Topic Editors

School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China
Prof. Dr. Jihong Liu
School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China
School of Engineering, Cardiff University, Cardiff CF24 3AA, UK
School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China

Smart Product Design and Manufacturing on Industrial Internet

Abstract submission deadline
30 September 2025
Manuscript submission deadline
31 December 2025
Viewed by
1709

Topic Information

Dear Colleagues,

In recent years, artificial intelligence and big data technologies, powered with Industrial Internet and web environment, have had huge impacts on research and development activities concerning product design and manufacturing fields. It is obvious that Industrial-Internet-based paradigms, systems, key enabling technologies, models, and algorithms for smart product design and manufacturing are playing an important role in making Industry 4.0/5.0 a reality. Topics associated with keywords like smart product design, smart manufacturing, product maintenance and services, robots and actuators, big data and intelligent algorithms, etc., in the context of Industrial Internet and web environment, often constitute the focus of both academic and industrial sectors. It is necessary to collect key contributions from the above fields, sum up the current progress on both academic research and industrial practices and present them to the public.

On the basis of the reasons mentioned above, this Special Topic Collection aims to explore a wide range of issues related to the product design and manufacturing with artificial intelligence and big data on Industrial Internet and web environment. Potential authors can feel free to involve any group journal as the host of their manuscripts. We welcome original research articles, reviews, short communication, and technical notes. Research areas include (but are not limited to) the following topics:

Smart Product Design:

  • Fundamentals, such as Industrial-Internet-based paradigms, architectures, and systems; computational geometry and graphics issues in product design; datasets and deep learning for 3D shapes and product semantics, representation learning for 3D shapes and product semantics, and intelligent generative and retrieval models for product design including text2shape, voice2shape, sketch2shape, image2shape, and graph2shape; topology optimization, finite element analysis and optimization, bond graphs, and Modelica for dynamic issues in design; etc.
  • Methods and practices, such as key enabling technologies, case study, and industrial scenarios and applications on Industrial Internet and web environment; data-driven and intelligent conceptual design; design for X, intelligent parameterized CAD, product service system design, product mass customization design, product platform and modular design; intelligent computational design, generative design especially for additive manufacturing; crowdsourcing design; Kansei engineering and emotional computing in product design; smart electromechanical system design, materials design; next-generation CAD software models on web; etc.

Smart Manufacturing:

  • Fundamentals, such as Industrial-Internet-based paradigms, architectures, and systems related to service-oriented manufacturing, social manufacturing, cloud manufacturing, networked collaborative manufacturing, digital manufacturing, mass customization, on-demand manufacturing, and shared manufacturing; issues with manufacturing interactions and collaborations; intelligent and interconnected equipment, protocols, and sensor networks; human factors within the context of Industry 4.0/5.0; blockchain technologies; low carbon and social impacts in manufacturing; meta verse and VR/AR in manufacturing; etc.
  • Methods and practices, such as key enabling technologies, case study, and industrial scenarios and applications on Industrial Internet and web environment; intelligent factory and production lines; intelligent assembly; smart equipment modeling and control; smart process technologies and experience representations; IOT and sensing/measuring networks, devices on web and manufacturing data sampling, CPS/CPSS, and digital twins; production planning and scheduling; APS/MES/DCS; intelligent process monitoring and quality control; materials processing and logistics, intelligent inventory; manufacturing performance analysis and optimization; sustainable production supply chain; new CAPP/CAM/APS/MES/DCS software models on the Internet or web; etc.

Smart Product Maintenance and Services:

  • Fundamentals, such as Industrial-Internet-based paradigms, architectures, and systems related to maintenance service principles, MRO lifecycle, and product service systems; maintenance service flow modeling and scheduling; quality of services evaluation; etc.
  • Methods and practices, such as key enabling technologies, case study, and industrial scenarios and applications on Industrial Internet and web environment; IoT and sensing networks, product CPS/CPSS, and digital twins; smart remote monitoring and performance prediction of product usages; product fault diagnosis and executive reliability, product predictive maintenance, and MRO modeling; smart configuration and running for product service systems, service workflow control and management, etc.

Smart Robots and Actuators:

  • Fundamentals, such as Industrial-Internet-based paradigms, architectures, and systems related to robot-driven manufacturing and maintenance, robotic actuators; actuators in smart manufacturing and control systems; robot and actuator thinking; human–robot/actuator interactions; etc.
  • Methods and practices, such as key enabling technologies, case study, and industrial scenarios and applications on Industrial Internet and web environment; robots and actuators on web; smart robot grasping, cognitive robots for manufacturing and maintenance, and robot path planning and scheduling; smart control for robots and actuators; etc.

Big Data and Intelligent Algorithms:

  • AI-related datasets, models and algorithms, computing powers for product design, manufacturing, maintenance and services, and robots and actuators, such as feature engineering and prompt engineering with special industrial fields; symbol-based AI including production rules, frames, ontology, knowledge graphs, CBR, and decision-making; computing-driven AI including neural networks, machine learning, deep learning, and causal inference; NLP, large language models (like chatGPT), and multi-modal models; swarm intelligence, multi-agents, and collective intelligence; learning algorithms including federated learning, transfer learning, reinforcement learning, representation learning, and few-shot learning; etc.
  • Big data for product design, manufacturing, maintenance and services, and robots and actuators, such as big data analytics, data flow processing, data cleaning, big data visualization, etc.

Please note that authors can submit their papers to this Special Topic Collection at any time. Papers will be published online immediately after their acceptance and without delays caused by whether all paper collections are ready.

We look forward to hearing from you.

Prof. Dr. Pingyu Jiang
Prof. Dr. Jihong Liu
Prof. Dr. Ying Liu
Prof. Dr. Jihong Yan
Topic Editors

Keywords

  • Industrial Internet
  • web-based applications
  • Industry 4.0/5.0
  • smart product design
  • smart manufacturing
  • product maintenance and services
  • robots and actuators
  • big data and intelligent algorithms

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Actuators
actuators
2.2 3.9 2012 16.5 Days CHF 2400 Submit
Algorithms
algorithms
1.8 4.1 2008 15 Days CHF 1600 Submit
Big Data and Cognitive Computing
BDCC
3.7 7.1 2017 18 Days CHF 1800 Submit
Future Internet
futureinternet
2.8 7.1 2009 13.1 Days CHF 1600 Submit
Journal of Manufacturing and Materials Processing
jmmp
3.3 5.1 2017 14.7 Days CHF 1800 Submit
Machines
machines
2.1 3.0 2013 15.6 Days CHF 2400 Submit
Robotics
robotics
2.9 6.7 2012 17.7 Days CHF 1800 Submit
Systems
systems
2.3 2.8 2013 17.3 Days CHF 2400 Submit

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Published Papers (1 paper)

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25 pages, 619 KiB  
Article
A Study of the Impact of Manufacturing Servitization on Firms’ Cost Stickiness
by Ming Bai, Hao Guan, Ye Hong and Haoyi Sun
Systems 2024, 12(7), 266; https://doi.org/10.3390/systems12070266 - 22 Jul 2024
Viewed by 504
Abstract
Since 2014, China has been actively promoting the transformation of manufacturing servitization, clarifying the importance of manufacturing servitization. This paper investigates the correlation between manufacturing servitization and cost stickiness, supplementing the research on the economic consequences of manufacturing servitization and the influencing factors [...] Read more.
Since 2014, China has been actively promoting the transformation of manufacturing servitization, clarifying the importance of manufacturing servitization. This paper investigates the correlation between manufacturing servitization and cost stickiness, supplementing the research on the economic consequences of manufacturing servitization and the influencing factors of cost stickiness. This paper launches an empirical study with a sample of A-share manufacturing companies from 2014 to 2022. The research results show that, first, manufacturing servitization can inhibit enterprise cost stickiness; second, manufacturing servitization affects enterprise cost stickiness through the path of reducing enterprise adjustment costs, reducing managers’ optimistic expectations and reducing enterprise agency costs; third, the negative relationship between manufacturing servitization and cost stickiness is stronger among firms with a low level of internal control, a strong degree of financing constraints, a good quality internal information environment, a strong degree of competition in the market, and firms that are in capital-intensive manufacturing industries; fourth, the role of embedded servitization on enterprise cost stickiness is not significant, while hybrid servitization can have a significant negative effect on enterprise cost stickiness; and fifth, the impact of manufacturing servitization on enterprise cost stickiness mainly lies in the cost of material resources rather than the cost of human resources. Full article
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