skip to main content


Title: Trends in intelligent manufacturing research: a keyword co-occurrence network based review
In recent years, driven by Industry 4.0 wave, academic research has focused on the science, engineering, and enabling technologies for intelligent and cyber manufacturing. Using a network science and data mining-based Keyword Co-occurrence Network (KCN) methodology, this work analyzes the trends in data science topics in the manufacturing literature over the past two decades to inform the researchers, educators, industry leaders of knowledge trends in intelligent manufacturing. It studies the evolution of research topics and methods in data science, Internet of Things (IoT), cloud computing, and cyber manufacturing. The KCN methodology is applied to systematically analyze the keywords collected from 84,041 papers published in top-tier manufacturing journals between 2000 and 2020. It is not practically feasible to review this large body of literature through tradition manual approaches like systematic review and scoping review to discover insights. The results of network modeling and data analysis reveal important knowledge components and structure of the intelligent and cyber manufacturing literature, implicit the research interests switch and provide the insights for industry development. This paper maps the high frequency keywords in the recent literature to nine pillars of Industry 4.0 to help manufacturing community identify research and education directions for emerging technologies in intelligent manufacturing.  more » « less
Award ID(s):
1935646
NSF-PAR ID:
10315342
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Journal of intelligent manufacturing
Volume:
33
ISSN:
1572-8145
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. In recent years, driven by Industry 4.0 wave, academic research has focused on the science, engineering, and enabling technologies for intelligent and cyber manufacturing. Using a network science and data mining-based Keyword Co-occurrence Network (KCN) methodology, this work analyzes the trends in data science topics in the manufacturing literature over the past two decades to inform the researchers, educators, industry leaders of knowledge trends in intelligent manufacturing. It studies the evolution of research topics and methods in data science, Internet of Things (IoT), cloud computing, and cyber manufacturing. The KCN methodology is applied to systematically analyze the keywords collected from 84,041 papers published in top-tier manufacturing journals between 2000 and 2020. It is not practically feasible to review this large body of literature through tradition manual approaches like systematic review and scoping review to discover insights. The results of network modeling and data analysis reveal important knowledge components and structure of the intelligent and cyber manufacturing literature, implicit the research interests switch and provide the insights for industry development. This paper maps the high frequency keywords in the recent literature to nine pillars of Industry 4.0 to help manufacturing community identify research and education directions for emerging technologies in intelligent manufacturing. 
    more » « less
  2. null (Ed.)
    Abstract Digital manufacturing technologies have quickly become ubiquitous in the manufacturing industry. The transformation commonly referred to as the fourth industrial revolution, or Industry 4.0, has ushered in a wide range of communication technologies, connection mechanisms, and data analysis capabilities. These technologies provide powerful tools to create more lean, profitable, and data-driven manufacturing processes. This paper reviews modern communication technologies and connection architectures for Digital Manufacturing and Industry 4.0 applications. An introduction to cyber-physical systems and a review of digital manufacturing trends is followed by an overview of data acquisition methods for manufacturing processes. Numerous communication protocols are presented and discussed for connecting disparate machines and processes. Flexible data architectures are discussed, and examples of machine monitoring implementations are provided. Finally, select implementations of these communication protocols and architectures are surveyed with recommendations for future architecture implementations. 
    more » « less
  3. The objective of this paper is to outline the details of a recently-funded National Science Foundation (NSF) Advanced Technological Education (ATE) project that aims to educate and enable the current and future manufacturing workforce to operate in an Industry 4.0 environment. Additionally, the startup procedures involved, the major ongoing activities during year-one, and preliminary impressions and lessons learned will be elaborated as well. Industry 4.0 refers to the ongoing reformation of advanced manufacturing (Operation Technologies - OT) enabled by advances in automation/data (Information Technologies - IT). Cyber-enabled smart manufacturing is a multidisciplinary approach that integrates the manufacturing process, its monitoring/control, data science, cyber-physical systems, and cloud computing to drive manufacturing operations. This is further propelled by the dissolution of boundaries separating IT and OT, presenting optimization opportunities not just at a machine-level, but at the plant/enterprise-levels. This so-called fourth industrial revolution is rapidly percolating the discrete and continuous manufacturing industry. It is therefore critical for the current and future US workforce to be cognizant and capable of such interdisciplinary domain knowledge and skills. To meet this workforce need, this project will develop curricula, personnel and communities in cyber-enabled smart manufacturing. The key project components will include: (i) Curriculum Road-Mapping and Implementation – one that integrates IT and OT to broaden the educational experience and employability via road-mapping workshops, and then to develop/implement curricula, (ii) Interdisciplinary Learning Experiences – through collaborative special-projects courses, industry internships and research experiences, (iii) Pathways to Industry 4.0 Careers – to streamline career pathways to enter Industry 4.0 careers, and to pursue further education, and (iv) Faculty Development – continuous improvement via professional development workshops and faculty development leaves. It is expected that this project will help define and chart-out the capabilities demanded from the next-generation workforce to fulfill the call of Industry 4.0, and the curricular ingredients necessary to train and empower them. This will help create an empowered workforce well-suited for Industry 4.0 careers in cyber-enabled smart manufacturing. The collaborative research team’s experience so far in starting up and establishing the project has further shed light on some of the essentials and practicalities needed for achieving the grand vision of enabling the manufacturing workforce for the future. Altogether, the experience and lessons learned during the year-one implementation has provided a better perception of what is needed for imparting a broader impact through this project. 
    more » « less
  4. The objective of this paper is to outline the details of a recently-funded National Science Foundation (NSF) Advanced Technological Education (ATE) project that aims to educate and enable the current and future manufacturing workforce to operate in an Industry 4.0 environment. Additionally, the startup procedures involved, the major ongoing activities during year-one, and preliminary impressions and lessons learned will be elaborated as well. Industry 4.0 refers to the ongoing reformation of advanced manufacturing (Operation Technologies - OT) enabled by advances in automation/data (Information Technologies - IT). Cyber-enabled smart manufacturing is a multidisciplinary approach that integrates the manufacturing process, its monitoring/control, data science, cyber-physical systems, and cloud computing to drive manufacturing operations. This is further propelled by the dissolution of boundaries separating IT and OT, presenting optimization opportunities not just at a machine-level, but at the plant/enterprise-levels. This so-called fourth industrial revolution is rapidly percolating the discrete and continuous manufacturing industry. It is therefore critical for the current and future US workforce to be cognizant and capable of such interdisciplinary domain knowledge and skills. To meet this workforce need, this project will develop curricula, personnel and communities in cyber-enabled smart manufacturing. The key project components will include: (i) Curriculum Road-Mapping and Implementation – one that integrates IT and OT to broaden the educational experience and employability via road-mapping workshops, and then to develop/implement curricula, (ii) Interdisciplinary Learning Experiences – through collaborative special-projects courses, industry internships and research experiences, (iii) Pathways to Industry 4.0 Careers – to streamline career pathways to enter Industry 4.0 careers, and to pursue further education, and (iv) Faculty Development – continuous improvement via professional development workshops and faculty development leaves. It is expected that this project will help define and chart-out the capabilities demanded from the next-generation workforce to fulfill the call of Industry 4.0, and the curricular ingredients necessary to train and empower them. This will help create an empowered workforce well-suited for Industry 4.0 careers in cyber-enabled smart manufacturing. The collaborative research team’s experience so far in starting up and establishing the project has further shed light on some of the essentials and practicalities needed for achieving the grand vision of enabling the manufacturing workforce for the future. Altogether, the experience and lessons learned during the year-one implementation has provided a better perception of what is needed for imparting a broader impact through this project. 
    more » « less
  5. null (Ed.)
    With the continuous development of technologies, our society is approaching the next stage of industrialization. The Fourth Industrial Revolution also referred to as Industry 4.0, redefines the manufacturing system as a smart and connected machinery system with fully autonomous operation capability. Several advanced cutting-edge technologies, such as cyber-physical systems (CPS), the internet of things (IoT), and artificial intelligence, are believed to the essential components to realize Industry 4.0. In this paper, we focus on a comprehensive review of how artificial intelligence benefits Industry 4.0, including potential challenges and possible solutions. A panoramic introduction of neuromorphic computing is provided, which is one of the most promising and attractive research directions in artificial intelligence. Subsequently, we introduce the vista of the neuromorphic-powered Industry 4.0 system and survey a few research activities on applications of artificial neural networks for IoT. 
    more » « less