Aerospace Transformation through Industry 4.0 Technologies

[1]  N. B. Anuar,et al.  The rise of "big data" on cloud computing: Review and open research issues , 2015, Inf. Syst..

[2]  Mauro de Mesquita Spinola,et al.  Towards I4.0: A comprehensive analysis of evolution from I3.0 , 2020, Comput. Ind. Eng..

[3]  Dimitris Mourtzis,et al.  Simulation in Manufacturing: Review and Challenges , 2014 .

[4]  Isabel Praça,et al.  A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future , 2020, Applied Sciences.

[5]  M. Echsel,et al.  Production and planned in-orbit qualification of a function-integrated, additive manufactured satellite sandwich structure with embedded automotive electronics , 2020, CEAS Space Journal.

[6]  Yi Wang,et al.  Enabling Technologies and Platforms to Aid Digitalization of Commercial Aviation Support, Maintenance and Health Management , 2019, 2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE).

[7]  Virgilio Cruz-Machado,et al.  Scanning the Industry 4.0: A Literature Review on Technologies for Manufacturing Systems , 2019, Engineering Science and Technology, an International Journal.

[8]  Xavier Maldague,et al.  Parameter Optimization of Robotize Line Scan Thermography for CFRP Composite Inspection , 2018 .

[9]  Tao Jiang,et al.  Pervasive intelligent endogenous 6G wireless systems: Prospects, theories and key technologies , 2020, Digit. Commun. Networks.

[10]  Ivan E. Sutherland,et al.  A head-mounted three dimensional display , 1968, AFIPS Fall Joint Computing Conference.

[11]  Azad M. Madni,et al.  Leveraging Digital Twin Technology in Model-Based Systems Engineering , 2019, Syst..

[12]  Zubair A. Baig,et al.  Machine learning and data analytics for the IoT , 2020, Neural Computing and Applications.

[13]  F. Izzo Management Transition to Big Data Analytics: Exploratory Study on Airline Industry , 2019, International Business Research.

[14]  Hakki Ozgur Unver,et al.  Review of tool condition monitoring in machining and opportunities for deep learning , 2020, The International Journal of Advanced Manufacturing Technology.

[15]  Diego Comin,et al.  An Exploration of Technology Diffusion , 2006 .

[16]  Don Tapscott,et al.  Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World , 2016 .

[17]  Hassan Charaf,et al.  SensorHUB: An IoT Driver Framework for Supporting Sensor Networks and Data Analysis , 2015, Int. J. Distributed Sens. Networks.

[18]  Levente Tamas,et al.  Augmented reality integration into MES for connected workers , 2021, Robotics Comput. Integr. Manuf..

[19]  Paolo Bellavista,et al.  Big Spatial Data Management for the Internet of Things: A Survey , 2020, Journal of Network and Systems Management.

[20]  Andreas M. Kaplan,et al.  Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence , 2019, Business Horizons.

[21]  G. Nassimbeni,et al.  Behind the definition of Industry 4.0: Analysis and open questions , 2020 .

[22]  Ercan Öztemel,et al.  Literature review of Industry 4.0 and related technologies , 2018, J. Intell. Manuf..

[23]  Guenter W. Hein,et al.  Status, perspectives and trends of satellite navigation , 2020, Satellite Navigation.

[24]  Yiqing Zhou,et al.  Service-aware 6G: An intelligent and open network based on the convergence of communication, computing and caching , 2020, Digit. Commun. Networks.

[25]  Ian K. Jennions,et al.  The application of reasoning to aerospace Integrated Vehicle Health Management (IVHM): Challenges and opportunities , 2019, Progress in Aerospace Sciences.

[26]  Andres Tovar,et al.  Review of additive manufacturing technologies and applications in the aerospace industry , 2019, Additive Manufacturing for the Aerospace Industry.

[27]  Abdulrahman Al-Ahmari,et al.  Virtual Assembly of an Airplane Turbine Engine , 2015 .

[28]  Ian Gibson,et al.  Additive manufacturing technologies : 3D printing, rapid prototyping, and direct digital manufacturing , 2015 .

[29]  Andrew Y. C. Nee,et al.  Enabling technologies and tools for digital twin , 2019 .

[30]  Yuqian Lu,et al.  IoT-enabled smart appliances under industry 4.0: A case study , 2020, Adv. Eng. Informatics.

[31]  Yang Lu,et al.  6G: A survey on technologies, scenarios, challenges, and the related issues , 2020, J. Ind. Inf. Integr..

[32]  Phillip Tretten,et al.  Collaborating AI and human experts in the maintenance domain , 2020, AI & SOCIETY.

[33]  Jie Zhang,et al.  The modelling and operations for the digital twin in the context of manufacturing , 2018, Enterp. Inf. Syst..

[34]  Arnaud De Bruyn,et al.  Artificial Intelligence and Marketing: Pitfalls and Opportunities , 2020, Journal of Interactive Marketing.

[35]  Dimitris Mourtzis,et al.  A cloud-based cyber-physical system for adaptive shop-floor scheduling and condition-based maintenance , 2018 .

[36]  Neville A. Stanton,et al.  Seeing through the mist: an evaluation of an iteratively designed head-up display, using a simulated degraded visual environment, to facilitate rotary-wing pilot situation awareness and workload , 2019, Cognition, Technology & Work.

[37]  Christine Chevallereau,et al.  Historical Perspective of Humanoid Robot Research in Europe , 2017, Humanoid Robotics: A Reference.

[38]  Uwe Klingauf,et al.  Modeling of aircraft fuel consumption using machine learning algorithms , 2019, CEAS Aeronautical Journal.

[39]  Lars Larsen,et al.  Autonomous Manufacturing of Composite Parts by a Multi-Robot System , 2017 .

[40]  Mohammad Abdullah Al Faruque,et al.  Manufacturing Supply Chain and Product Lifecycle Security in the Era of Industry 4.0 , 2018, J. Hardw. Syst. Secur..

[41]  Hanan Elazhary,et al.  Internet of Things (IoT), mobile cloud, cloudlet, mobile IoT, IoT cloud, fog, mobile edge, and edge emerging computing paradigms: Disambiguation and research directions , 2019, J. Netw. Comput. Appl..

[42]  Laura Porcu,et al.  Cloud manufacturing as a sustainable process manufacturing route , 2018 .

[43]  Alasdair Gilchrist Introduction to the Industrial Internet , 2016 .

[44]  G. D. Goh,et al.  A review on machine learning in 3D printing: applications, potential, and challenges , 2020, Artificial Intelligence Review.

[45]  N. Tunzelmann Historical coevolution of governance and technology in the industrial revolutions , 2003 .

[46]  Kaj Helin,et al.  User Experience of Augmented Reality System for Astronaut's Manual Work Support , 2018, Front. Robot. AI.

[47]  Shafii Muhammad Abdulhamid,et al.  Deep learning architectures in emerging cloud computing architectures: Recent development, challenges and next research trend , 2020, Appl. Soft Comput..

[48]  Jun Ni,et al.  A review of 4D printing , 2017 .

[49]  Hichem Snoussi,et al.  Digital twin improved via visual question answering for vision-language interactive mode in human–machine collaboration , 2020 .

[50]  Pai Zheng,et al.  A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives , 2019, Journal of Intelligent Manufacturing.

[51]  Toufik Al Khawli,et al.  Introducing data analytics to the robotic drilling process , 2018, Ind. Robot.

[52]  Dohoon Kim A 2020 perspective on "A dynamic model for the evolution of the next generation Internet - Implications for network policies": Towards a balanced perspective on the Internet's role in the 5G and Industry 4.0 era , 2020, Electron. Commer. Res. Appl..

[53]  Xuelong Li,et al.  The Next Breakthroughs of Artificial Intelligence: The Interdisciplinary Nature of AI , 2020 .

[54]  Tao Zhan,et al.  Augmented Reality and Virtual Reality Displays: Perspectives and Challenges , 2020, iScience.

[55]  P. Milgram,et al.  A Taxonomy of Mixed Reality Visual Displays , 1994 .

[56]  Tomi Wijaya,et al.  An AWS Machine Learning-Based Indirect Monitoring Method for Deburring in Aerospace Industries Towards Industry 4.0 , 2018, Applied Sciences.

[57]  Linkan Bian,et al.  Deep Learning for Distortion Prediction in Laser-Based Additive Manufacturing using Big Data , 2019, Manufacturing Letters.

[58]  Marco Macchi,et al.  MES-integrated digital twin frameworks , 2020 .

[59]  Liz Nickels,et al.  AM and aerospace: an ideal combination , 2015 .

[60]  B. Colosimo,et al.  Process defects and in situ monitoring methods in metal powder bed fusion: a review , 2017 .

[61]  Ray Y. Zhong,et al.  Big Data for supply chain management in the service and manufacturing sectors: Challenges, opportunities, and future perspectives , 2016, Comput. Ind. Eng..

[62]  Robert Rządca,et al.  Industry 4.0: coherent definition framework with technological and organizational interdependencies , 2019 .

[63]  F. Froes Combining additive manufacturing with conventional casting and reduced density materials to greatly reduce the weight of airplane components such as passenger seat frames , 2019, Additive Manufacturing for the Aerospace Industry.

[64]  Alessandro Ceruti,et al.  Maintenance in aeronautics in an Industry 4.0 context: The role of Augmented Reality and Additive Manufacturing , 2019, J. Comput. Des. Eng..

[65]  Marc Sartor,et al.  Creation of helicopter dynamic systems digital twin using multibody simulations , 2019, CIRP Annals.

[66]  Xun Xu,et al.  From cloud computing to cloud manufacturing , 2012 .

[67]  Zheng Xiang,et al.  From digitization to the age of acceleration: On information technology and tourism , 2017 .

[68]  Markus Bambach,et al.  New Hybrid Manufacturing Routes Combining Forging and Additive Manufacturing to Efficiently Produce High Performance Components from Ti-6Al-4V , 2020 .

[69]  Frank Kirchner,et al.  INVERITAS: A facility for hardware-in-the-loop long distance movement simulation for rendezvous and capture of satellites and other autonomous objects , 2015 .

[70]  Nelson Luis Saldanha da Fonseca,et al.  The Internet of Things, Fog and Cloud Continuum: Integration and Challenges , 2018, Internet Things.

[71]  Ramjee Prasad,et al.  Impact of 5G Technologies on Industry 4.0 , 2018, Wireless Personal Communications.

[72]  Dóra Horváth,et al.  Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities? , 2019, Technological Forecasting and Social Change.

[73]  Sami Kara,et al.  Manufacturing big data ecosystem: A systematic literature review , 2020, Robotics Comput. Integr. Manuf..

[74]  Christian Eitzinger,et al.  Using Business Analytics for Decision Support in Zero Defect Manufacturing of Composite Parts in the Aerospace Industry , 2019, IFAC-PapersOnLine.

[75]  Martin Hilbert,et al.  Info Capacity| How to Measure the World’s Technological Capacity to Communicate, Store and Compute Information? Part I: Results and Scope , 2012 .

[76]  Atefeh Mashatan,et al.  Touching holograms with windows mixed reality: Renovating the consumer retailing services , 2020 .

[77]  Seung Ki Moon,et al.  Additive manufacturing for space: status and promises , 2019, The International Journal of Advanced Manufacturing Technology.

[78]  George Okeyo,et al.  A survey on privacy and security of Internet of Things , 2020, Comput. Sci. Rev..

[79]  Min Liao,et al.  Airframe digital twin technology adaptability assessment and technology demonstration , 2020 .

[80]  Nandinbaatar Tsog,et al.  Enabling radiation tolerant heterogeneous GPU-based onboard data processing in space , 2020, CEAS Space Journal.

[81]  Niki Werkheiser,et al.  3D Printing in Zero G Technology Demonstration Mission: complete experimental results and summary of related material modeling efforts , 2018, The International journal, advanced manufacturing technology.

[82]  George-Christopher Vosniakos,et al.  Prototyping proactive and adaptive techniques for human-robot collaboration in manufacturing using virtual reality , 2018 .

[83]  Aaron D. Ames,et al.  Valkyrie: NASA's First Bipedal Humanoid Robot , 2015, J. Field Robotics.

[84]  Ruben Nicolas-Sans,et al.  The digital transformation of business. Towards the datafication of the relationship with customers , 2021 .

[85]  Venkat N. Gudivada,et al.  Cognitive Computing: Concepts, Architectures, Systems, and Applications , 2016 .

[86]  Václav Snásel,et al.  Big Data Pre-processing Techniques Within the Wireless Sensors Networks , 2015, AECIA.

[87]  F. Mas,et al.  Using augmented reality in AIRBUS A400M shop floor assembly work instructions , 2012 .

[88]  Yuling Hsu,et al.  Revolution on digital twin technology—a patent research approach , 2020 .

[89]  Chen Shen,et al.  Towards an automated robotic arc-welding-based additive manufacturing system from CAD to finished part , 2016, Comput. Aided Des..

[90]  Hwa Jen Yap,et al.  Haptic-based virtual reality system to enhance actual aerospace composite panel drilling training , 2019 .

[91]  Michael Huth,et al.  Mapping the values of IoT , 2018, J. Inf. Technol..

[92]  Pai Zheng,et al.  Smart additive manufacturing: Current artificial intelligence-enabled methods and future perspectives , 2020, Science China Technological Sciences.

[93]  Tong Gao,et al.  An aerospace bracket designed by thermo-elastic topology optimization and manufactured by additive manufacturing , 2020 .

[94]  M. Ghobakhloo,et al.  Industry 4.0, digitization, and opportunities for sustainability , 2020 .

[95]  Tibor S. Balint,et al.  Humanly space objects—Perception and connection with the observer , 2015 .

[96]  Tiago M. Fernández-Caramés,et al.  A Review on Internet of Things for Defense and Public Safety , 2016, Sensors.

[97]  Flávia Cristina Martins Queiroz Mariano,et al.  A survey of industrial augmented reality , 2020, Comput. Ind. Eng..

[98]  Lei Wang,et al.  Big data challenges: Prioritizing by decision-making process using Analytic Network Process technique , 2019, Multimedia Tools and Applications.

[99]  Alexandre Dolgui,et al.  Operations management issues in design and control of hybrid human-robot collaborative manufacturing systems: a survey , 2020, Annu. Rev. Control..

[100]  Chuan Lv,et al.  Applications of virtual reality in maintenance during the industrial product lifecycle: A systematic review , 2020 .

[101]  Jinsong Bao,et al.  Digital twin modeling method based on biomimicry for machining aerospace components , 2020 .

[102]  Daniel F. García,et al.  Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review , 2016, Sensors.

[103]  Aitzol Lamikiz,et al.  Latest Developments in Industrial Hybrid Machine Tools that Combine Additive and Subtractive Operations , 2018, Materials.

[104]  Xuqian Zhang,et al.  Application framework of digital twin-driven product smart manufacturing system: A case study of aeroengine blade manufacturing , 2019, International Journal of Advanced Robotic Systems.

[105]  M. Pantzar,et al.  The data economy: How technological change has altered the role of the citizen-consumer , 2019, Technology in Society.

[106]  Nicholas Negroponte,et al.  Being Digital , 1995 .

[107]  Petri T. Helo,et al.  Cloud manufacturing ecosystem analysis and design , 2021, Robotics Comput. Integr. Manuf..

[108]  Johnny S. Wong,et al.  Cloud and IoT-based emerging services systems , 2018, Cluster Computing.

[109]  Federico Vicentini,et al.  Systemic Approach for the Definition of a Safer Human-Robot Interaction , 2019 .

[110]  Fridolin Wild,et al.  Augmented Reality for the enhancement of space product assurance and safety , 2020 .

[111]  Ayman I. Kayssi,et al.  IoT survey: An SDN and fog computing perspective , 2018, Comput. Networks.

[112]  Renato Vidoni,et al.  Emerging research fields in safety and ergonomics in industrial collaborative robotics: A systematic literature review , 2021, Robotics Comput. Integr. Manuf..

[113]  Marcello Colledani,et al.  Zero Defect Manufacturing Strategies for Reduction of Scrap and Inspection Effort in Multi-stage Production Systems , 2018 .

[114]  Paolo Gaudenzi,et al.  Selective Laser Melting of a 1U CubeSat structure. Design for Additive Manufacturing and assembly , 2019, Acta Astronautica.

[115]  E. C. Crofton,et al.  Potential applications for virtual and augmented reality technologies in sensory science , 2019, Innovative Food Science & Emerging Technologies.

[116]  S. Lathabai Additive Manufacturing of Aluminium-Based Alloys and Composites , 2018 .

[117]  Zhizhou Zhang,et al.  Developments in 4D-printing: a review on current smart materials, technologies, and applications , 2019, International Journal of Smart and Nano Materials.

[118]  Javier Guerrero,et al.  Topology optimization and additive manufacturing for aerospace components , 2018, Progress in Additive Manufacturing.

[119]  Les A. Piegl,et al.  Ten challenges in 3D printing , 2015, Engineering with Computers.

[120]  Louise Wright,et al.  How to tell the difference between a model and a digital twin , 2020, Advanced Modeling and Simulation in Engineering Sciences.

[121]  Markus Wilde,et al.  Historical survey of kinematic and dynamic spacecraft simulators for laboratory experimentation of on-orbit proximity maneuvers , 2019, Progress in Aerospace Sciences.

[122]  Fadi Al-Turjman,et al.  A smart lightweight privacy preservation scheme for IoT-based UAV communication systems , 2020, Comput. Commun..

[123]  Alasdair Gilchrist Industry 4.0: The Industrial Internet of Things , 2016 .

[124]  Qi Gao,et al.  Digital assembly technology based on augmented reality and digital twins: a review , 2019, Virtual Real. Intell. Hardw..

[125]  Xifan Yao,et al.  Design and management of digital manufacturing and assembly systems in the Industry 4.0 era , 2019, The International Journal of Advanced Manufacturing Technology.

[126]  Eleonora Bottani,et al.  Digital Twin Reference Model Development to Prevent Operators’ Risk in Process Plants , 2020 .

[127]  Andrew Y. C. Nee,et al.  Digital Twin and Services , 2019 .

[128]  Krishna Rawat,et al.  4D printing of materials for the future: Opportunities and challenges , 2020, Applied Materials Today.

[129]  Angela Lin,et al.  Cloud computing as an innovation: Percepetion, attitude, and adoption , 2012, Int. J. Inf. Manag..

[130]  Nir Kshetri,et al.  1 Blockchain's roles in meeting key supply chain management objectives , 2018, Int. J. Inf. Manag..

[131]  Bernadett Koles,et al.  Virtual reality and its impact on B2B marketing: A value-in-use perspective , 2019, Journal of Business Research.

[132]  Tao Xie,et al.  4D Printing: History and Recent Progress , 2018, Chinese Journal of Polymer Science.

[133]  Carlos Becker Westphall,et al.  Cloud resource management: A survey on forecasting and profiling models , 2015, J. Netw. Comput. Appl..

[134]  Konstantinos I. Diamantaras,et al.  Enhancing the functionality of augmented reality using deep learning, semantic web and knowledge graphs: A review , 2020, Vis. Informatics.

[135]  Fabienne Salimi,et al.  Modeling and Simulation: The Essential Tools to Manage the Complexities , 2017 .

[136]  Gabor Sziebig,et al.  Trends in Smart Manufacturing: Role of Humans and Industrial Robots in Smart Factories , 2020, Current Robotics Reports.

[137]  Rajit Gadh,et al.  Virtual and Augmented Reality Technologies for Product Realization , 1999 .

[138]  Yun Zhang,et al.  Missile-Target Situation Assessment Model Based on Reinforcement Learning , 2020 .

[139]  Sung Ho Choi,et al.  Deep learning-based mobile augmented reality for task assistance using 3D spatial mapping and snapshot-based RGB-D data , 2020, Comput. Ind. Eng..

[140]  J. Paulo Davim,et al.  Enabling Technologies for the Successful Deployment of Industry 4.0 , 2020 .

[141]  S. Behdad,et al.  Blockchain for the future of sustainable supply chain management in Industry 4.0 , 2020 .

[142]  Gilbert Tang,et al.  Human–Robot Shared Workspace in Aerospace Factories , 2019 .

[143]  Mihai Nadin,et al.  Machine intelligence: a chimera , 2018, AI & SOCIETY.

[144]  Philip Webb,et al.  Identifying the key organisational human factors for introducing human-robot collaboration in industry: an exploratory study , 2015 .

[145]  Ishwar Singh,et al.  From Industry 4.0 to Robotics 4.0 - A Conceptual Framework for Collaborative and Intelligent Robotic Systems , 2020 .

[146]  Kazuo Mizuta Human and Robots Interaction , 2014 .

[147]  Zakwan Skaf,et al.  Understanding the role of a Digital Twin in Integrated Vehicle Health Management (IVHM)* , 2019, 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC).

[148]  Andreas Buchheim,et al.  Investigation of an automated dry fiber preforming process for an aircraft fuselage demonstrator using collaborating robots , 2016 .

[149]  Jason Yon,et al.  Characterising the Digital Twin: A systematic literature review , 2020, CIRP Journal of Manufacturing Science and Technology.

[150]  Barbara Bigliardi,et al.  Industry 4.0: Emerging themes and future research avenues using a text mining approach , 2019, Comput. Ind..

[151]  Mark Blackburn,et al.  Is Digital Thread/Digital Twin Affordable? A Systemic Assessment of the Cost of DoDs Latest Manhattan Project , 2017 .

[152]  J. S. Butler,et al.  Austin, Boston, Silicon Valley, and New York: Case studies in the location choices of entrepreneurs in maintaining the Technopolis , 2019, Technological Forecasting and Social Change.

[153]  Robert Bogue,et al.  The growing use of robots by the aerospace industry , 2018, Ind. Robot.

[154]  Jinguo Liu,et al.  Robust real-time hand detection and localization for space human-robot interaction based on deep learning , 2020, Neurocomputing.

[155]  Martin Hilbert,et al.  The World’s Technological Capacity to Store, Communicate, and Compute Information , 2011, Science.