structural features and domain-specific style features. It also utilizes randomly generated samples for training to further expand the training sample.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Fang Xu, Tianyu Zhou, Hengxu You, Jing Du
Summary: This study explores the impact of AR-based egocentric perspectives on indoor wayfinding performance. The results reveal that participants using the egocentric perspective demonstrate improved efficiency, reduced cognitive load, and enhanced spatial awareness in indoor navigation tasks.
ADVANCED ENGINEERING INFORMATICS
(2024)
Review
Computer Science, Artificial Intelligence
Yujie Lu, Shuo Wang, Sensen Fan, Jiahui Lu, Peixian Li, Pingbo Tang
Summary: Image-based 3D reconstruction plays a crucial role in civil engineering by bridging the gap between physical objects and as-built models. This study provides a comprehensive summary of the field over the past decade, highlighting its interdisciplinary nature and integration of various technologies such as photogrammetry, 3D point cloud analysis, semantic segmentation, and deep learning. The proposed 3D reconstruction knowledge framework outlines the essential elements, use phases, and reconstruction scales, and identifies eight future research directions. This review is valuable for scholars interested in the current state and future trends of image-based 3D reconstruction in civil engineering, particularly in relation to deep learning methods.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Hang Zhang, Wenhu Wang, Shusheng Zhang, Yajun Zhang, Jingtao Zhou, Zhen Wang, Bo Huang, Rui Huang
Summary: This paper presents a novel framework for segmenting intersecting machining features using deep reinforcement learning. The framework enhances the effectiveness of intersecting machining feature segmentation by leveraging the robust feature representation, decision-making, and automatic learning capabilities of deep reinforcement learning. Experimental results demonstrate that the proposed approach successfully addresses some existing challenges faced by several state-of-the-art methods in intersecting machining feature segmentation.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Chao Zhao, Weiming Shen
Summary: This paper proposes a semantic-discriminative augmentation-driven network for imbalanced domain generalization fault diagnosis, which enhances the model's generalization capabilities through synthesizing reliable samples and optimizing representations.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Ching-Chih Chang, Teng-Wen Chang, Hsin-Yi Huang, Shih-Ting Tsai
Summary: Ideation is the process of generating ideas through exploring visual and semantic stimuli for creative problem-solving. This process often requires changes in user goals and insights. Using pre-designed content and semantic-visual concepts for ideation can introduce uncertainty. An adaptive workflow is proposed in this study that involves extracting and summarizing semantic-visual features, using clusters of adapted information for multi-label classification, and constructing a design exploration model with visualization and exploration.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Zhen Wang, Shusheng Zhang, Hang Zhang, Yajun Zhang, Jiachen Liang, Rui Huang, Bo Huang
Summary: This research proposes a novel approach for machining feature process planning using graph convolutional neural networks. By representing part information with attribute graphs and constructing a learning model, the proposed method achieves higher accuracy and resolves current limitations in machining feature process planning.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Hong-Wei Xu, Wei Qin, Jin-Hua Hu, Yan-Ning Sun, You -Long Lv, Jie Zhang
Summary: Wafer fabrication is a complex manufacturing system, where understanding the correlation between parameters is crucial for identifying the cause of wafer defects. This study proposes a Copula network deconvolution-based framework for separating direct correlations, which involves constructing a complex network correlation diagram and designing a nonlinear correlation metric model. The proposed method enables explainable fault detection by identifying direct correlations.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Yida Hong, Wenqiang Li, Chuanxiao Li, Hai Xiang, Sitong Ling
Summary: An adaptive push method based on feature transfer is proposed to address sparsity and cold start issues in product intelligent design. By constructing a collaborative filtering algorithm model and transforming the rating model, the method successfully alleviates data sparsity and cold start problems.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Hairui Fang, Jialin An, Bo Sun, Dongsheng Chen, Jingyu Bai, Han Liu, Jiawei Xiang, Wenjie Bai, Dong Wang, Siyuan Fan, Chuanfei Hu, Fir Dunkin, Yingjie Wu
Summary: This work proposes a model for real-time fault diagnosis and distance localization on edge computing devices, achieving lightweight design and high accuracy in complex environments. It also demonstrates a high frame rate on edge computing devices, providing a novel solution for industrial practice.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Yujun Jiao, Xukai Zhai, Luyajing Peng, Junkai Liu, Yang Liang, Zhishuai Yin
Summary: This paper proposes a digital twin-based motion forecasting framework that predicts the future trajectories of workers on construction sites, accurately predicting workers' motions in potential risk scenarios.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Ling-Zhe Zhang, Xiang-Dong Huang, Yan-Kai Wang, Jia-Lin Qiao, Shao-Xu Song, Jian-Min Wang
Summary: Time-series DBMSs based on the LSM-tree have been widely applied in various scenarios. The characteristics of time-series data workload pose challenges to efficient queries. To address issues like query latency and inaccurate range, we propose a novel compaction algorithm called Time-Tiered Compaction.
ADVANCED ENGINEERING INFORMATICS
(2024)