Collaborative manufacturing based on cloud, and on other I4.0 oriented principles and technologies: a systematic literature review and reflections

• Autorzy: Varela M. L. R. , Putnik G. D. , Manupati V. K. , Rajyalakshmi G. , Trojanowska J. , Machado J.

Identyfikatory

DOI

10.24425/119538

• Języki publikacji: EN

Abstrakty

EN

Recent rapid developments in information and network technology have profoundly influenced manufacturing research and its application. However, the product’s functionality and complexity of the manufacturing environments are intensifying, and organizations need to sustain the advantage of huge competitiveness in the markets. Hence, collaborative manufacturing, along with computer-based distributed management, is essential to enable effective decisions and to increase the market. A comprehensive literature review of recent and state-of-the-art papers is vital to draw a framework and to shed light on the future research avenues. In this review paper, the use of technology and management by means of collaborative and cloud manufacturing process and big data in networked manufacturing system have been discussed. A systematic review of research papers is done to draw conclusion and moreover, future research opportunities for collaborative manufacturing system were highlighted and discussed so that manufacturing enterprises can take maximum benefit.

Słowa kluczowe

EN

collaborative manufacturing; networked manufacturing; cloud manufacturing; I4.0; cyber physical system; Internet of things; big data management

• Wydawca: Production Engineering Committee of the Polish Academy of Sciences ; Polish Association for Production Management
• Czasopismo: Management and Production Engineering Review
• Rocznik: 2018
• Tom: Vol. 9, No. 3
• Strony: 90--99
• Opis fizyczny: Bibliogr. 34 poz., rys., tab.

Twórcy

autor

Varela M. L. R.

• Department of Production and Systems, School of Engineering, University of Minho, Portugal

autor

Putnik G. D.

• Department of Production and Systems, School of Engineering, University of Minho, Portugal

autor

Manupati V. K.

• School of Mechanical Sciences, VIT University, Vellore, Tamil Nadu, India

autor

Rajyalakshmi G.

• School of Mechanical Sciences, VIT University, Vellore, Tamil Nadu, India

autor

Trojanowska J.

• Poznan University of Technology, Chair of Management and Production Engineering, Piotrowo 3, 60-965 Poznan, Poland

autor

Machado J.

• Department of Mechanical Engineering, School of Engineering, University of Minho, Portugal

Bibliografia

• [1] Liu F., Liu J., Lei Q., The Connotation and research development trend of networked manufacturing, Proceedings of China Mechanical Engineering Annual Conference, Beijing, China, 22–27, 2002.
• [2] Trojanowska J., Varela M.L.R., Machado J., The Tool Supporting Decision Making Process in Area of Job-Shop Scheduling, [in:] Rocha A., Correia ´ A., Adeli H., Reis L., Costanzo S. [Eds.], Recent Advances in Information Systems and Technologies, WorldCIST 2017, Advances in Intelligent Systems and Computing, vol 571, pp. 490–498, 2017, Springer, Cham.
• [3] Kawa A., Pawlewski P., Golinska P., Hajdul M., Cooperative purchasing of logistics services among manufacturing companies based on semantic web and multi-agent system, Trends in Practical Applications of Agents and Multiagent Systems Springer, Berlin, pp. 249–256, 2010.
• [4] Monka P., Monkova K., Edl M., Zidkova H., Duchek V., Fundamental Requirements for CAPP Software Design Focusing on Industry 4.0 Specific Features, [in:] Ni J., Majstorovic V., Djurdjanovic D. [Eds.], Proceedings of 3rd International Conference on the Industry 4.0 Model for Advanced Manufacturing, AMP 2018, pp. 146–155, Lecture Notes in Mechanical Engineering, Springer, Cham
• [5] Kawa A., Simulation of dynamic supply chain configuration based on software agents and graph theory, International Work-Conference on Artificial Neural Networks, Springer, Berlin, pp. 346–349, 2009.
• [6] Rezaeian Nikbakhsh Javadian, Reza TavakkoliMoghaddam, Fariborz Jolai, A hybrid approach based on the genetic algorithm and neural network to design an incremental cellular manufacturing system, Applied Soft Computing, 11, 6, 4195–4202, 2011.
• [7] Costa E., Soares A.L., de Sousa J.P., Information, knowledge and collaboration management in the internationalisation of SMEs: a systematic literature review, International Journal of Information Management, 36, 4, 557–569, 2016.
• [8] Mohammad Rizal Firmansyah, Yousef Amer, A Review of Collaborative Manufacturing Network Models, International Journal of Materials, Mechanics and Manufacturing, 1, 1, 6–12, 2013.
• [9] Liang Guo, Shilong Wang, Ling Kang, Yang Cao, Agent-based manufacturing service discovery method for cloud manufacturing, Springer-Verlag London, 2015.
• [10] Zhi-Zhong Liu, Cheng Song, Dian-Hui Chu, ZhanWei Hou, Wei-Ping Peng, An Approach for Multipath Cloud Manufacturing Services Dynamic Composition, International Journal of Intelligent Systems, 1–23, 2016.
• [11] Liu Zhi-Zhong, et al., An Approach for Multipath Cloud Manufacturing Services Dynamic Composition, International Journal of Intelligent Systems, 32, 4, 371–393, 2017.
• [12] Hossein Akbaripour, Mahmoud Houshmand, Omid Fatahi Valilai, Cloud-Based Global Supply Chain: A Conceptual Model and Multilayer Architecture, Journal of Manufacturing Science and Engineering, 137, 04091, 2015.
• [13] Fanghua Ning, Weizong Zhou, Fengying Zhang, Qian Yin, Xiajing Ni, The Architecture Of Cloud Maufacturing And Its Key Technologies Research, Proceedings of IEEE CCIS2011 978-1-61284-204- 2/11, 2011.
• [14] Weixi Ji, Yi Cao, Suqing Liang, Yunzhong Yuan, Qi Zhang, Research and Application of Manufacturing Recourse Management In Manufacturing Enterprise Based on Internet of Things, International Conference on Intelligent System Design and Engineering Application 978-0-7695-4212-6/10, 2010.
• [15] Manupati V.K., Gokula Krishnan M., Varela M.L.R., Machado J., Telefacturing Based Distributed Manufacturing Environment for Optimal Manufacturing Service by Enhancing the Interoperability in the Hubs, Journal of Engineering, Vol. 2017, Article ID 9305989, 15 pages, 2017, Knowledge management.
• [16] He X.B. et al., Multi-View Modeling Scheme and Total Solution for Enterprise Digitalization, Advanced Materials Research, 102–104, 841–845, 2010.
• [17] Liu Yongkui et al., Workload-based multi-task scheduling in cloud manufacturing, Robotics and Computer-Integrated Manufacturing, 45, 3–20, 2017.
• [18] Lee H., Kim S.S., Integration of process planning and scheduling using simulation based genetic algorithms, International Journal of Advanced Manufacturing Technology, 18, 586–590, 2001.
• [19] Yang Y., Parsaei H., Leep H., A prototype of a feature-based multiple-alternative process planning system with scheduling verification, Computers and Industrial Engineering, 39, 109–124, 2001.
• [20] Li Yu-Chuan, Hsu-Sung Kuo, Wen-Shan Jian, DahDian Tang, Chien-Tsai Liu, Li Liu, Chien-Yeh Hsu, Yong-Kok Tan, Chung-Hong Hu, Building a generic architecture for medical information exchange among healthcare providers, International Journal of Medical Informatics, 61, 2, 241–246, 2001.
• [21] Zhang Y., Saravanan A., Fuh J., Integration of process planning and scheduling by exploring the flexibility of process planning, International Journal of Production Research, 41, 3, 611–628, 2003.
• [22] Cheng T.C.E. et al., A two-agent single-machine scheduling problem with truncated sum-of-processing-times-based learning considerations, Computers & Industrial Engineering, 60, 4, 534–541, 2011.
• [23] Bailey M.W., VerDuin W.H., FIPER – an intelligent system for the optimal design of highly engineered products. NIST Performance Metrics for Intelligent Systems Workshop, Gaithersburg, MD, USA, 2000.
• [24] Beiter K.A., Ishii K., Integrating producibility and product performance tools within a Web-service environment, Proceedings of ASME 2003 Design Engineering Technical Conferences, Chicago, IL, USA, DETC03/CIE-48281, 2003.
• [25] Xiao Angran et al., A Web-based distributed product realization environment, Proceedings of ASME 2001 Computer and Information in Engineering Conference, Pittsburgh, PA, 2001.
• [26] Mervyn Fathianathan, Bok S.H., Nee A.Y.C., Development of an Internet-enabled interactive fixture design system, Computer-Aided Design, 35, 10, 945– 957, 2003.
• [27] Ivanov V., Process-Oriented Approach to Fixture Design, [in:] Ivanov V. et al. [Eds.], Advances in Design, Simulation and Manufacturing, DSMIE 2018, Lecture Notes in Mechanical Engineering, Springer, Cham, pp. 42–50, 2019, https://doi.org/10.1007/978-3-319-93587-4 5.
• [28] Liaposhchenko O.O., Sklabinskyi V.I., Zavialov V.L., Pavlenko I.V., Nastenko O.V., Demianenko M.M., Appliance of inertial gas-dynamic separation of gas dispersion flaws in the curvilinear convergentdivergent channels for compressor equipment reliability improvement, IOP Conference Series: Materials Science and Engineering, 233, 012025, 2017, doi: 10.1088/1757-899X/233/1/012025.
• [29] Bigaj Z., Kolinski A., The analysis of the cold supply chain efficiency with the use of mobile technology, LogForum, 13, 1, 77–90, 2017.
• [30] Ge X., Fuwen Yang, Qing-Long Han, Distributed networked control systems: A brief overview, Information Sciences, 2015.
• [31] Kujawińska A., Rogalewicz M., Diering M., Hamrol A., Statistical Approach to Making Decisions in Manufacturing Process of Floorboard, [in:] Rocha Á., Correia A., Adeli H., Reis L., Costanzo S. [Eds.], Recent Advances in Information Systems and Technologies. WorldCIST, Advances in Intelligent Systems and Computing, Springer, 571, 499–508, 2017.
• [32] Kujawińska A., Diering M., Rogalewicz M., Żywicki K., Hetman Ł., Soft Modelling-Based Methodology of Raw Material Waste Estimation, [in:] Burduk A., Mazurkiewicz D. [Eds.], Intelligent Systems in Production Engineering and Maintenance – ISPEM 2017, Advances in Intelligent Systems and Computing, vol. 637, pp. 407–417, 2018, Springer, Cham.
• [33] Monostori L., Cyber-physical production systems: Roots, expectations and R&D challenges, Procedia CIRP, 17, 9–13, 2014.
• [34] Nitta N., Wu F., Lee J.T., Yushin G., Li-ion battery materials: present and future, Materials Today, 18, 5, 252–264, 2015.