Article
Computer Science, Interdisciplinary Applications
Raj Jiten Machchhar, Carl Nils Konrad Toller, Alessandro Bertoni, Marco Bertoni
Summary: This paper systematically reviews the kind of data being collected from the operational stage, the purposes being achieved from that data, and how they lead to value creation in Smart Product Service Systems. It highlights the current gaps in the literature and raises opportunities for future contributions.
COMPUTERS IN INDUSTRY
(2022)
Article
Green & Sustainable Science & Technology
Ujjwal Nag, Satyendra Kumar Sharma, Sidhartha S. Padhi
Summary: This study discusses the feasible solution in Indian wind farms to extend the life cycle of aging wind turbines instead of repowering. The study proposes a research framework consisting of two stages, focusing on the elicitation of customer value requirements and the evaluation methodology for prioritizing and ranking these requirements using Fuzzy AHP. The findings reveal the highest priority and weight in the category of Repair, Upgrade, and Debugging, named as Improved perceived performance and Smart monitoring.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Computer Science, Artificial Intelligence
Ke Zhang, Kuo-Yi Lin, Jinfeng Wang, Yakun Ma, Huailiang Li, Luyao Zhang, Kehui Liu, Lijie Feng
Summary: With the rise of digital servitization, smart product-service systems (smart PSS) have become a new source of revenue and competitive advantage for manufacturers. However, the heterogeneity of smart PSS requirements, the use of user-generated data, and data-driven approaches have not been sufficiently considered. This study develops a UNISON framework that integrates deep learning techniques to effectively elicit and evaluate user requirements for smart PSS in a systematic, data-driven, and quantitative manner.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Business
Christopher Agyapong Siaw, David Sarpong
Summary: The article examines the opportunities for knowledge-intensive entrepreneurship (KIE) firms and existing firms to co-create and co-capture value in ecosystems through open sources and digital platforms. By developing the 'dynamic exchange capabilities (DEC) framework', it highlights the transient nature of exchanges in ecosystems and how they can impact relationships and resource integration between firms.
JOURNAL OF BUSINESS RESEARCH
(2021)
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
Business
Md Afnan Hossain, Shahriar Akter, Venkata Yanamandram
Summary: Advances in data-driven marketing analytics have accelerated the development of value creation in recent years, with a focus on the potential of customer data and analytics in creating new pathways for value creation. This research develops and validates a hierarchical model on customer analytics-driven value creation capability in the big data analytics spectrum, revealing that customer linking plays a crucial mediating role in sustaining competitive advantage. The paper discusses key theoretical and practical contributions, as well as suggests future research directions.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Hospitality, Leisure, Sport & Tourism
Ioannis Assiouras, Niklas Vallstrom, George Skourtis, Dimitrios Buhalis
Summary: This study investigates the principles and factors influencing interaction for resource integration during service mega-disruptions in the tourism ecosystem. The study reveals that following interaction principles such as willingness to exchange, access to information, dialogue, transparency, coordination, adaptation, and informed risk assessment leads to value co-creation, while failure to follow these principles can result in value no-creation or value co-destruction. The most critical factors influencing interaction for resource integration during mega-disruptions are traveler's safety needs, initiation of travel cancellation, sympathy, proactivity, omnichannel communication, effectiveness of technology and employees, and the number of involved actors.
CURRENT ISSUES IN TOURISM
(2023)
Article
Hospitality, Leisure, Sport & Tourism
Ioannis Assiouras, Niklas Vallstroem, George Skourtis, Dimitrios Buhalis
Summary: This paper explores the role of value propositions, practices, and institutions in the tourism ecosystem during COVID-19 and discusses value co-creation and co-destruction. The findings reveal that customers prioritize eudemonic well-being during service mega-disruptions and show sympathy for the well-being of tourism firms. However, customers expect reciprocity, honesty, transparency, and flexibility from tourism firms. The misalignment of practices and routines caused value co-destruction during the service mega-disruption of COVID-19. The paper suggests that value co-creation can be achieved when actors demonstrate altruism, solidarity, and shared intentions to protect the well-being of the ecosystem's actors.
ANNALS OF TOURISM RESEARCH
(2022)
Article
Business
Haksin Chan, Morgan X. Yang, Kevin J. Zeng
Summary: This research focuses on the strategic design of ratings and reviews systems on multi-sided platforms to ensure a steady flow of buyer-generated product knowledge. It presents a theoretical model and identifies exemplary practices through exploratory observations, contributing to theory and practice in the field of multi-sided platforms.
JOURNAL OF BUSINESS RESEARCH
(2022)
Article
Environmental Studies
Xavier Font, Rosa English, Alkmini Gkritzali, Wen (Stella) Tian
Summary: By applying a user-centred design methodology, we gained a deeper understanding of the sustainability value for travel agents, analyzed the failure of sustainability communications on online platforms, explored why agents exclude sustainability information during sales, and investigated opportunities for co-creating value.
TOURISM MANAGEMENT
(2021)
Article
Business
Thomas Schulz, Sina Zimmermann, Markus Boehm, Heiko Gewald, Helmut Krcmar
Summary: In recent years, there has been a shift from goods-dominant to service-dominant business logic, with companies like Daimler AG and the BMW Group providing services in addition to products. Despite the potential for smart mobility, services like the Reach Now app have relatively low user numbers.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Article
Green & Sustainable Science & Technology
Ann Vellesalu, Olga Chkanikova, Daniel Hjelmgren, Nicklas Salomonson
Summary: Research on circular product development has become popular, but it lacks understanding of the co-created and dynamic nature of actors in the system. This study explores institutional re-configuration patterns and their influence on resource integration and value co-creation in circular product development. Through a case study in the healthcare workwear supply chain, the findings highlight the importance of interdependencies and the levels within a service ecosystem for value co-creation.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Business
Ali Hussain, Muhammad Farrukh Abid, Amjad Shamim, Ding Hooi Ting, Md Abu Toha
Summary: This article covers research on customer market construction, co-creative service design, co-creation value, and other fields. The focus of the research includes consumer behavior, services marketing, and customer co-creation experience. The authors explore the importance and development trends of these areas through empirical studies and literature reviews.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2023)
Article
Business
Meina Zhao, Xuqi Wang
Summary: The digital trends in product-service system (PSS) development focus on developing win-win solutions for both companies and customers, particularly when considering human behavior issues. This study solved the PSS implementation that satisfied the demands of both customers and manufacturers through a neuroscience methodology, emphasizing the importance of service experience and a personalized understanding of PSS value perception.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2021)
Article
Green & Sustainable Science & Technology
Jingjing Li, Yongjian Li, Hua Song, Chunxing Fan
Summary: This study aims to clarify the process of sustainable value creation in product design from the capability perspective, proposing a new sustainable value-creation system composed of three capabilities: value chain operations, internal integration, and external integration. The research complements capability-oriented operations strategies and provides a holistic perspective to companies willing to integrate sustainability in product design. It suggests organizations periodically reassess the system to create sustainable value.
JOURNAL OF CLEANER PRODUCTION
(2021)
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
Shufei Li, Pai Zheng, Shibao Pang, Xi Vincent Wang, Lihui Wang
Summary: This paper proposes a temporal subgraph reasoning-based method for self-organising task planning in multiple human-robot collaboration (HRC). The method utilizes a tri-layer Knowledge Graph (KG) to depict task-agent-operation relations and a subgraph mechanism to learn node embeddings from the KG. A temporal reasoning module is employed to integrate previous records and update the KG for forecasting future operations. Experimental results demonstrate that the proposed method outperforms other benchmarks in a car engine assembly task.
JOURNAL OF MANUFACTURING SYSTEMS
(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)