An assistant professor from West Virginia University has received a best review award from the International Journal of Automation Technology.
Thorsten Wuest, J. Wayne and Kathy Richards Faculty Fellow and assistant professor in the Department of industrial and management systems engineering, teamed with Klaus-Dieter Thoben and Stefan Wiesner from the University of Bremen in Germany, to create “Industrie 4.0 and Smart Manufacturing – A Review of Research Issues ad Application Examples.” The review, which was selected from 15 reviews published between 2016 and 2018, received the Best Review 2018 Award from the IJAT Editorial Committee.
The introduction of the Internet of Things and servitization concepts into manufacturing companies has led to a fourth industrial revolution in global manufacturing that features vertically and horizontally integrated production systems. This new paradigm strives to enable smart factories to fulfill dynamic customer demands with high variability in small lot sizes while integrating human ingenuity and automation.
To support this transition and enhance global competitiveness, policy makers in several countries have established research and technology transfer schemes. The review provides an overview of Germany’s Industrie 4.0 program and the smart manufacturing initiative in the U.S.
“The German notion of Industry 4.0 is a little broader and encompasses what is in the U.S. commonly split into advanced manufacturing and smart manufacturing. Advanced manufacturing covers new manufacturing processes and technologies,” said Wuest. “These include 3D printing and nano-manufacturing. Smart manufacturing on the other hand, aims at the integration of information technology and operational technology with data-focused applications, such as cognitive automation, machine learning and artificial intelligence. What both initiatives have in common is that they strive to bring together research institutions, industry, and innovative start-ups.”
The review also analyzes the application potential of cyber-physical systems from product design through production and logistics up to maintenance and exploitation and identifies current and future research issues.
“Given the novelty of the topic, there are many open questions and research gaps. Overall, we can cluster them in three main categories: technological, methodological and business model-related issues,” Wuest said. “Technological issues that demand our attention include common standards facilitating interoperability, potent and easy-to-use data analytics, cybersecurity, sensors, IoT and data quality. Methodological issues include the need for accepted reference models, human-centric and stakeholder-specific visualization of complex insights, marketplaces for applications for smart manufacturing platforms, as well as support to improve requirements engineering. Business model issues that we need to address include privacy issues that emerge with collecting and analyzing more data, investment barriers, developing sustainable service focused business models.
“This highlights again, that Industry 4.0 and smart manufacturing bridges departmental borders,” Wuest concluded, “and requires a truly interdisciplinary approach when we plan to address these issues sustainably and effectively.”