Industry 4.0 – A Glimpse

Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment

Lee, J., Kao, H.-A., & Yang, S. (2014) · Procedia CIRP · doi:10.1016/j.procir.2014.02.001 · Cited by 1,965

Opportunities of Sustainable Manufacturing in Industry 4.0

Stock, T. W., & Seliger, G. (2016) · Procedia CIRP · doi:10.1016/j.procir.2016.01.129 · Cited by 1,947

A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises

Schumacher, A., Erol, S., & Sihn, W. (2016) · Procedia CIRP · doi:10.1016/j.procir.2016.07.040 · Cited by 1,766

Implementing Smart Factory of Industrie 4.0: An Outlook

Wang, S., Wan, J., Li, D., & Zhang, C. (2016) · International Journal of Distributed Sensor Networks · doi:10.1155/2016/3159805 · Cited by 1,527

“Industrie 4.0” and Smart Manufacturing – A Review of Research Issues and Application Examples

Thoben, K., Wiesner, S., Wuest, T., & Industrial and Management Systems Engineering (2017) · International Journal of Automation Technology · doi:10.20965/ijat.2017.p0004 · Cited by 1,148

A Categorical Framework of Manufacturing for Industry 4.0 and Beyond

Qin, J., Liu, Y., & Grosvenor, R. I. (2016) · Procedia CIRP · doi:10.1016/j.procir.2016.08.005 · Cited by 1,043

INDUSTRY 4.0: A REVIEW ON INDUSTRIAL AUTOMATION AND ROBOTIC

Bahrin, M. A. K., Othman, M. F., Azli, N. H. N., & Talib, M. F. (2016) · Jurnal Teknologi · doi:10.11113/jt.v78.9285 · Cited by 680

Tangible Industry 4.0: A Scenario-Based Approach to Learning for the Future of Production

Erol, S., Jäger, A., Hold, P., Ott, K., & Sihn, W. (2016) · Procedia CIRP · doi:10.1016/j.procir.2016.03.162 · Cited by 636

The Industry 4.0 revolution and the future of Manufacturing Execution Systems (MES)

Almada-Lobo, F. (2016) · Journal of Innovation Management · doi:10.24840/2183-0606_003.004_0003 · Cited by 622

Lean Automation enabled by Industry 4.0 Technologies

Kolberg, D., & Zühlke, D. (2015) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2015.06.359 · Cited by 617

Exact solution approaches for order acceptance and scheduling decisions in m-machine open shops

Spindler, S. A., Steinhardt, C., & Klein, R. (2022) · Computers & Industrial Engineering · doi:10.1016/j.cie.2022.108952 · Cited by 9

Transforming Strategic Management Using Agile Methodologies

Kargas, A. D., & Aretos, A. (2023) · Advances in logistics, operations, and management science book series · doi:10.4018/978-1-6684-9261-1.ch018 · Cited by 9

Hybrid Particle Swarm Optimization and Simulated Annealing for Capacitated Vehicle Routing Problem

Mar’i, F., Mahmudy, W. F., & Santoso, P. B. (2019) · International Conference on Sustainable Information Engineering and Technology (SIET) · doi:10.1109/siet48054.2019.8986006 · Cited by 9

Dördüncü Endüstri Devriminin (Endüstri 4.0) Neresindeyiz?

GÖV, S. A., & Erdoğan, D. (2020) · İstanbul Gelişim Üniversitesi Sosyal Bilimler Dergisi · doi:10.17336/igusbd.661236 · Cited by 9

Hydrodynamics and Mixing in a Novel Design of Compact Microreactors: Arc Flow Inverters

Gaddem, M. R., Ookawara, S. A., Nigam, K. D. P., Yoshikawa, S., & Matsumoto, H. (2021) · Chemical Engineering and Processing - Process Intensification · doi:10.1016/j.cep.2021.108770 · Cited by 9

Integration of IR 4.0 Into Six Sigma for Sustainability in Malaysia Manufacturing Industry

Akanmu, M. D., & Nordin, N. B. (2022) · Jurnal Intelek · doi:10.24191/ji.v17i1.15849 · Cited by 9

Factors influencing the creation of an industry 4.0 strategy in the generic pharmaceutical industry

Graham, J. (2024) · Journal of Generic Medicines The Business Journal for the Generic Medicines Sector · doi:10.1177/17411343241238178 · Cited by 8

Development of Russia’s industry: Some regularities and prospects

Сухарев, О. (2024) · Journal of New Economy · doi:10.29141/2658-5081-2024-25-1-1 · Cited by 8

Model-based assembly process planning for flexible aircraft cabin architectures

Ghanjaoui, Y., Satwan, P., Biedermann, J., & Nagel, B. (2024) · CEAS Aeronautical Journal · doi:10.1007/s13272-024-00773-3 · Cited by 8

Recent Innovations in Computer and Automation Engineering for Performance Improvement in the Steel Industry Production Chain: A Review

Pepe, C., Farella, G., Bartucci, G., & Zanoli, S. M. (2025) · Energies · doi:10.3390/en18081981 · Cited by 8

Use of live digital twin (shadow) soft sensor to monitor membrane degradation in continuous manufacturing single pass tangential flow filtration

Taylor, R., Mandur, J. S., Amira, U., Al‐Inati, N., Marin‐Celis, J., Hatch, S., Fernandez‐Cerezo, L., Pinto, N. D. S., Metsi‐Guckel, E., Matos, T., et al. (2025) · Biotechnology Progress · doi:10.1002/btpr.70058 · Cited by 8

Multi-layer thermal history prediction framework for directed energy deposition based on extended physics-informed neural networks (XPINN)

Peng, B., & Panesar, A. S. (2025) · Additive manufacturing · doi:10.1016/j.addma.2025.104953 · Cited by 8

Analyzing the Smart Industry Readiness Index in Adopting Industry 4.0 Technologies

Abdullah, F. M., & Al-Ahmari, A. M. (2025) · Processes · doi:10.3390/pr13103172 · Cited by 8

Towards a formal description and automatic execution of production processes

Vještica, M., Dimitrieski, V., Pisarić, M., Kordić, S., Ristić, S., & Luković, I. (2019) · IEEE International Scientific Conference on Informatics (Informatics) · doi:10.1109/informatics47936.2019.9119314 · Cited by 8

Identifying Challenges Related to Industry 4.0 in Five Manufacturing Companies

Dogea, R., & Stolt, R. (2021) · Procedia Manufacturing · doi:10.1016/j.promfg.2021.10.046 · Cited by 8

Evolution of the biomechanical dimension of the professional gestures of grinders when using a collaborative robot

Schoose, C., Cuny-Guerrier, A., Caroly, S., Claudon, L., Wild, P. P., & Savescu, A. V. (2022) · International Journal of Occupational Safety and Ergonomics · doi:10.1080/10803548.2022.2065063 · Cited by 8

Current Trend of Artificial Intelligence-Augmented Reality in Science Learning: Systematic Literature Review

Kharisma, D. B., Sudirman, S., Edi, F., & Ruth Rize Paas Megahati, S. (2023) · Jurnal Penelitian Pendidikan IPA · doi:10.29303/jppipa.v9i8.4484 · Cited by 8

Remodeling the Traditional Fashion Industry in the Era of Industry 4.0

Guo, H., Rusli, R. D., & Aris, A. B. (2023) · International Journal of Global Optimization and Its Application · doi:10.56225/ijgoia.v2i3.259 · Cited by 8

Orbit Bound. Predictors of ‘readiness to space’ and government support

Paladini, S., & Barbieri, D. (2024) · Space Policy · doi:10.1016/j.spacepol.2024.101628 · Cited by 8

Path-Sampling and Machine Learning for Rare Abnormal Events: Application to Polymerization CSTRs

Sudarshan, V., Seider, W. D., Patel, A. J., Oktem, U. G., & Arbogast, J. E. (2024) · Chemical Engineering Science · doi:10.1016/j.ces.2024.120513 · Cited by 8

Machine learning-assisted interfacial modulation and configuration design of metal matrix composites: A review

Cheng, Y., Shu, R., Sun, H., Zou, M., Jiao, Y., Wu, Z., Liu, Y., & Jiang, X. (2025) · Materials Today Communications · doi:10.1016/j.mtcomm.2025.112504 · Cited by 8

Guidelines for Machine Tool Sensing and Smart Manufacturing Integration

Costa, S., Silva, F. J. G., Campilho, R. D. S. G., & Pereira, T. (2020) · Procedia Manufacturing · doi:10.1016/j.promfg.2020.10.036 · Cited by 8

The Impact of Industry 4.0 Implementation on Organizational Behavior and Corporate Culture: The Case of Pakistan’s Retail Industry

Ali, S., & Xie, Y. (2020) · International Journal of Engineering and Manufacturing · doi:10.5815/ijem.2020.06.03 · Cited by 8

Tool monitoring of end milling based on gap sensor and machine learning

Jaini, S. N. B., Lee, D.-W., Lee, S.-J., Kim, M.-R., & Kwon, Y. (2021) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-020-02875-2 · Cited by 8

Factors affecting the adoption of technologies to improve fleet safety management

Mohamed, Y., & Jokonya, O. (2021) · Procedia Computer Science · doi:10.1016/j.procs.2021.01.278 · Cited by 8

Integration of Technology Initiatives with Educational Neuroscience and its Impact on Technology Readiness to Technology Adoption by HSS Teachers, Kerala

Joseph, G. V., & Thomas, K. A. (2021) · Springer eBooks · doi:10.1007/978-3-030-72400-9_21 · Cited by 8

Smart quality control powered by machine learning algorithms

Bonomi, N., Cardoso, F. M., Confalonieri, M., Daniele, F., Ferrario, A., Foletti, M., Giordano, S., Luceri, L., & Pedrazzoli, P. (2021) · IEEE International Conference on Automation Science and Engineering (CASE) · doi:10.1109/case49439.2021.9551421 · Cited by 8

Triple Disruption dan Percepatan Akselerasi Transformasi Digital di Desa

Yunas, N. S., Hakim, A. I., & Pohan, I. A. (2023) · Matra Pembaruan · doi:10.21787/mp.7.2.2023.87-97 · Cited by 8

Readiness for Implementing Industry 4.0 in Food and Beverage Manufacturer in Indonesia

Ichsan, M., Dachyar, M., & Farizal, F. (2019) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/598/1/012129 · Cited by 8

Modeling and management of human resources in the reconfiguration of production system in industry 4.0 by neural networks

Khalifa, R. B., Tliba, K., Diallo, M., Penas, O., Yahia, N. B., & Choley, J. (2019) · IEEE International Conference on Signal, Control and Communication (SCC) · doi:10.1109/scc47175.2019.9116104 · Cited by 8

Industry 4.0: current trend and future scope for further research in High Performance Manufacturing

Alfalla-Luque, R., Machuca, J. A. D., Amaya, M. R. A., & Ortega-Jimenez, C. H. (2020) · LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI) · doi:10.18687/laccei2020.1.1.303 · Cited by 8

Factors influencing the acceptance and patronage of E-commerce logistics operations in Nigeria

Adeniran, A. O., Akinsehinwa, F. O., & Olorunfemi, S. O. (2022) · Bulletin of the National Research Centre/Bulletin of the National Research Center · doi:10.1186/s42269-022-00816-x · Cited by 8

Emerging Communication Technologies for Industrial Internet of Things: Industry 5.0 Perspective

Kumar, N., Sharma, B., & Narang, S. K. (2022) · Lecture notes in networks and systems · doi:10.1007/978-981-19-1142-2_9 · Cited by 8

Anomaly detection using different types of machine learning models in the context of “smart maintenance technologies in the manufacturing industry”

Giliyana, S. A. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.01.156 · Cited by 7

The Global Factory Revisited

Buckley, P. J., & Enderwick, P. (2025) · Management International Review · doi:10.1007/s11575-025-00585-5 · Cited by 7

Leveraging Digital Twin for operational resilience in the oil and gas industry

Mazzuto, G., Pietrangeli, I., Ortenzi, M., Ciarapica, F. E., & Bevilacqua, M. (2025) · Array · doi:10.1016/j.array.2025.100443 · Cited by 7

Society 5.0 ‐ Aiming for a super smart society through industry 5.0: An emerging research agenda

Mahajan, S., Narkhede, G. B., Washimkar, D., Kore, S. S., Narkhede, R., & Chaudhari, T. (2025) · Business and Society Review · doi:10.1111/basr.70024 · Cited by 7

Real-time penetration depth prediction via physics-informed learning from molten pool surface morphology in laser filler wire welding

Lu, R., Lou, M., Xia, Y.-J., & Li, Y. (2025) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-025-02738-7 · Cited by 7

Design of a prototype of manipulator arm for implementing pick-and-place task in industrial robot system using TCS3200 color sensor and ATmega2560 microcontroller

Najmurrokhman, A., Kusnandar, K., Maulana, F. R. I., Wibowo, B. H., & Nurlina, E. (2019) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1375/1/012041 · Cited by 7

SÜRDÜRÜLEBİLİR ÜRETİMDE ENDÜSTRİ 4.0’IN YERİ

Özenir, İ., & Nakıboğlu, G. (2019) · Business And Management Studies An International Journal · doi:10.15295/bmij.v7i5.1197 · Cited by 7

Deep-Learning-Based Cyber-Physical System Framework for Real-Time Industrial Operations

Maru, V., Nannapaneni, S., Krishnan, K., & Arishi, A. (2022) · Machines · doi:10.3390/machines10111001 · Cited by 8

Adoptation of Blockchain of Things(BCOT): Oppurtunities & Challenges

Yadav, A. K., & Vishwakarma, V. P. (2022) · IEEE International Conference on Blockchain and Distributed Systems Security (ICBDS) · doi:10.1109/icbds53701.2022.9935985 · Cited by 7

Environmental Side of Fourth Industrial Revolution: The Positive and Negative Effects of I4.0 Technologies

Parmentola, A., Tutore, I., & Fiore, M. C. D. (2022) · Springer eBooks · doi:10.1007/978-3-030-84205-5_84 · Cited by 9

EREMI: An Innovative Interdisciplinary Approach for Higher Education in Resource Efficient Manufacturing Environments

Sikora, A., Titova, T. P., Janevska, G., Kostov, M., Halunga, S. V., Suciu, G. D., & Georgiev, G. (2023) · Sustainability · doi:10.3390/su151310244 · Cited by 7

Technological anxiety during the implementation of Industry 4.0 technologies – a cross-case study analysis among Polish manufacturing companies

Sajdak, M., & Młody, M. (2023) · Competitiveness Review An International Business Journal incorporating Journal of Global Competitiveness · doi:10.1108/cr-03-2023-0066 · Cited by 7

Assessing Factory's Industry 4.0 Readiness: A Practical Method for IIoT Sensor and Network Analysis

Anbalagan, S. N., Schwarz-Tonhauser, M., Bemthuis, R., & Havinga, P. (2024) · Procedia Computer Science · doi:10.1016/j.procs.2024.02.090 · Cited by 7

Integration of AHP and fuzzy inference systems for empowering transformative journeys in organizations: Assessing the implementation of Industry 4.0 in SMEs

Fernández, I., Puente, J., Ponte, B., & Gómez, A. G. (2024) · Applied Intelligence · doi:10.1007/s10489-024-05816-0 · Cited by 7

Industry 5.0: a conceptual cybersecurity model for secured digital transformation of enterprises

Chaudhuri, A., Jayalakshmi, R., Bala, P. K., Shoemaker, D., & Behera, R. K. (2025) · EDPACS · doi:10.1080/07366981.2024.2445413 · Cited by 7

Semantic-Enhanced Digital Twin for Industrial Working Environments

Yang, C., Guo, Q., Yu, H., Chen, Y., Taleb, T., & Tammi, K. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-78572-6_1 · Cited by 7

Exploring the experiences of oil and gas industry executives in embracing industry 4.0: Insights, challenges, and strategies

Dua, S. (2025) · Computers & Industrial Engineering · doi:10.1016/j.cie.2025.111377 · Cited by 7

Analysis Regarding the Approach of the aspects of Resilience in the Implementation of Industry 4.0, for Employees who have had technological Unemployment

dos Santos, J. P., de Andrade, A. A., Facó, J. F. B., Gasi, F., & Junger, A. P. (2020) · International Journal of Advanced Engineering Research and Science · doi:10.22161/ijaers.76.34 · Cited by 7

A novel taxonomy of organizational learning contextual factors: Review of 2004–2020 top-ranked journals

Scipioni, S. (2021) · Online Journal of Applied Knowledge Management · doi:10.36965/ojakm.2021.9(1)16-30 · Cited by 8

Zombification and Industry 4.0—Directional Financialisation against Doomed Industrial Revolution

Kovács, O. (2022) · Social Sciences · doi:10.3390/socsci11050218 · Cited by 7

Lean Manufacturing and Industry 4.0/5.0

Thomaz, J. P. C. F., & Bispo, H. I. N. (2022) · Advances in logistics, operations, and management science book series · doi:10.4018/978-1-7998-9715-6.ch006 · Cited by 7

One datum and many values for sustainable Industry 4.0: a prognostic and health management use case

Sabbatini, L., Belli, A., Palma, L., & Pierleoni, P. (2022) · International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering · doi:10.11591/ijece.v13i1.pp658-668 · Cited by 7

Digital Twin Application to Energy Consumption Management in Production: A Literature Review

Perossa, D., Santacruz, R. F. B., Rocca, R. L., & Fumagalli, L. (2023) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-25182-5_10 · Cited by 7

An Integrated Joint for Cooperative Robots

Tang, J., Cheng, L., Liu, J., Wang, Y., & Liu, R. (2019) · IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO) · doi:10.1109/arso46408.2019.8948780 · Cited by 7

Integration of an MES and AIV Using a LabVIEW Middleware Scheduler Suitable for Use in Industry 4.0 Applications

Rao, M., Lynch, L., Coady, J., Toal, D., & Newe, T. (2020) · Applied Sciences · doi:10.3390/app10207054 · Cited by 7

Design, Fabrication and Risk Assessment of IoT Unit for Products Manufactured in Industry 4.0 Factory

Hirman, M., Benešová, A., Šíma, K., Steiner, F., & Tupa, J. (2020) · Procedia Manufacturing · doi:10.1016/j.promfg.2020.10.165 · Cited by 7

Examination of Science Self-Regulation Skills of Gifted and Non-Gifted Students

Nacaroğlu, O., Bektaş, O., & Tüysüz, M. (2021) · Journal on Efficiency and Responsibility in Education and Science · doi:10.7160/eriesj.2021.140403 · Cited by 7

Developing a supervised machine‐learning model capable of distinguishing fiber orientation of polymer composite samples nondestructively tested using active ultrasonics

Bedrosian, A. D., Thompson, M. R., Hrymak, A. N., & Lanza, G. (2022) · Journal of Advanced Manufacturing and Processing · doi:10.1002/amp2.10138 · Cited by 7

Making model checking feasible for GOAL

Yang, Y. H., & Holvoet, T. (2023) · Annals of Mathematics and Artificial Intelligence · doi:10.1007/s10472-023-09898-3 · Cited by 7

Modeling System Based on Machine Learning Approaches for Predictive Maintenance Applications

Martins, J. P. S., Rodrigues, F. M., & Henriques, N. P. F. (2020) · KnE Engineering · doi:10.18502/keg.v5i6.7105 · Cited by 7

A three-level hierachical framework for additive manufacturing

Ren, Y. M., Ding, Y., Zhang, Y., & Christofides, P. D. (2021) · Digital Chemical Engineering · doi:10.1016/j.dche.2021.100001 · Cited by 7

Digital Technologies for Lean Manufacturing

George, M., Nhi, L. K. Y., Ngọc, N. M., Tung, V. N. D., Truc, L. P. T., & Nayak, R. (2022) · Textile science and clothing technology · doi:10.1007/978-981-19-2108-7_10 · Cited by 6

Adoption of Industry 4.0 in Developing Countries: Scale Development and Empirical Validation

Düzgün, S. S., Özen, Ü., & Fındık, D. (2025) · Verimlilik dergisi · doi:10.51551/verimlilik.1647544 · Cited by 6

Future-fit TVET students for Industry 4.0: exploring talent domains and components through WBL and applied research in higher education

Mazlan, M. H., Puteh, S., Mohamad, Z., Sulaiman, N. L., Salleh, K. M., Omar, W. R. W., Buhari, R., Bahrum, M. I. H., & Nasuha, A. (2026) · Higher Education Skills and Work-based Learning · doi:10.1108/heswbl-05-2025-0205 · Cited by 6

Federated-Learning-based Decision Support for Industrial Internet of Things (IIoT)-based Printed Circuit Board Assembly Process

Tsang, Y. P., Wu, C. H., Ip, W. H., & Lee, C. K. M. (2022) · Journal of Grid Computing · doi:10.1007/s10723-022-09637-8 · Cited by 6

Edupreneur: Developing Boardgame As a product of University Entrepreneurial Activities

Wicaksana, S. A., & Mangundjaya, W. L. (2022) · IJEBD (International Journal Of Entrepreneurship And Business Development) · doi:10.29138/ijebd.v5i2.1758 · Cited by 6

Cross-sectional determinants of lactose-free food awareness and purchase among adult consumers

Yılmaz, B., Ağagündüz, D., Kalyoncu, Z., Yeşilyurt, N., Ergin, Ş., & Murat, N. (2023) · Journal of Dairy Research · doi:10.1017/s0022029923000018 · Cited by 6

Work Life Balance Model, Work Stress and Performance of Millennial Generation Online Taxibike Drivers

Ghani, M. A., & Muttaqiyathun, A. (2023) · International Journal of Social Service and Research · doi:10.46799/ijssr.v3i3.318 · Cited by 6

The Impact of Industry 4.0 on Supply Chain Integration in Apparel Sector, Sri Lanka

Madushanka, C., Hakeem, A., Uththarangi, C., Rupigeena, J., Wickramaarachchi, C., Ehalapitiya, S., & Madhavika, N. (2023) · International Research Conference on Smart Computing and Systems Engineering (SCSE) · doi:10.1109/scse59836.2023.10215014 · Cited by 6

Advanced virtual prototyping of robotic cells using physics-based simulation

Raffaeli, R., Neri, F., Peruzzini, M., Berselli, G., & Pellicciari, M. (2023) · International Journal on Interactive Design and Manufacturing (IJIDeM) · doi:10.1007/s12008-023-01677-y · Cited by 6

Employing word-embedding for schema matching in standard lifecycle management

Oh, H., Kulvatunyou, B., Jones, A. T., & Finin, T. (2023) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2023.100547 · Cited by 6

A Comparison Between Supervised Learning Techniques for Predictive Maintenance in Twin Screw Air Compressors

Zanoli, S. M., Pepe, C., & Hancha, M. S. (2023) · IEEE International Conference on Industry Applications · doi:10.1109/induscon58041.2023.10374593 · Cited by 6

Internet of Production: Unleashing the Full Potential of Industry 4.0 – A Comprehensive Review of Trends, Drivers, and Challenges

Onu, P., Mbohwa, C., & Pradhan, A. (2024) · Procedia Computer Science · doi:10.1016/j.procs.2024.02.027 · Cited by 6

Inovasi dan Tren Terkini dalam Pengembangan Karir Pendidikan Teknologi Kejuruan

Latifah, U., Jalinus, N., & Fadhilah, F. (2024) · Al Qalam Jurnal Ilmiah Keagamaan dan Kemasyarakatan · doi:10.35931/aq.v18i5.3934 · Cited by 8

Projections of global energy transition models in the wake of industrial revolution and climate change policies

Mert, E., Aksu, M., & Çeliktaş, M. S. (2025) · Clean Energy Science and Technology · doi:10.18686/cest273 · Cited by 6

The convergence of additive manufacturing and artificial intelligence with LLMs for smart product design

Bassey, M., Akpan, J., Ikpe, A., David, V., & Kehinde, T. (2025) · Academia Materials Science · doi:10.20935/acadmatsci7868 · Cited by 5

From smart manufacturing in Industry 4.0 to industrial metaverse for Industry 5.0

Jiang, Z. H., Ma, N., Yao, X., Zhou, J., Wang, K., Xie, T., & Meng, J. (2025) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2025.2556440 · Cited by 6

“New Normal” Strategic Communication

Kostić, S. C., & Šarenac, J. G. (2019) · Advances in logistics, operations, and management science book series · doi:10.4018/978-1-5225-9416-1.ch005 · Cited by 6

Selection of the ERP System with Regard to the Global 4th Industrial Revolution

Polívka, M., & Dvořáková, L. (2021) · SHS Web of Conferences · doi:10.1051/shsconf/20219204019 · Cited by 6

An Analysis of Big Data Analytics, IoT and Augmented Banking on Consumer Loan Banking Business in Germany

Putra, M. P. (2021) · Journal of Research on Business and Tourism · doi:10.37535/104001120212 · Cited by 6

An Open-Source Tool Modeling the ETSI-MEC Architecture in the Industry 4.0 Context

Massari, S., Mirizzi, N., Piro, G., & Boggia, G. (2021) · Mediterranean Conference on Control and Automation (MED) · doi:10.1109/med51440.2021.9480205 · Cited by 6

Multi-criteria Decision Support with SWARA and TOPSIS Methods to the Digital Transformation Process in the Iron and Steel Industry

Şahin, Y., & Bozkurt, Y. (2021) · Lecture notes in mechanical engineering · doi:10.1007/978-3-030-90421-0_26 · Cited by 6

User-centred design in industrial collaborative automated systems

Pizzagalli, S. L., Kuts, V., & Otto, T. (2021) · Proceedings of the Estonian Academy of Sciences · doi:10.3176/proc.2021.4.10 · Cited by 6

A robust 4.0 dual-classifier for determining the internal condition of watermelons using YOLOv4-tiny and sensory

Adeniji, K. A., Onibonoje, M. O., Minevesho, A., Ejidokun, T. O., & Omitola, O. O. (2022) · Indonesian Journal of Electrical Engineering and Computer Science · doi:10.11591/ijeecs.v28.i3.pp1834-1844 · Cited by 6

Artificial Intelligence and Cognitive Computing in Companies in Portugal: An Outcome of Partial Least Squares—Structural Equations Modeling

Costa, R. L. D., Gupta, V., Gonçalves, R., Dias, Á., Pereira, L., & Gupta, C. (2022) · Mathematics · doi:10.3390/math10224358 · Cited by 7

Assessing 3D printing processes as enablers of circular economy

Psihoyos, H. O., Mouzakitis, Y., Adamides, E. D., & Lampeas, G. N. (2022) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/1123/1/012004 · Cited by 6

A new SysML profile for autonomous mobile robots development: ROS2ML

Guizani, A., Aloui, K., Hammadi, M., Soriano, T., & Haddar, M. (2023) · Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science · doi:10.1177/09544062221149314 · Cited by 6

SWOT Analysis of Batik Semarangan Competitiveness in The Disruption Era

Widiastuti, C. T., & Santoso, A. (2022) · Indonesian Journal of Business and Entrepreneurship · doi:10.17358/ijbe.8.3.430 · Cited by 6

Smart IoT platform for Big Data analysis in predictive maintenance

Przepióra, J., Bałazy, P., Książek, P., Knap, P., Pasławski, P., & Pietrzak, M. (2023) · International Carpathian Control Conference · doi:10.1109/iccc57093.2023.10178906 · Cited by 6

CAPTURING THE REALITY OF INDUSTRY 4.0 READINESS DIMENSIONS AND INDICATORS IN A DEVELOPING COUNTRY: AN ANALYSIS OF APPLYING I4.0 IN INDONESIA

Hasbullah, H., & Bareduan, S. A. (2023) · The South African Journal of Industrial Engineering · doi:10.7166/34-2-2846 · Cited by 6

Precision Grazing: when Agriculture, Livestock and Technology unite

Tamburis, O., Magliulo, M., Tramontano, A., Perillo, G., Benis, A., & Calabrò, S. (2023) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata59044.2023.10386768 · Cited by 6

SoK: A Taxonomy for Hardware-Based Fingerprinting in the Internet of Things

Spinnler, C., Labs, T., & Franchi, N. (2024) · International Conference on Availability, Reliability and Security (ARES) · doi:10.1145/3664476.3670872 · Cited by 6

Modelling and verification of the nickel electroforming process of a mechanical vane fit for Industry 4.0

Andreou, E., & Roy, S. (2024) · Digital Chemical Engineering · doi:10.1016/j.dche.2024.100177 · Cited by 6

Scaling approach towards electrochemical micromachining: a method to evaluate similarity

Mouliprasanth, B., & Hariharan, P. (2020) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-020-05604-3 · Cited by 6

Examining the roles and challenges of human capital influence on 4th industrial revolution

Fayomi, O. S. I., Akande, I. G., Esse, U. C., & Oladipupo, S. I. (2020) · AIP conference proceedings · doi:10.1063/5.0033737 · Cited by 6

IoT-TEG 4.0: A New Approach 4.0 for Test Event Generation

Vélez-Estévez, A., Gutiérrez‐Madroñal, L., & Medina‐Bulo, I. (2021) · IEEE Transactions on Reliability · doi:10.1109/tr.2021.3087781 · Cited by 6

What Are the Chances of Resilon to Dominate the Market Filling Materials for Endodontics?

Dobrzańska, J., Dobrzański, L. B., Dobrzański, L. A., Dobrzańska-Danikiewicz, A. D., & Gołombek, K. (2021) · Metals · doi:10.3390/met11111744 · Cited by 6

ANNOUNCEMENT

(1998) · Social Science Research · doi:10.1016/s0049-089x(98)90614-7

Artificial Intelligence Towards Future Industrial Opportunities and Challenges

Dagnaw, G. A. (2020) · DigitalCommons - Kennesaw State University (Kennesaw State University) · Cited by 17

The Nine Pillars of technology for Industry 4.0

Chuah, J. H. (2020) · Institution of Engineering and Technology eBooks · doi:10.1049/pbte088e_ch1 · Cited by 2

Industry 4.0: tools and implementation

Sanghavi, D., Parikh, S., & Raj, S. A. (2019) · Management and Production Engineering Review · doi:10.24425/mper.2019.129593 · Cited by 42

Everything You Need to Know about Intelligent Manufacturing

Shah, A. A., Chowdhry, B. S., Hussain, T., Nisar, K., Shaikh, M. Z., & Samo, S. (2022) · CRC Press eBooks · doi:10.1201/9781003220985-2