Key Takeaways & Executive Findings
- •• This bibliometric review systematically maps the intelligent manufacturing (IM) landscape, identifying frontier hotspots, key technologies, and applications across the full product lifecycle. • Core enabling technologies—including IoT, AI, digital twins, and VR/AR—are critically examined for their roles in enhancing productivity, quality, and sustainability in manufacturing. • The study highlights the shift toward sustainable and green manufacturing, emphasizing the integration of intelligent systems to reduce resource waste and environmental impact. • Future research directions underscore the need for interdisciplinary collaboration, technological integration, computing power upgrades, and robust security and privacy measures in IM.
Abstract
Intelligent manufacturing (IM), a driving force behind the fourth industrial revolution, is reshaping the manufacturing sector by enhancing productivity, efficiency, and sustainability. Despite the rapid technological advancements in IM, comprehensive bibliometric reviews remain limited. This article systematically reviews the latest research in IM, addressing emerging hotspots, key technologies, and their applications across the entire product manufacturing cycle. Bibliometric analysis is employed to identify research trends visualize publication volume, collaboration patterns, research domains, co-citations, and emerging areas of interest. The article then examines key technologies supporting IM, including sensors, the Internet of Things (IoT), big data analytics, cloud computing, artificial intelligence (AI), digital twins, and virtual reality (VR)/augmented reality (AR). Furthermore, it explores the application of these technologies throughout the manufacturing cycle—from intelligent reliability design, material transportation and tracking, to intelligent planning and scheduling, machining and fabrication, monitoring and maintenance, quality inspection and control, warehousing and management, and sustainable green manufacturing—through specific case studies. Lastly, the article discusses future research directions, highlighting the increasing global market and the need for enhanced interdisciplinary collaboration, technological integration, computing power upgrades, and attention to security and privacy in IM. This study provides valuable insights for scholars and serves as a guide for future research and strategic investment decisions, offering a comprehensive view of the IM field.
1. Introduction
As the backbone of the global economy, the manufacturing industry plays a crucial role in economic growth [1]. From the first industrial revolution, marked by improvements in the steam engine, to the second characterized by electrification, the third by the advent of computer technology, and the fourth—defined by unprecedented technological advancements and integration—the industry has entered the era of Intelligent manufacturing (IM), also known as Industry 4.0 [2, 3]. Today, the manufacturing sector faces two core challenges: achieving IM and embracing green innovation.
In recent years, governments worldwide have enacted policies to promote high-end, intelligent, and sustainable development in manufacturing [4]. Amid global resource shortages and environmental pressures, IM integrates advanced technologies to enhance productivity, reduce resource waste, and drive eco-friendly innovations, offering a transformative path toward sustainable development. The sector is shifting from traditional methods to digital, networked, and intelligent processes [5], improving production efficiency [6, 7], product quality [8, 9], and reducing operational costs [10] and resource consumption, while promoting green production [11]. IM utilizes information-driven technology, combining advanced manufacturing techniques with communication technologies.
Loading authentic research manuscript (Pages 1–5)...
Xiaohan Sun, Lan Dong, Zongyi Liu, Aiguo Qin, Jixin Liu, Zongming Zhou, Xu Yan, Guang Wang, Bo Liu, Zhigang Zhou, Xiangguo Chen, Yuewen Feng, Bo Zhang, Danyang Liu, Changhe Li (2025). Intelligent Manufacturing of a Bibliometric Review: From Frontier Hotspots to Key Technologies and Applications. Chinese Journal of Mechanical Engineering. https://doi.org/10.1186/s10033-025-01274-y
Research & Educational Purpose Only:The translations, structured abstracts, analytical annotations, and data reports provided by SinoTechIntel are intended exclusively for academic research, internal corporate R&D, and educational benchmarking. They do not constitute formal engineering, chemical safety, legal, or professional advice.
Copyright & Intellectual Property Notice: Original copyright of the underlying source articles and experimental data remains with the respective authors, institutions, and original publishing journals. SinoTechIntel claims intellectual property only over its proprietary translations, analytical syntheses, and AEO structured enhancements in accordance with international fair use and academic citation principles.
Frequently Asked Questions
What is the main focus of this bibliometric review on intelligent manufacturing?
The review systematically maps the intelligent manufacturing (IM) landscape, identifying frontier hotspots, key technologies, and applications across the entire product manufacturing cycle, using bibliometric analysis to reveal research trends and collaboration patterns.
Which key technologies are examined in the article?
The article examines sensors, the Internet of Things (IoT), big data analytics, cloud computing, artificial intelligence (AI), digital twins, and virtual reality (VR)/augmented reality (AR) as key enabling technologies for intelligent manufacturing.
How does intelligent manufacturing contribute to sustainability?
Intelligent manufacturing enhances productivity and efficiency while reducing resource waste and environmental impact, promoting green production and sustainable development across the manufacturing cycle.
What are the future research directions highlighted in the review?
Future research directions include enhancing interdisciplinary collaboration, technological integration, computing power upgrades, and addressing security and privacy concerns in intelligent manufacturing.
Who is the corresponding author and what is their affiliation?
The corresponding author is Changhe Li, affiliated with the Key Lab of Industrial Fluid Energy Conservation and Pollution Control, Ministry of Education, Qingdao University of Technology, Qingdao 266520, China.
Related Technical Papers & Translations
Direct Repair of the Crystal Structure and Coating Surface of Spent LiFePO4 Materials Enables Superfast Li-Ion Migration
The rapid accumulation of spent LiFePO4 (LFP) cathodes from retired lithium-ion batteries necessitates the development of effective and environmental-friendly recycling strategies. In this context, direct regeneration has emerged as a promising approach for reclaiming LFP cathode materials, offering a streamlined pathway to restore their electrochemical functionality. We report an integrated regeneration protocol that simultaneously repairs the degraded crystal structure and reconstructs the damaged carbon coating in spent LFP. The regenerated cathode material had superfast lithium-ion diffusion kinetics and a stable cathode–electrolyte interface, giving a remarkable rate capability with specific capacities of 122 mAh g−1 at 5C and 106 mAh g−1 at 10C (1C = 170 mA g−1). It also maintained capacities of 110.7 mAh g−1 (5C) and 84.1 mAh g−1 (10C) after 400 cycles. It could be used in harsh environments and could be stably cycled at subzero temperatures (−10 and −20 °C) and in solid-state electrolyte batteries. Life cycle assessment combined with economic evaluation using the EverBatt model reveals that this direct regeneration approach has high economic and environmental benefits.
Oxide Semiconductor for Advanced Memory Architectures: Atomic Layer Deposition, Key Requirement and Challenges
Oxide semiconductors (OSs), introduced by the Hosono group in the early 2000s, have evolved from display backplane materials to promising candidates for advanced memory and logic devices. The exceptionally low leakage current of OSs and compatibility with three-dimensional (3D) architectures have recently sparked renewed interest in their use in semiconductor applications. This review begins by exploring the unique material properties of OSs, which fundamentally originate from their distinct electronic band structure. Subsequently, we focus on atomic layer deposition (ALD), a core technique for growing excellent OS films, covering both basic and advanced processes compatible with 3D scaling. The basic surface reaction mechanisms—adsorption and reaction—and their roles in film growth are introduced. Furthermore, material design strategies, such as cation selection, crystallinity control, anion doping, and heterostructure engineering, are discussed. We also highlight challenges in memory applications, including contact resistance, hydrogen instability, and lack of p-type materials, and discuss the feasibility of ALD-grown OSs as potential solutions. Lastly, we provide an outlook on the role of ALD-grown OSs in memory technologies. This review bridges material fundamentals and device-level requirements, offering a comprehensive perspective on the potential of ALD-driven OSs for next-generation semiconductor memory devices.
Laser powder bed fusion of biodegradable Zn-4Cu alloy: Processing, microstructure and properties
Zn's natural degradability and biocompatibility make it a promising candidate for implants, however, its mechanical properties remain insufficient for bone applications. In this study, the performance of Zn was enhanced by developing Zn-Cu alloys via laser powder bed fusion (LPBF). Optimal LPBF parameters for forming stable tracks were achieved by adjusting laser power and scanning speed. Under optimized conditions of 100 W and 100 mm/s, high-density (99.58%) Zn-Cu alloys with improved hardness (68.2HV) and yield strength (160 MPa) were achieved. These improvements are attributed to solid solution strengthening, segregation strengthening, and grain refinement. The Zn-Cu alloys also demonstrated favorable degradation behavior, with a rate of 0.16 mm/year. This degradation is primarily driven by micro-galvanic corrosion between the CuZn5 phase and Zn matrix, along with refined grains and increased grain boundary density. This work demonstrates a viable strategy for fabricating Zn-based implants with enhanced structural integrity and mechanical performance via LPBF.