Recent Advances in Smart Manufacturing: A Case Study of Small, Medium, and Micro Enterprises (SMME)
Keywords:
Automation, Digitalization, Smart Manufacturing, Indusrty 4.0, Artificial Intelligence, Automation, Digitalization, Smart Manufacturing, Fourth Industrial Revolution, Artificial intelligenceAbstract
The digital revolution is the future pathway to experiencing business evolution. It will be difficult for any organization to remain in business without deploying fourth industry revolution (4IR) techniques. This review guides prospective business owners on the need to embrace Smart Manufacturing (SM) timely and appropriate to enhance their business performance indicators. Many manufacturing companies are facing challenges in adopting SM tools in their organization due to a lack of essential resources despite the benefits associated with SM. Therefore, this study systematically reviewed the criteria evaluation techniques in implementing digital factories. This work has analysed small, medium, and micro enterprises (SMME), with the view to enumerate the appropriate criteria to determine the level of digital technology tools adoption framework. It also highlights how to compensate for the inadequate technical and financial resources in SM. The guidelines for SM implementation adoption in SMME is a research gap that was missing in previous studies. SM benefits, challenges, applications, significance, impact, and future perspectives, are discussed. Evaluation Criteria for SM Adoption practices were also expounded. The framework used in this study will help SMME owners to adopt SM.
References
Abd Rahman, M. S. B.; E. Mohamad and A. A. B. abdul rahman. (2021). Development of IoT—enabled data analytics enhances decision support system for lean manufacturing process improvement. Concurrent Engineering, 29, 208-220.
Abubakr, M.; A. T. Abbas; I. Tomaz; M. S. Soliman; M. Luqman and H. Hegab. (2020). Sustainable and smart manufacturing: an integrated approach. Sustainability, 12, 2280.
Andronie, M.; G. Lăzăroiu; M. Iatagan; I. Hurloiu and I. Dijmărescu. (2021). Sustainable Cyber-Physical Production Systems in Big Data-Driven Smart Urban Economy: A Systematic Literature Review. Sustainability, 13, 751.
Ante, L. (2021). Digital twin technology for smart manufacturing and industry 4.0: A bibliometric analysis of the intellectual structure of the research discourse. Manufacturing Letters, 27, 96-102.
Ashima, R.; A. Haleem; S. Bahl; M. Javaid; S. K. Mahla and S. Singh. (2021). Automation and manufacturing of smart materials in Additive Manufacturingtechnologies using the Internet of Things towards the adoption of Industry 4.0. Materials Today: Proceedings, 45, 5081-5088.
Badhotiya, G. K.; S. Avikal; G. Soni and N. Sengar. (2021). Analyzing barriers to the adoption of circular economy in the manufacturing sector. International Journal of Productivity and Performance Management.
Barari, A.; M. De Sales Guerra Tsuzuki; Y. Cohen and M. Macchi. (2021). intelligent manufacturing systems towards the Industry 4.0 era. Journal of Intelligent Manufacturing, 32, 1793-1796.
Baroroh, D. K.; C.-H. Chu and L. Wang. (2021). Systematic literature review on augmented reality in smart manufacturing: Collaboration between human and computational intelligence. Journal of Manufacturing Systems, 61, 696-711.
Bermeo-Ayerbe, M. A.; C. Ocampo-martinez and J. Diaz-Rozo. (2022). Data-driven energy prediction modeling for both energy efficiency and maintenance in smart manufacturing systems. Energy, 238, 121691.
BI, Z.; W.-J. Zhang; C. Wu; C. Luo and L. Xu. (2021). Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective, Part I—Digital Triad Concept and Its Application as a System Reference Model. Machines, 9, 207.
Blaga, A.; C. Militaru; A.-D. Mezei and L. Tamas. (2021). Augmented reality integration into MES for connected workers. Robotics and Computer-Integrated Manufacturing, 68, 102057.
Büchi, G.; M. Cugno and R. Castagnoli. (2020). Smart factory performance and Industry 4.0. Technological Forecasting and Social Change, 150, 119790.
Bustinza, O. F.; M. Opazo-Basaez and S. Tarba. (2021). Exploring the interplay between Smart Manufacturing and KIBS firms in configuring product-service innovation performance. Technovation, 102258.
Cagliano, A. C.; G. Mangano and C. Rafele. (2021). Determinants of digital technology adoption in the supply chain. An exploratory analysis. Supply Chain Forum: An International Journal. Taylor & Francis, 100-114.
Chandra Shekhar Rao, V.; P. Kumarswamy; M. Phridviraj; S. Venkatramulu and V. Subba Rao. (2021). 5G enabled industrial Internet of Things (IIoT) architecture for smart manufacturing. Data Engineering and Communication Technology. Springer.
Chauhan, C. and Singh, A. (2021). Analysis of challenges responsible for the slow pace of Industry 4.0 diffusion. Research Anthology on Cross-Industry Challenges of Industry 4.0. IGI Global.
Chen, J. C.; T.-L. Chen; W.-J. Liu; C. Cheng and M.-G. Li. (2021). Combining empirical mode decomposition and deep recurrent neural networks for predictive maintenance of lithium-ion battery. Advanced Engineering Informatics, 50, 101405.
Çınar, Z. M.; Q. Zeeshan and O. Korhan. (2021). A Framework for Industry 4.0 Readiness and Maturity of Smart Manufacturing Enterprises: A Case Study. Sustainability, 13, 6659.
Cioffi, R.; M. Travaglioni; G. Piscitelli; A. Petrillo and A. Parmentola. (2020). Smart manufacturing systems and applied industrial technologies for a sustainable industry: A systematic literature review. Applied Sciences, 10, 2897.
Cohen, S. and Macek, J. (2021). Cyber-Physical Process Monitoring Systems, Real-Time Big Data Analytics, and Industrial Artificial Intelligence in Sustainable Smart Manufacturing. Economics, Management & Financial Markets, 16.
Davis, J.; T. Edgar; R. Graybill; P. Korambath; B. Schott; D. Swink; J. Wang and J. Wetzel. (2015). Smart manufacturing. Annual review of chemical and biomolecular engineering, 6, 141-160.
Del Giudice, M.; V. Scuotto; A. Papa; S. Y. Tarba; S. Bresciani and M. O. Warkentin. (2021). A self‐tuning model for smart manufacturing SMEs: Effects on digital innovation. Journal of Product Innovation Management, 38, 68-89.
Dey, B. K.; S. Bhuniya and B. Sarkar. (2021). Involvement of controllable lead time and variable demand for a smart manufacturing system under supply chain management. Expert Systems with Applications, 184, 115464.
Di Cataldo, S.; S. Lee; E. Macii and B. Vogel-Heuser. (2021). Leading information and communication technologies for smart manufacturing: facing the new challenges and opportunities of the 4th industrial revolution. Proceedings of the IEEE, 109, 320-325.
Didaskalou, E.; P. Manesiotis and D. Georgakellos (2021). Smart Manufacturing and Industry 4.0: A preliminary approach in Structuring a conceptual framework. WSEAS Transactions on Advances in Engineering Education, 18, 27-36.
Dobrilovic, D.; V. Brtka; Z. Stojanov; G. Jotanovic; D. Perakovic and G. Jausevac. (2021). A Model for Working Environment Monitoring in Smart Manufacturing. Applied Sciences, 11, 2850.
Edwards, C. (2021). Real-time advanced analytics, automated production systems, and smart industrial value creation in sustainable manufacturing Internet of Things. Journal of Self-Governance and Management Economics, 9, 32-41.
Elahi, B. and Tokaldany, S. A. (2021). Application of Internet of Things-aided simulation and digital twin technology in smart manufacturing. Advances in Mathematics for Industry 4.0. Elsevier.
Fazlollahtabar, H. (2021). Robotic Manufacturing Systems Using Internet of Things: New Era of Facing Pandemics. Automation, Robotics & Communications for Industry 4.0, 82.
Ferrer, B. R.; W. M. Mohammed; J. L. M. Lastra; A. Villalonga; G. Beruvides; F. Castaño and R. E. Haber. (2018). Towards the adoption of cyber-physical systems of systems paradigm in smart manufacturing environments. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN). IEEE, 792-799.
Friederich, J.; S. C. Jepsen; S. Lazarova-Molnar and T. Worm. (2021). Requirements for data-driven reliability modeling and simulation of smart manufacturing systems. 2021 Winter Simulation Conference (WSC). IEEE, 1-12.
F García-Muiña,. E., Medina-Salgado, M. S., Ferrari, A. M. and Cucchi, M. (2020). Sustainability transition in industry 4.0 and smart manufacturing with the triple-layered business model canvas. Sustainability, 12, 2364.
Ghobakhloo, M. (2020). Determinants of information and digital technology implementation for smart manufacturing. International Journal of Production Research, 58, 2384-2405.
Ghouat, M., Haddout, A. and Benhadou, M. (2021). Impact of Industry 4.0 Concept on the Levers of Lean Manufacturing Approach in Manufacturing Industries. International Journal of Automotive and Mechanical Engineering, 18, 8523–8530-8523–8530.
Guo, J. and Martinez-Garcia, M. (2021). Key technologies towards smart manufacturing based on swarm intelligence and edge computing. Computers & Electrical Engineering, 92, 107119.
Haricha, K., Khiat, A., Issaoui, Y., Bahnasse, A. and Ouajji, H. (2020). Towards smart manufacturing: Implementation and benefits. Procedia Computer Science, 177, 639-644.
Haricha, K., Khiat, A., Issaoui, Y., Bahnasse, A. and Ouajji, H. (2021). Towards smart manufacturing: Implementation and benefits. J. Ubiquitous Syst. Pervasive Networks, 15, 25-31.
Jamwal, A., Agrawal, R., Sharma, M. and Giallanza, A. (2021). Industry 4.0 technologies for manufacturing sustainability: a systematic review and future research directions. Applied Sciences, 11, 5725.
Jang, S., Chung, Y. and Son, H. (2022). Are smart manufacturing systems beneficial for all SMEs? Evidence from Korea. Management Decision.
Javaid, M., Haleem, A., Singh, R. P. and Suman, R. (2021). Substantial capabilities of robotics in enhancing industry 4.0 implementation. Cognitive Robotics, 1, 58-75.
Jwo, J.-S., Lin, C.-S. and Lee, C.-H. (2021). Smart technology-driven aspects for human-in-the-loop smart manufacturing. The International Journal of Advanced Manufacturing Technology, 114, 1741-1752.
Kamat, P., Shah, M., Lad, V., Desai, P., Vikani, Y. and Savani, D. (2021). Data Acquisition Using IoT Sensors for Smart Manufacturing Domain. Innovations in Information and Communication Technologies (IICT-2020). Springer.
Ke, G., Chen, R.-S., Chen, Y.-C., Wang, S. and Zhang, X. (2022). Using ant colony optimisation for improving the execution of material requirements planning for smart manufacturing. Enterprise information systems, 16, 379-401.
Kinkel, S., Baumgartner, M. and Cherubini, E. (2022). Prerequisites for the adoption of AI technologies in manufacturing–Evidence from a worldwide sample of manufacturing companies. Technovation, 110, 102375.
Kotsiopoulos, T., Sarigiannidis, P., Ioannidis, D. and Tzovaras, D. (2021). Machine learning and deep learning in smart manufacturing: the smart grid paradigm. Computer Science Review, 40, 100341.
Ku, C.-C., Chien, C.-F. and Ma, K.-T. (2020). Digital transformation to empower smart production for Industry 3.5 and an empirical study for textile dyeing. Computers & Industrial Engineering, 142, 106297.
Kumar, M., Shenbagaraman, V., Shaw, R. N. and Ghosh, A. (2021). Predictive data analysis for energy management of a smart factory leading to sustainability. Innovations in electrical and electronic engineering. Springer.
Larsen, M. S. S. and Lassen, A. H. (2020). Design parameters for smart manufacturing innovation processes. Procedia CIRP, 93, 365-370.
Lassen, A. H. and Waehrens, B. V. V. (2021). Labour 4.0: developing competencies for smart production. Journal of Global Operations and Strategic Sourcing.
Lăzăroiu, G., Kliestik, T. and Novak, A. (2021). Internet of Things smart devices, industrial artificial intelligence, and real-time sensor networks in sustainable cyber-physical production systems. Journal of Self-Governance and Management Economics, 9, 20-30.
Leng, J., Wang, D., Shen, W., Li, X., Liu, Q. and Chen, X. (2021). Digital twins-based smart manufacturing system design in Industry 4.0: A review. Journal of manufacturing systems, 60, 119-137.
Lepore, D., Dubbini, S., Micozzi, A. and Spigarelli, F. (2022). Knowledge sharing opportunities for Industry 4.0 firms. Journal of the Knowledge Economy, 13, 501-520.
Li, C., Chen, Y. and Shang, Y. (2021a). A review of industrial big data for decision making in intelligent manufacturing. Engineering Science and Technology, an International Journal.
Li, W., Huynh, B. H., Akhtar, H. and Myo, K. S. (2021b). Discrete Event Simulation as a Robust Supporting Tool for Smart Manufacturing. Implementing Industry 4.0. Springer.
Li, W., Liang, Y. and Wang, S. (2021c). Data-driven smart manufacturing technologies and applications, Springer.
Liu, J., Yu, D., Hu, Y., Yu, H., He, W. and Zhang, L. (2021). CNC Machine Tool Fault Diagnosis Integrated Rescheduling Approach Supported by Digital Twin-Driven Interaction and Cooperation Framework. IEEE Access, 9, 118801-118814.
Lyu, Z., Lin, P., Guo, D. and Huang, G. Q. (2020). Towards zero-warehousing smart manufacturing from zero-inventory just-in-time production. Robotics and Computer-Integrated Manufacturing, 64, 101932.
Majeed, A., Zhang, Y., Ren, S., Lv, J., Peng, T., Waqar, S. and Yin, E. (2021). A big data-driven framework for sustainable and smart additive manufacturing. Robotics and Computer-Integrated Manufacturing, 67, 102026.
Marinas, M., Dinu, M., Socol, A. G. and Socol, C. (2021). The technological transition of European Manufacturing companies to Industry 4.0. Is the human resource ready for advanced. Economic Computation & Economic Cybernetics Studies & Research, 55.
Mehrpouya, M., Dehghanghadikolaei, A., Fotovvati, B., Vosooghnia, A., Emamian, S. S. and Gisario, A. (2019). The potential of additive manufacturing in the smart factory industrial 4.0: A review. Applied Sciences, 9, 3865.
Meng, Y., Yang, Y., Chung, H., Lee, P.-H. and Shao, C. (2018). Enhancing sustainability and energy efficiency in smart factories: A review. Sustainability, 10, 4779.
Mittal, S., Khan, M. A., Purohit, J. K., Menon, K., Romero, D. and Wuest, T. (2020). A smart manufacturing adoption framework for SMEs. International Journal of Production Research, 58, 1555-1573.
Moiceanu, G. and Paraschiv, G. (2022). Digital Twin and Smart Manufacturing in Industries: A Bibliometric Analysis with a Focus on Industry 4.0. Sensors, 22, 1388.
Mondejar, M. E., Avtar, R., Diaz, H. L. B., Dubey, R. K., Esteban, J., Gómez-Morales, A., Hallam, B., Mbungu, N. T., Okolo, C. C. and Prasad, K. A. (2021). Digitalization to achieve sustainable development goals: Steps towards a Smart Green Planet. Science of The Total Environment, 794, 148539.
Moran, J. (2022). Manufacturers’ Dilemma: The Benefits, Risks, Policies, Laws, and Ethics of Smart Manufacturing.
Moshiri, M., Charles, A., Elkaseer, A., Scholz, S., Mohanty, S. and Tosello, G. (2020). An Industry 4.0 framework for tooling production using metal additive manufacturing-based first-time-right smart manufacturing system. Procedia CIRP, 93, 32-37.
Mourtzis, D., Angelopoulos, J. and Panopoulos, N. (2021). Smart Manufacturing and Tactile Internet Based on 5G in Industry 4.0: Challenges, Applications and New Trends. Electronics, 10, 3175.
My, C. A. (2021). The Role of Big Data Analytics and AI in Smart Manufacturing: An Overview. Research in Intelligent and Computing in Engineering, 911-921.
Nazir, A., Azhar, A., Nazir, U., Liu, Y.-F., Qureshi, W. S., Chen, J.-E. and Alanazi, E. (2021). The rise of 3D Printing entangled with smart computer aided design during COVID-19 era. Journal of Manufacturing Systems, 60, 774-786.
Nica, E., Stan, C. I., Luțan, A. G. and Oașa, R.-Ș. (2021). Internet of things-based real-time production logistics, sustainable industrial value creation, and artificial intelligence-driven big data analytics in cyber-physical smart manufacturing systems. Economics, Management, and Financial Markets, 16, 52-63.
Nicora, M. L., Ambrosetti, R., Wiens, G. J. and Fassi, I. (2021). Human–Robot Collaboration in Smart Manufacturing: Robot Reactive Behavior Intelligence. Journal of Manufacturing Science and Engineering, 143.
Oh, J. and Jeong, B. (2019). Tactical supply planning in smart manufacturing supply chain. Robotics and Computer-Integrated Manufacturing, 55, 217-233.
Parhi, S., Joshi, K. and Akarte, M. (2021). Smart manufacturing: a framework for managing performance. International Journal of Computer Integrated Manufacturing, 34, 227-256.
Patalas-Maliszewska, J. and Topczak, M. (2021). A new management approach based on Additive Manufacturing technologies and Industry 4.0 requirements. Advances in Production Engineering & Management, 16.
Patel, P., Ali, M. I. and Sheth, A. (2018). From raw data to smart manufacturing: AI and semantic web of things for industry 4.0. IEEE Intelligent Systems, 33, 79-86.
Pfeifer, M. R. (2021). Development of a Smart Manufacturing Execution System Architecture for SMEs: A Czech Case Study. Sustainability, 13, 10181.
Phuyal, S., Bista, D. and Bista, R. (2020). Challenges, opportunities and future directions of smart manufacturing: a state of art review. Sustainable Futures, 2, 100023.
Pixley, J. E., Kunrath, S., Paz, G., Li, B., Donovan, R. and Li, G. (2021). Enabling small and mediu m manufacturers to adopt smart manufacturing. The American Council for an Energy-Efficient Economy (ACEEE) 2021 summer study on energy efficiency in industry to be held on July 12–15.
Qi, Q. and Tao, F. (2018). Digital twin and big data towards smart manufacturing and industry 4.0: 360 degree comparison. Ieee Access, 6, 3585-3593.
Qi, Q., Tao, F., Cheng, Y., Cheng, J. and Nee, A. (2021). New IT driven rapid manufacturing for emergency response. Journal of Manufacturing Systems, 60, 928-935.
Qi, Q., Tao, F., Zuo, Y. and Zhao, D. (2018). Digital twin service towards smart manufacturing. Procedia Cirp, 72, 237-242.
Qian, Y., Liu, J., Cheng, Z. and Forrest, J. Y.-L. (2021). Does the smart city policy promote the green growth of the urban economy? Evidence from China. Environmental Science and Pollution Research, 28, 66709-66723.
Qiao, F., Liu, J. and Ma, Y. (2021). Industrial big-data-driven and CPS-based adaptive production scheduling for smart manufacturing. International Journal of Production Research, 59, 7139-7159.
Qu, Y., Ming, X., Liu, Z., Zhang, X. and Hou, Z. (2019). Smart manufacturing systems: state of the art and future trends. The International Journal of Advanced Manufacturing Technology, 103, 3751-3768.
Rinaldi, M., Caterino, M., Manco, P., Fera, M. and Macchiaroli, R. (2021). The impact of Additive Manufacturing on Supply Chain design: A simulation study. Procedia Computer Science, 180, 446-455.
Rizvi, A. T., Haleem, A., Bahl, S. and Javaid, M. (2021). Artificial intelligence (AI) and its applications in Indian manufacturing: a review. Current Advances in Mechanical Engineering, 825-835.
Sajjad, A., Ahmad, W., Hussain, S. and Mehmood, R. M. (2021). Development of Innovative Operational Flexibility Measurement Model for Smart Systems in Industry 4.0 Paradigm. IEEE Access.
Saqlain, M., Piao, M., Shim, Y. and Lee, J. Y. (2019). Framework of IoT-based industrial data management for smart manufacturing. Journal of Sensor and Actuator Networks, 8, 25.
Schein, K. E. and Rauschnabel, P. A. (2021). Augmented reality in manufacturing: exploring workers’ perceptions of barriers. IEEE Transactions on Engineering Management.
Serrano-Ruiz, J. C., Mula, J. and Poler, R. (2021). Smart manufacturing scheduling: A literature review. Journal of Manufacturing Systems, 61, 265-287.
Serrano-Ruiz, J. C., Mula, J. and Poler, R. (2022). Development of a multidimensional conceptual model for job shop smart manufacturing scheduling from the Industry 4.0 perspective. Journal of Manufacturing Systems, 63, 185-202.
Shahbazi, Z. and Byun, Y.-C. (2021a). Integration of blockchain, IoT and machine learning for multistage quality control and enhancing security in smart manufacturing. Sensors, 21, 1467.
Shahbazi, Z. and Byun, Y.-C. (2021b). Smart manufacturing real-time analysis based on blockchain and machine learning approaches. Applied Sciences, 11, 3535.
Sharifi, A., Ahmadi, M. and Ala, A. (2021). The impact of artificial intelligence and digital style on industry and energy post-COVID-19 pandemic. Environmental Science and Pollution Research, 28, 46964-46984.
Sharma, A., Mehtab, R., Mohan, S. and Shah, M. K. M. (2021). Augmented reality–an important aspect of Industry 4.0. Industrial Robot: the international journal of robotics research and Application.
Sharp, M., AK, R. and Hedberg JR, T. (2018). A survey of the advancing use and development of machine learning in smart manufacturing. Journal of manufacturing systems, 48, 170-179.
Shen, W., Hu, T., Zhang, C. and Ma, S. (2021). Secure sharing of big digital twin data for smart manufacturing based on blockchain. Journal of Manufacturing Systems, 61, 338-350.
Shukla, M. and Shankar, R. (2021). Modeling of critical success factors for adoption of smart manufacturing system in Indian SMEs: an integrated approach. OPSEARCH, 1-33.
Sivaji, A., Razak, R. A., Mohamad, N. F., Sazali, N., Musa, A., Bajuri, N. M., Hashim, A. M., Abdullah, M. S., Joha, N. D. and Azis, N. E (2020). Software Testing Automation: A Comparative Study on Productivity Rate of Open Source Automated Software Testing Tools For Smart Manufacturing. 2020 IEEE Conference on Open Systems (ICOS), IEEE, 7-12.
Thoben, K.-D., Wiesner, S. and Wuest, T. (2017). Industrie 4.0 and smart manufacturing-a review of research issues and application examples. International journal of automation technology, 11, 4-16.
Tripathi, V., Chattopadhyaya, S., Mukhopadhyay, A. K., Sharma, S., Singh, J., Pimenov, D. Y. and Giasin, K. (2021). An innovative agile model of smart lean–green approach for sustainability enhancement in Industry 4.0. Journal of Open Innovation: Technology, Market, and Complexity, 7, 215.
Tucker, G. (2021). Sustainable product lifecycle management, industrial big data, and Internet of things sensing networks in cyber-physical system-based smart factories. Journal of Self-Governance and Management Economics, 9, 9-19.
Uysal, M. P. and Mergen, A. E. (2021). Smart manufacturing in intelligent digital mesh: Integration of enterprise architecture and software product line engineering. Journal of Industrial Information Integration, 22, 100202.
Viswanathan, R. and Telukdarie, A. (2021). A systems dynamics approach to SME digitalization. Procedia Computer Science, 180, 816-824.
Volk, A. A., Campbell, Z. S., Ibrahim, M. Y., Bennett, J. A. and Abolhasani, M. (2022). Flow Chemistry: A Sustainable Voyage Through the Chemical Universe en Route to Smart Manufacturing. Annual Review of Chemical and Biomolecular Engineering, 13.
Wang, B., Tao, F., Fang, X., Liu, C., Liu, Y. and Freiheit, T. (2021a). Smart manufacturing and intelligent manufacturing: A comparative review. Engineering, 7, 738-757.
Wang, J., MA, Y., Zhang, L., Gao, R. X. and Wu, D. (2018). Deep learning for smart manufacturing: Methods and applications. Journal of manufacturing systems, 48, 144-156.
Wang, L., Liu, Z., Liu, A. and Tao, F. (2021b). Artificial intelligence in product lifecycle management. The International Journal of Advanced Manufacturing Technology, 114, 771-796.
Wang, P. and Luo, M. (2021). A digital twin-based big data virtual and real fusion learning reference framework supported by industrial internet towards smart manufacturing. Journal of manufacturing systems, 58, 16-32.
Wang, S., Jiang, L., Meng, J., Xie, Y. and Ding, H. (2021c). Training for smart manufacturing using a mobile robot-based production line. Frontiers of Mechanical Engineering, 16, 249-270.
Wang, S., Zhang, Y., Qian, C. and Zhang, D. (2021d). A framework for credit-driven smart manufacturing service configuration based on complex networks. International Journal of Computer Integrated Manufacturing, 1-26.
Warke, V., Kumar, S., Bongale, A. and Kotecha, K. (2021). Sustainable Development of Smart Manufacturing Driven by the Digital Twin Framework: A Statistical Analysis. Sustainability, 13, 10139.
Wunderle, M., Olmes, G., Nabieva, N., Häberle, L., Jud, S. M., Hein, A., Rauh, C., Hack, C. C., Erber, R. and Ekici, A. B. (2018). Risk, prediction and prevention of hereditary breast cancer–large-scale genomic studies in times of big and smart data. Geburtshilfe und Frauenheilkunde, 78, 481-492.
Xia, T., Zhang, W., Chiu, W. and Jing, C. O (2021). Using cloud computing integrated architecture to improve the delivery committed rate in smart manufacturing. Enterprise Information Systems, 15, 1260-1279.
Yalcinkaya, E., Maffei, A., Akillioglu, H. and Onori, M. (2021). Empowering ISA9-compliant traditional and smart manufacturing systems with blockchain technology. Manufacturing review.
Yao, X., Zhou, J., Lin, Y., Li, Y., Yu, H. and Liu, Y. (2019). Smart manufacturing based on cyber-physical systems and beyond. Journal of Intelligent Manufacturing, 30, 2805-2817.
Yonghui, C. and Jiang, H.(2021). Comparative analysis of China's equipment manufacturing enterprises and world-class enterprises based on a case study. 2021 2nd International Conference on E-Commerce and Internet Technology (ECIT). IEEE, 79-82.
Zeid, A., Sundaram, S., Moghaddam, M., Kamarthi, S. and Marion, T. (2019). Interoperability in smart manufacturing: Research challenges. Machines, 7, 21.
Zenisek, J., Wild, N. and Wolfartsberger, J. (2021). Investigating the potential of smart manufacturing technologies. Procedia computer science, 180, 507-516.
Zhang, X., Chang, X. and Qiu, H. (2021). Optimal product co-creation strategies in a service-oriented smart manufacturing supply chain. Procedia Computer Science, 192, 1924-1933.
Zheng, P., Sang, Z., Zhong, R. Y., Liu, Y., Liu, C., Mubarok, K., Yu, S. and Xu, X. (2018). Smart manufacturing systems for Industry 4.0: Conceptual framework, scenarios, and future perspectives. Frontiers of Mechanical Engineering, 13, 137-150.
Zhou, L., Jiang, Z., Geng, N., Niu, Y., Cui, F., Liu, K. and Qi, N. (2022). Production and operations management for intelligent manufacturing: a systematic literature review. International Journal of Production Research, 60, 808-846.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Nigerian Journal of Technological Development
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
In accordance with the Copyright Act of 1976, which became effective January 1, 1978, the following statement signed by each author must accompany the manuscript submitted: "I, the undersigned author, transfer all copyright ownership of the manuscript referenced above to the Nigerian Journal of Technological Development, in the event the work is published. I warrant that the article is original, does not infringe upon any copyright or other proprietary right of any third party, is not under consideration by another journal, and has not been published previously. I have reviewed and approve the submitted version of the manuscript and agree to its publication in the Nigerian Journal of Technological Development." A copyright transfer form should be downloaded from the NJTD Website ( http://njtd.com.ng/index.php/njtd). Author(s) will be consulted, whenever possible, regarding republication of material. All authors must have access to the data presented and the authors and sponsor (if applicable) must agree to share original data with the editor if requested.
