This study presents a comprehensive evaluation of the current status of smart manufacturing systems (SMS), with a specific emphasis on their theoretical significance in the context of technology management and technology development. The paper examines the theoretical underpinnings of development of technology through the lens of Rogers' Diffusion of Innovation (DoI) theory. Additionally, the paper employs Rieck and Dickson's Technology Strategy Model (TSM) to emphasize the importance of technology management. By incorporating the Management of Technology (MOT) theory, the paper aims to provide a comprehensive framework for understanding and shaping technology development. The integration of several technologies inside the SMS system has been the subject of discussion in relation to patenting. The features of Smart Manufacturing Systems (SMS) have been examined in order to analyze the comprehensive components of this emerging technological system. The suggested SMS model of the clothing manufacturing unit has been used to represent the global textile complex. This research incorporates recent scholarly publications and advancements in technology to provide a comprehensive understanding of future manufacturing system views. The objective is to minimize human involvement and enhance production efficiency within the manufacturing business. The primary components of the SMS have been identified as the cyber-physical system, artificial intelligence (AI), digital twin, enterprise resource planning, additive manufacturing, and big data
Keywords
Smart Manufacturing Systems, Cyber-Physical Systems, Rogers' Diffusion of Innovation, Rieck and Dickson's Technology Strategy Model
S. Jain and A. Narayanan, “Digital Twin–Enabled Machine Learning for Smart Manufacturing,” Smart and Sustainable Manufacturing Systems, vol. 7, no. 1, p. 20220035, Jul. 2023, doi: 10.1520/ssms20220035.
V. Kharchenko, “A Digital Twin for the Logistics System of a Manufacturing Enterprise Using Industrial IoT,” Information & Security: An International Journal, vol. 47, no. 1, pp. 125–134, 2020, doi: 10.11610/isij.4708.
J. Morgan, M. Halton, Y. Qiao, and J. G. Breslin, “Industry 4.0 smart reconfigurable manufacturing machines,” Journal of Manufacturing Systems, vol. 59, pp. 481–506, Apr. 2021, doi: 10.1016/j.jmsy.2021.03.001.
A. M. Beausoleil, “Revisiting Rogers: the diffusion of his innovation development process as a normative framework for innovation managers, students and scholars,” Journal of Innovation Management, vol. 6, no. 4, pp. 73–97, Mar. 2019, doi: 10.24840/2183-0606_006.004_0006.
F. F. Kharbat and A. S. Abu Daabes, “E-proctored exams during the COVID-19 pandemic: A close understanding,” Education and Information Technologies, vol. 26, no. 6, pp. 6589–6605, Feb. 2021, doi: 10.1007/s10639-021-10458-7.
R. Baskerville and J. Pries-Heje, “A multiple-theory analysis of a diffusion of information technology case,” Information Systems Journal, vol. 11, no. 3, pp. 181–212, Jul. 2008, doi: 10.1111/j.1365-2575.2001.00106.x.
M. R. Julianto and B. Daniawan, “E-Commerce Information System Using Technology Acceptance Model Approach,” Jurnal TAM (Technology Acceptance Model), vol. 13, no. 1, p. 1, Jul. 2022, doi: 10.56327/jurnaltam.v13i1.1106.
A. Tahriri and H. Divsar, “Male and Female EFL Learners’ Self-Perceived Strategy Use across Various Educational Levels: A Case Study,” English Language Teaching, vol. 4, no. 4, Nov. 2011, doi: 10.5539/elt.v4n4p181.
B. Lundvall, “National Innovation Systems—Analytical Concept and Development Tool,” Industry & Innovation, vol. 14, no. 1, pp. 95–119, Feb. 2007, doi: 10.1080/13662710601130863.
R. Subha, A. Haldorai, and A. Ramu, “An Optimal Approach to Enhance Context Aware Description Administration Service for Cloud Robots in a Deep Learning Environment,” Wireless Personal Communications, vol. 117, no. 4, pp. 3343–3358, Feb. 2021, doi: 10.1007/s11277-021-08073-3.
S. K. Gates, “Pretrial diversion agreements after Andersen’s prosecution: a utilitarian theoretical framework,” Journal of Financial Crime, Oct. 2022, Published, doi: 10.1108/jfc-08-2022-0203.
I. Kovalenko, M. Saez, K. Barton, and D. Tilbury, “SMART: A System-Level Manufacturing and Automation Research Testbed,” Smart and Sustainable Manufacturing Systems, vol. 1, no. 1, p. 20170006, Oct. 2017, doi: 10.1520/ssms20170006.
S. Dong and L. Qi, “Model Analysis and Simulation of Equipment-Manufacturing Value Chain Integration Process,” Complexity, vol. 2020, pp. 1–10, Nov. 2020, doi: 10.1155/2020/6620679.
S. Roffeh, “Social and legal aspects on the topic of virtual rape,” Legal Novels, vol. 9, pp. 120–130, 2019, doi: 10.32847/ln.2019.9.16.
M. Hedelind and M. Jackson, “How to improve the use of industrial robots in lean manufacturing systems,” Journal of Manufacturing Technology Management, vol. 22, no. 7, pp. 891–905, Sep. 2011, doi: 10.1108/17410381111160951.
Y. Lu, P. Witherell, and A. Jones, “Standard connections for IIoT empowered smart manufacturing,” Manufacturing Letters, vol. 26, pp. 17–20, Oct. 2020, doi: 10.1016/j.mfglet.2020.08.006.
E. Yalcinkaya, A. Maffei, H. Akillioglu, and M. Onori, “Empowering ISA95 compliant traditional and smart manufacturing systems with the blockchain technology,” Manufacturing Review, vol. 8, p. 15, 2021, doi: 10.1051/mfreview/2021013.
G. Hofbauer, A. Sangl, and S. Engelhardt, “The Digital Transformation of the Product Management Process: Conception of Digital Twin Impacts for the Different Stages,” International Journal Of Innovation And Economic Development, vol. 5, no. 2, pp. 74–86, 2019, doi: 10.18775/ijied.1849-7551-7020.2015.52.2006.
I. Bhattacharya, J. Toombs, and H. Taylor, “High fidelity volumetric additive manufacturing,” Additive Manufacturing, vol. 47, p. 102299, Nov. 2021, doi: 10.1016/j.addma.2021.102299.
E. J. Mcmanus and L. J. Scianna, “Configuration sets new technique for use in configuration management,” IEEE Transactions on Engineering Management, vol. EM-15, no. 4, pp. 193–197, 1968, doi: 10.1109/tem.1968.6447031.
J. S. Johnson, S. B. Friend, and H. S. Lee, “Big Data Facilitation, Utilization, and Monetization: Exploring the 3Vs in a New Product Development Process,” Journal of Product Innovation Management, vol. 34, no. 5, pp. 640–658, Jun. 2017, doi: 10.1111/jpim.12397.
Acknowledgements
Author(s) thanks to University in the Renmin University of China for research support.
Funding
No funding was received to assist with the preparation of this manuscript.
Ethics declarations
Conflict of interest
The authors have no conflicts of interest to declare that are relevant to the content of this article.
Availability of data and materials
No data available for above study.
Author information
Contributions
All authors have equal contribution in the paper and all authors have read and agreed to the published version of the manuscript.
Corresponding author
Anandakumar Haldorai
Anandakumar Haldorai
Sri Eshwar College of Engineering, Coimbatore, TamilNadu, India.
Open Access This article is licensed under a Creative Commons Attribution NoDerivs is a more restrictive license. It allows you to redistribute the material commercially or non-commercially but the user cannot make any changes whatsoever to the original, i.e. no derivatives of the original work. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
Cite this article
Anandakumar Haldorai, “Theoretical and Technological Analysis of Smart Manufacturing Systems”, Journal of Enterprise and Business Intelligence, vol.3, no.2, pp. 085-094, April 2023. doi: 10.53759/5181/JEBI202303009.