Mixed Reality Improves Education and Training in Assembly Processes

Mixed reality is the outcome of blending the physical world with the digital world, made possible by technological advancement. Mixed reality is the next evolution in human, computer, and environment interaction. Augmented reality (AR) uses a virtual model of the real world, augmented by using a computer to see the real environment through a special display device. Current education and training systems in the engineering maintenance field are still insufficiently directed at the psychomotor skills in learning about machine parts, which makes them less effective for trainees. The oil and gas industry always face problems related to inefficiency due to downtime of critical equipment. This study was conducted at designing and developing a virtual reality (VR) and augmented reality (AR) system as a learning and training platform. This work also reviewed AR applications for machine part maintenance and assembly. An AR system was modelled and developed using the following software: CATIA, Blender, Unity and Vuforia. The effectiveness of using the AR technique in an education and training process was evaluated with 20 respondents among university students. The results showed that using this AR app enhanced the participant's understanding according to certain criteria and can be adopted as a learning method

The Development of an Advanced Maintenance training programme utilizing Augmented Reality

Maintenance engineering represents an area of great opportunity to reduce cost, improve productivity, and increase profitability for manufacturing companies. There are examples of best practice that can be classed as World Class Maintenance which deliver great benefits. Unfortunately very few companies, and especially small and medium sized companies, remotely approach this level. Research has shown that savings of around 10% are achievable by improving asset management techniques through adopting modern maintenance practices, tools, and techniques. One area that is often overlooked is the development of an appropriate training programme in which the skills and knowledge are retained and used to develop the skills of young apprentices or new staff using specific technologies. Augmented Reality (AR) has been identified as a technology offering a promising approach to training which combines a number of disciplines including engineering, computing, and psychology. Augmented Reality (AR) enables users to view, through the use of see-through displays, virtual objects superimposed dynamically, and merged seamlessly, with real world objects in a real environment via a range of devices such as Ipad or Tablet, so that the virtual objects and real world images appear to exist at the same time in the same place providing real-time interaction. Therefore, this approach expands the surrounding real world environment by superimposing computer-generated information. It presents the information more intuitively than legacy interfaces such as paper-based instruction manuals enabling the users to interact directly with the information and use their natural spatial processing ability. This paper will identify augmented reality tools and techniques with the potential to support efficient training systems for maintenance and assembly skills that accelerate the technicians’ acquisition of new maintenance procedures. A platform for multimodal Augmented Reality based training will be proposed which could allow small to medium sized companies to develop and implement appropriate maintenance tasks based upon cost effective and efficient training systems. Such systems would give technicians’ the opportunity for practical training, that is, the possibility to “learn by doing” in the workplace; provide information when and where needed, thus reducing the technicians’ information search time; and potentially reduce errors due to violations in procedure, misinterpretation of facts, or insufficient training. A detailed bibliography on these topics is also provided

Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

A systematic review of augmented reality applications in maintenance

Augmented Reality (AR) technologies for supporting maintenance operations have been an academic research topic for around 50 years now. In the last decade, major progresses have been made and the AR technology is getting closer to being implemented in industry. In this paper, the advantages and disadvantages of AR have been explored and quantified in terms of Key Performance Indicators (KPI) for industrial maintenance. Unfortunately, some technical issues still prevent AR from being suitable for industrial applications. This paper aims to show, through the results of a systematic literature review, the current state of the art of AR in maintenance and the most relevant technical limitations. The analysis included filtering from a large number of publications to 30 primary studies published between 1997 and 2017. The results indicate a high fragmentation among hardware, software and AR solutions which lead to a high complexity for selecting and developing AR systems. The results of the study show the areas where AR technology still lacks maturity. Future research directions are also proposed encompassing hardware, tracking and user-AR interaction in industrial maintenance is proposed

Comparative study of AR versus video tutorials for minor maintenance operations

[EN] Augmented Reality (AR) has become a mainstream technology in the development of solutions for repair and maintenance operations. Although most of the AR solutions are still limited to specific contexts in industry, some consumer electronics companies have started to offer pre-packaged AR solutions as alternative to video-based tutorials (VT) for minor maintenance operations. In this paper, we present a comparative study of the acquired knowledge and user perception achieved with AR and VT solutions in some maintenance tasks of IT equipment. The results indicate that both systems help users to acquire knowledge in various aspects of equipment maintenance. Although no statistically significant differences were found between AR and VT solutions, users scored higher on the AR version in all cases. Moreover, the users explicitly preferred the AR version when evaluating three different usability and satisfaction criteria. For the AR version, a strong and significant correlation was found between the satisfaction and the achieved knowledge. Since the AR solution achieved similar learning results with higher usability scores than the video-based tutorials, these results suggest that AR solutions are the most effective approach to substitute the typical paper-based instructions in consumer electronics.This work has been supported by Spanish MINECO and EU ERDF programs under grant RTI2018-098156-B-C55.Morillo, P.; García García, I.; Orduña, JM.; Fernández, M.; Juan, M. (2020). Comparative study of AR versus video tutorials for minor maintenance operations. Multimedia Tools and Applications. 79(11-12):7073-7100. https://doi.org/10.1007/s11042-019-08437-9S707371007911-12Ahn J, Williamson J, Gartrell M, Han R, Lv Q, Mishra S (2015) Supporting healthy grocery shopping via mobile augmented reality. ACM Trans Multimedia Comput Commun Appl 12(1s):16:1–16:24. https://doi.org/10.1145/2808207Anderson TW (2011) Anderson–darling tests of goodness-of-fit. Springer, Berlin, pp 52–54. https://doi.org/10.1007/978-3-642-04898-2_118Awad N, Lewandowski SE, Decker EW (2015) Event management system for facilitating user interactions at a venue. US Patent App. 14/829,382Azuma R (1997) A survey of augmented reality. Presence: Teleoperators and Virtual Environments 6(4):355–385Baird K, Barfield W (1999) Evaluating the effectiveness of augmented reality displays for a manual assembly task. Virtual Reality 4:250–259Ballo P (2018) Hardware and software for ar/vr development. In: Augmented and virtual reality in libraries, pp 45–55. LITA guidesBarrile V, Fotia A, Bilotta G (2018) Geomatics and augmented reality experiments for the cultural heritage. Applied Geomatics. https://doi.org/10.1007/s12518-018-0231-5Billinghurst M, Duenser A (2012) Augmented reality in the classroom. Computer 45(7):56–63. https://doi.org/10.1109/MC.2012.111Bowman DA, McMahan RP (2007) Virtual reality: how much immersion is enough? Computer 40(7)Brown TA (2015) Confirmatory factor analysis for applied research. Guilford PublicationsDodge Y. (ed) (2008) Kruskal-Wallis test. Springer, New York. https://doi.org/10.1007/978-0-387-32833-1_216Elmunsyah H, Hidayat WN, Asfani K (2019) Interactive learning media innovation: utilization of augmented reality and pop-up book to improve user’s learning autonomy. J Phys Conf Ser 1193(012):031. https://doi.org/10.1088/1742-6596/1193/1/012031Entertainment L (2017) Dolphin Player. https://play.google.com/store/apps/details?id=com.broov.player. Online; Accessed 09-September-2017Fletcher J, Belanich J, Moses F, Fehr A, Moss J (2017) Effectiveness of augmented reality & augmented virtuality. In: MODSIM Modeling & simulation of systems and applications) world conferenceFraga-Lamas P, Fernández-Caramés TM, Blanco-Novoa O, Vilar-Montesinos MA (2018) A review on industrial augmented reality systems for the industry 4.0 shipyard. IEEE Access 6:13,358–13,375. https://doi.org/10.1109/ACCESS.2018.2808326Furió D, Juan MC, Seguí I, Vivó R (2015) Mobile learning vs. traditional classroom lessons: a comparative study. J Comput Assist Learn 31(3):189–201. https://doi.org/10.1111/jcal.12071Gavish N, Gutiérrez T, Webel S, Rodríguez J, Peveri M, Bockholt U, Tecchia F (2015) Evaluating virtual reality and augmented reality training for industrial maintenance and assembly tasks. Interact Learn Environ 23(6):778–798. https://doi.org/10.1080/10494820.2013.815221Gimeno J, Morillo P, Orduña JM, Fernández M (2013) A new ar authoring tool using depth maps for industrial procedures. Comput Ind 64(9):1263–1271. https://doi.org/10.1016/j.compind.2013.06.012Holzinger A, Kickmeier-Rust MD, Albert D (2008) Dynamic media in computer science education; content complexity and learning performance: is less more? Educational Technology & Society 11(1):279–290Hornbaek K (2013) Some whys and hows of experiments in human–computer interaction. Foundations and TrendsⓇ in Human–Computer Interaction 5(4):299–373. https://doi.org/10.1561/1100000043Huang J, Liu S, Xing J, Mei T, Yan S (2014) Circle & search: Attribute-aware shoe retrieval. ACM Trans Multimedia Comput Commun Appl 11 (1):3:1–3:21. https://doi.org/10.1145/2632165Jiang S, Wu Y, Fu Y (2018) Deep bidirectional cross-triplet embedding for online clothing shopping. ACM Trans Multimedia Comput Commun Appl 14(1):5:1–5:22. https://doi.org/10.1145/3152114Kim SK, Kang SJ, Choi YJ, Choi MH, Hong M (2017) Augmented-reality survey: from concept to application. KSII Transactions on Internet and Information Systems 11:982–1004. https://doi.org/10.3837/tiis.2017.02.019Langlotz T, Zingerle M, Grasset R, Kaufmann H, Reitmayr G (2012) Ar record&replay: Situated compositing of video content in mobile augmented reality. In: Proceedings of the 24th Australian Computer-Human Interaction Conference, OzCHI ’12. ACM, New York, pp 318–326, DOI https://doi.org/10.1145/2414536.2414588, (to appear in print)Martin-SanJose JF, Juan MC, Mollá R, Vivó R (2017) Advanced displays and natural user interfaces to support learning. Interact Learn Environ 25(1):17–34. https://doi.org/10.1080/10494820.2015.1090455Massey FJ (1951) The kolmogorov-Smirnov test for goodness of fit. J Am Stat Assoc 46(253):68–78van der Meij H, van der Meij J, Voerman T, Duipmans E (2018) Supporting motivation, task performance and retention in video tutorials for software training. Educ Technol Res Dev 66(3):597–614. https://doi.org/10.1007/s11423-017-9560-zvan der Meij J, van der Meij H (2015) A test of the design of a video tutorial for software training. J Comput Assist Learn 31 (2):116–132. https://doi.org/10.1111/jcal.12082Mestre LS (2012) Student preference for tutorial design: a usability study. Ref Serv Rev 40(2):258–276. https://doi.org/10.1108/00907321211228318Mohr P, Kerbl B, Donoser M, Schmalstieg D, Kalkofen D (2015) Retargeting technical documentation to augmented reality. In: Proceedings of the 33rd annual ACM conference on human factors in computing systems, CHI ’15. ACM, New York, pp 3337–3346, DOI https://doi.org/10.1145/2702123.2702490, (to appear in print)Mohr P, Mandl D, Tatzgern M, Veas E, Schmalstieg D, Kalkofen D (2017) Retargeting video tutorials showing tools with surface contact to augmented reality. In: Proceedings of the 2017 CHI conference on human factors in computing systems, CHI ’17. ACM, New York, pp 6547–6558, DOI https://doi.org/10.1145/3025453.3025688, (to appear in print)Montgomery DC, Runger GC (2003) Applied statistics and probability for engineers. Wiley, New YorkMorillo P, Orduña JM, Casas S, Fernández M (2019) A comparison study of ar applications versus pseudo-holographic systems as virtual exhibitors for luxury watch retail stores. Multimedia Systems. https://doi.org/10.1007/s00530-019-00606-yMorse JM (2000) Determining sample size. Qual Health Res 10(1):3–5. https://doi.org/10.1177/104973200129118183Muñoz-Montoya F, Juan M, Mendez-Lopez M, Fidalgo C (2019) Augmented reality based on slam to assess spatial short-term memory. IEEE Access 7:2453–2466. https://doi.org/10.1109/ACCESS.2018.2886627Neuhäuser M (2011) Wilcoxon–Mann–Whitney test. Springer, Berlin, pp 1656–1658Neumann U, Majoros A (1998) Cognitive, performance, and systems issues for augmented reality applications in manufacturing and maintenance. In: Inproceedings of the IEEE virtual reality annual international symposium (VR ’98), pp 4–11no JJA, Juan MC, Gil-Gómez JA, Mollá R. (2014) A comparative study using an autostereoscopic display with augmented and virtual reality. Behaviour & Information Technology 33(6):646–655. https://doi.org/10.1080/0144929X.2013.815277Palmarini R, Erkoyuncu JA, Roy R, Torabmostaedi H (2018) A systematic review of augmented reality applications in maintenance. Robot Comput Integr Manuf 49:215–228Quint F, Loch F (2015) Using smart glasses to document maintenance processes. Mensch und Computer 2015–WorkshopbandRadkowski R, Herrema J, Oliver J (2015) Augmented reality-based manual assembly support with visual features for different degrees of difficulty. International Journal of Human–Computer Interaction 31(5):337–349. https://doi.org/10.1080/10447318.2014.994194Regenbrecht H, Schubert T (2002) Measuring presence in augmented reality environments: design and a first test of a questionnaire, Porto, PortugalRobertson J (2012) Likert-type scales, statistical methods, and effect sizes. Commun ACM 55(5):6–7. https://doi.org/10.1145/2160718.2160721Rodríguez-Andrés D, Juan MC, Méndez-López M, Pérez-Hernández E, Lluch J (2016) Mnemocity task: Assessment of childrens spatial memory using stereoscopy and virtual environments. PLos ONE 1(8). https://doi.org/10.1371/journal.pone.0161858Sanna A, Manuri F, Lamberti F, Paravati G, Pezzolla P (2015) Using handheld devices to support augmented reality-based maintenance and assembly tasks. In: 2015 IEEE International conference on consumer electronics (ICCE), pp. 178–179. https://doi.org/10.1109/ICCE.2015.7066370Schmidt S, Ehrenbrink P, Weiss B, Voigt-Antons J, Kojic T, Johnston A, Moller S (2018) Impact of virtual environments on motivation and engagement during exergames. In: 2018 Tenth international conference on quality of multimedia experience (qoMEX), pp 1–6. https://doi.org/10.1109/QoMEX.2018.8463389Shapiro SS, Wilk MB (1965) An analysis of variance test for normality (complete samples). Biometrika 52(3/4):591–611Tang A, Owen C, Biocca F, Mou W (2003) Comparative effectiveness of augmented reality in object assembly. In: Proceedings of the SIGCHI conference on human factors in computing systems, CHI ’03. ACM, New York, pp 73–80, DOI https://doi.org/10.1145/642611.642626, (to appear in print)Tomás JM, Oliver A, Galiana L, Sancho P, Lila M (2013) Explaining method effects associated with negatively worded items in trait and state global and domain-specific self-esteem scales. Structural Equation Modeling: A Multidisciplinary Journal 20(2):299–313. https://doi.org/10.1080/10705511.2013.769394Uva AE, Gattullo M, Manghisi VM, Spagnulo D, Cascella GL, Fiorentino M (2017) Evaluating the effectiveness of spatial augmented reality in smart manufacturing: a solution for manual working stations. The Int J Adv Manuf Technol: 1–13Wang X, Ong SK, Nee AYC (2016) A comprehensive survey of augmented reality assembly research. Advances in Manufacturing 4(1):1–22. https://doi.org/10.1007/s40436-015-0131-4Westerfield G, Mitrovic A, Billinghurst M (2015) Intelligent augmented reality training for motherboard assembly. Int J Artif Intell Educ 25(1):157–172. https://doi.org/10.1007/s40593-014-0032-xWiedenmaier S, Oehme O, Schmidt L, Luczak H (2003) Augmented reality (ar) for assembly processes - design and experimental evaluation. International Journal of Human-Computer Interaction 16(3):497–514Witmer BG, Singer MJ (1998) Measuring presence in virtual environments: a presence questionnaire. Presence: Teleoperators and Virtual Environments 7(3):225–240Wu HK, Lee SWY, Chang HY, Liang JC (2013) Current status, opportunities and challenges of augmented reality in education. Computers & Education 62:41–49. https://doi.org/10.1016/j.compedu.2012.10.024Yim MYC, Chu SC, Sauer PL (2017) Is augmented reality technology an effective tool for e-commerce? an interactivity and vividness perspective. Journal of Interactive Marketing 39(http://www.sciencedirect.com/science/article/pii/S1094996817300336):89–103. https://doi.org/10.1016/j.intmar.2017.04.001Yuan ML, Ong SK, Nee AYC (2008) Augmented reality for assembly guidance using a virtual interactive tool. Int J Prod Res 46(7):1745–1767. https://doi.org/10.1080/0020754060097293

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

A Scoping Review on Virtual Reality-Based Industrial Training

The fourth industrial revolution has forced most companies to technologically evolve, applying new digital tools, so that their workers can have the necessary skills to face changing work environments. This article presents a scoping review of the literature on virtual reality-based training systems. The methodology consisted of four steps, which pose research questions, document search, paper selection, and data extraction. From a total of 350 peer-reviewed database articles, such as SpringerLink, IEEEXplore, MDPI, Scopus, and ACM, 44 were eventually chosen, mostly using the virtual reality haptic glasses and controls from Oculus Rift and HTC VIVE. It was concluded that, among the advantages of using this digital tool in the industry, is the commitment, speed, measurability, preservation of the integrity of the workers, customization, and cost reduction. Even though several research gaps were found, virtual reality is presented as a present and future alternative for the efficient training of human resources in the industrial field.This work was supported by Instituto Superior Tecnológico Victoria Vásconez Cuvi. The authors appreciate the opportunity to analyze topics related to this paper. The authors must also recognize the supported bringing by Universidad Tecnica de Ambato (UTA) and their Research and Development Department (DIDE) under project CONIN-P-256-2019, and SENESCYT by grants “Convocatoria Abierta 2011” and “Convocatoria Abierta 2013”

Remote Real-Time Collaboration Platform enabled by the Capture, Digitisation and Transfer of Human-Workpiece Interactions

In this highly globalised manufacturing ecosystem, product design and verification activities, production and inspection processes, and technical support services are spread across global supply chains and customer networks. Therefore, a platform for global teams to collaborate with each other in real-time to perform complex tasks is highly desirable. This work investigates the design and development of a remote real-time collaboration platform by using human motion capture technology powered by infrared light based depth imaging sensors borrowed from the gaming industry. The unique functionality of the proposed platform is the sharing of physical contexts during a collaboration session by not only exchanging human actions but also the effects of those actions on the task environment. This enables teams to remotely work on a common task problem at the same time and also get immediate feedback from each other which is vital for collaborative design, inspection and verifications tasks in the factories of the future