Announcements

Name: Prof. Dr. Dimitris Mourtzis
Email: [email protected]
Article Title: “Real-Time Remote Maintenance Support Based on Augmented Reality (AR)”

Prof. Dr. Dimitris Mourtzis is a Professor at the Department of Mechanical Engineering and Aeronautics at the University of Patras. At this institute, he also serves as Vice President of the Research and Development Council of the University of Patras and Governing Board Member for the Clean Aviation Joint Undertaking, representing European Academia. He is also the Director of the Laboratory for Manufacturing Systems and Automation (LMS). Additionally, he is the coordinator of the Internal Evaluation Team for the evaluation of the Department of Mechanical Engineering and Aeronautics. At the University of Patras, he has served as Vice Chairman of the Department of Mechanical Engineering and Aeronautics from 2017 to 2020 and the Director of the Design and Manufacturing Division from 2015 to 2017. He has remarkable teaching experience, having taught for many years eight undergraduate and four postgraduate courses at the Department of Mechanical Engineering and Aeronautics at the University of Patras in the field of Manufacturing Systems Programming and Control Methods. He has been the coordinator of the innovative educational activity for engineers, Teaching Factories—“New training methods of the Engineer”, in close collaboration with the industry. At an international level, he is the Faculty Liaison representing the University of Patras in the iPodia program. His scientific interests focus on the simulation, design, planning and control of manufacturing systems and networks, robotic systems, automation, augmented, mixed, and virtual reality in manufacturing, manufacturing processes modeling and machine tool maintenance. Furthermore, his research interests are also focused on the design, development and implementation of solutions based on technologies such as the cloud, internet of things (IoT), the digital twin, 5G cellular networks, and artificial intelligence as well as on the development of product–service systems (PSS). He is also actively involved in the digital transformation of manufacturing companies and implementation of Industry 4.0 as well as of the upcoming Industry 5.0 and Society 5.0 practices, both on a national and international level.

He is a Fellow of the International Academy for Production Research (CIRP), International Federation of Automatic Control (IFAC 5.2), and International Federation of Information Processing (IFIP WG 5.7); Member of the Scientific Committee of the International Association of Learning Factories (IALF), European Factories of the Future Association (EFFRA), American Society of Mechanical Engineers (ASME), Society of Manufacturing Engineers (SME), and European Manufacturing and Innovation Research Association (EMIRACLE); and Founding Member of the European Aeronautics Science Network/Association (EASN).

He is also the author and editor of the book Design and Operation of Production Networks for Mass Personalization in the Era of Cloud Technology, published by Elsevier in 2022. He also participates as a member of the editorial board of nine international scientific journals and has participated as a guest editor in four international scientific journals with a high impact factor.

He has published around three hundred scientific papers, of which one hundred were in highly regarded international scientific journals and one hundred and fifty at international scientific conferences in addition to thirty-five chapters in books, ten editorials, and four white papers. His research work has been acknowledged by the scientific community with more than 10,300 citations (h-index 52) according to the Google Scholar, Scopus, and ResearchGate databases.

We want to congratulate Prof. Dr. Dimitris Mourtzis for winning the Applied Sciences 2020 Best Paper Award in “Mechanical Engineering”.

The following is an interview with Prof. Dr. Dimitris Mourtzis:

1. Could you please briefly introduce the main research content of the winning paper?

Cloud computing has enabled the provision of high-quality services, especially in the field of maintenance. However, since modern machines are becoming more complex, maintenance has to be carried out by experienced and well-trained personnel, while overseas support is timely and financially costly. Furthermore, augmented reality (AR) is a backbone technology facilitating the development of robust maintenance support tools. However, its applications are limited to the provision of predefined scenarios. Thus, the main research content of the winning paper is research work that aims to design and develop a framework for the support of remote maintenance and repair operation based on AR by creating suitable communication channels between the shop-floor technicians and the expert engineers who are utilizing real-time feedback from the operator’s field of view. Finally, the applicability and validation of the proposed tool are tested in a lab-based machine shop and a real-life industrial case study.

2. Could you describe the difficulties and breakthrough innovations encountered in this research?

Τhe most important challenge that the research and development community has to overcome is the creation of highly intuitive AR applications and tools. Even though there are several publications covering the AR-based aspect of maintenance, the majority of publications have focused on the remote assistance of technical operation. However, in the majority of publications, the use of frame markers is inevitable, which can highly affect the overall performance of the tool and, by extension, the performance of the shop-floor/field technician. Therefore, according to our literature search, a more robust and compact framework to enhance the technician’s mobility when working on the machine is needed. This research work is one of the first publications that provide real-time support based on AR technology.

3. What are the current cutting-edge research areas in this field?

The majority of maintenance tasks are now being completed in one of four ways: shipment to a repair facility, hiring a skilled specialist, hiring a novice technician, or a combination of these. The method, involving the use of a skilled specialist, would undoubtedly result in faster and higher-quality maintenance than that provided by a novice technician. However, there may not be a specialist available, resulting in longer downtime for equipment and higher travel costs. Additionally, if the maintenance problem is not properly reported before the specialist arrives, additional transportation may be required to allow the specialist to diagnose the problem and obtain the necessary tools and replacement parts. Next, another method used for maintenance would be to utilize a novice technician, aided by an operations manual or additional instructional material such as videos. While personnel would be readily available, support material takes a long time to produce and quickly becomes obsolete as the equipment is modified. Finally, allowing an off-site skilled specialist to guide an on-site novice technician through maintenance tasks using an audiovisual call is another option for performing maintenance. Therefore, it may be difficult to effectively communicate tasks when both the specialist and the novice technician are unfamiliar with the same terminology because of the high reliance on technical vocabulary. As a result, finding more efficient ways to train and guide technicians is critical to the continued maintenance of globally distributed equipment.

Taking into consideration that, under the framework of Industry 4.0, the complexity of machines and systems has greatly increased, suitably trained personnel are required for maintenance repair and operations (MRO). Moreover, during the current Industrial Revolution, the research community has expended great efforts in the design, development, and implementation of big dataset analytics toward predictive maintenance (PdM). PdM approaches can facilitate the improvement of production and manufacturing networks by providing good estimates for future events (e.g., machine breakdowns). However, there is a lack within the field of decision-making and human support.

Above all, engineering is a wide and highly technological field that focuses on the satisfaction of market demands (human demands). Therefore, it is imperative that humans remain at the center of attention. Many countries are already moving toward more human-centric, resilient, and sustainable initiatives in what is known as Industry 5.0 and Society 5.0. Similar to the pillar technologies of Industry 4.0, Industry 5.0 and Society 5.0 will focus on the development of new analytics methods also known as prescriptive analytics. Prescriptive analytics can be realized as the next generation of predictive analytics. Their main differentiation lies in the provision of decision-making support (for prescriptive analytics), which will facilitate humans into foreseeing future events and act proactively and, by extension, improve the seamless and continuous operation of manufacturing and production networks. Furthermore, digital technologies, such as extended reality (which encapsulates augmented reality, virtual reality, and mixed reality) will be key drivers for delivering more intuitive human experiences and improved data interpretation and visualization.

4. As one of the winners of the Applied Sciences Best Paper Award, what do you think researchers find appealing about this award?

Beyond the publication of their manuscripts, the Best Paper Award is the ultimate recognition of the research work accomplished by scientists. It is important for authors to receive recognition for their research activities as well as to know that the community has benefited from their research work. Furthermore, the Best Paper Award is one of the most important points for building a strong academic and professional profile. Finally, such awards drive young researchers to strive even harder to produce and publish top-quality research works.

5. How do you think open access impacts authors?

Scientific research shows that publishing in open access results in more citations and impact because of the global visibility without barriers. Businesses can also gain access to the most up-to-date scientific ideas, which they can then build on. Increased visibility is one of the most widely praised benefits of open access publishing; since there is no barrier to accessing articles, more people can find and read them. To that end, this research work has been cited 43 times so far, based on Google Scholar.

About the other authors of “Real-Time Remote Maintenance Support Based on Augmented Reality (AR)”:

John Angelopoulos
John Angelopoulos holds an integrated master’s in Mechanical Engineering and Aeronautics from the University of Patras. He is currently a Ph.D. candidate and Research Associate with the Laboratory of Manufacturing Systems and Automation (LMS) at the Department of Mechanical Engineering and Aeronautics, University of Patras. His research activities are related to extended reality (XR), maintenance techniques, artificial intelligence (AI), and manufacturing systems in Industry 4.0. He has published 45 research works, including 2 book chapters, 10 publications in scientific journals, 32 publications at international scientific conferences, and 1 white paper. His research work has been acknowledged by the scientific community with more than 300 citations corresponding to an h-index of 10 according to Google Scholar.

Vasileios Siatras
Vasilis Siatras is an undergraduate integrated master’s degree student at the Department of Mechanical Engineering and Aeronautics at the University of Patras. His research interests are focused on artificial intelligence (AI), optimization, and extended reality (XR) technologies. He is also a Research Associate at the Laboratory for Manufacturing Systems and Automation (LMS) working on European-funded projects in close collaboration with key innovation drivers and SMEs in Europe. He has also published thirteen research papers in international journals and conferences. His research work has been acknowledged by the scientific community with 120 citations corresponding to an h-index of 5 according to Google Scholar.