Assessment of the requirements of smart production Systems in SMEs: Intuitionistic Fuzzy Best-Worst Method and Total Interpretive Structural Modeling Integrated Method
محورهای موضوعی : Operations ManagementMarjan Tavasoli Fard 1 , Payam Shojaei 2 , علی محمدی 3
1 - Department of Management, Shiraz University, Shiraz, Iran
2 - Shiraz University
3 - استاد بخش مدیریت دانشگاه شیراز
کلید واژه: Smart Manufacturing Systems, Small and Medium-Sized Companies, Intuitionistic Fuzzy Multiplicative Best-Worst Method, Total Interpretative Structural Modeling,
چکیده مقاله :
Today, manufacturing companies must address the increasing trend of smart manufacturing (SM) to maintain their competitiveness. Concurrently, small and medium enterprises (SMEs), which constitute the backbone of numerous production economies, are endeavoring to comprehend the complexities associated with implementing this advanced production system. However, many of these enterprises are hesitant to adopt SM due to insufficient human and financial resources. The transformation of a company's existing system into smart production systems, as opposed to implementing smart manufacturing from the outset, necessitates greater financial and temporal investment. Consequently, it is imperative to consider and integrate effective requirements for smart production systems during the design phase. This study aims to identify these requirements, ascertain their significance, and comprehend the contextual relationships among them. To achieve this, a systematic review method is employed to identify the requirements, followed by the Intuitionistic Fuzzy Multiplicative Best-Worst Method (IFMBWM) to determine their weights. Finally, the TISM method is utilized to understand the interrelationships and compare the levels obtained with the results of the best-worst method. The results indicated that the effective requirements can be categorized into eight main criteria. The highest and most fundamental criterion is the requirement for digitalization and real-time data connection. The second criterion is automation, followed by smart communication with beneficiaries as the third. Overall, small and medium-sized enterprises should prioritize information technology and artificial intelligence requirements to advance towards smart production systems.
Bello K A, Kanakana-Katumba M G, Maladzhi R W, Omoyi C O (2024) Recent advances in smart manufacturing: a case study of small, medium, and micro enterprises (SMME). Nigerian Journal of Technological Development, 21(1), 29-41. https://doi.org/10.4314/njtd.v21i1.1905
Bonab S R, Haseli G, Rajabzadeh H, Ghoushchi S J, Hajiaghaei-Keshteli M, Tomaskova, H (2023) Sustainable resilient supplier selection for IoT implementation based on the integrated BWM and TRUST under spherical fuzzy sets. Decision making: applications in management and engineering, 6(1), 153-185. https://doi.org/10.31181/dmame12012023b
Dubey R, Altay N, Gunasekaran A, Blome C, Papadopoulos T, Childe S J (2018) Supply chain agility, adaptability and alignment: Empirical evidence from the Indian auto components industry. International Journal of Operations and Production Management, 38(1), 129–148. https://doi.org/10.1108/IJOPM-04-2016-0173
Ghobakhloo M (2020) Determinants of information and digital technology implementation for smart manufacturing. Int J Prod Res 58:2384–2405. https://doi.org/10.1080/00207543.2019.1630775
Hammad M, Islam M S, Salam M A, Jafry A T, Ali I, Khan W A (2023) Framework for the implementation of smart manufacturing systems: a case in point. Processes, 11(5), 1436. https://doi.org/10.3390/pr11051436
Haricha K, Khiat A, Issaoui Y, Bahnasse A, Ouajji H (2023) Recent technological progress to empower smart manufacturing: Review and potential guidelines. IEEE Access, 11, 77929-77951. https://doi.org/10.1109/ACCESS.2023.3246029
Jung W K, Kim D R, Lee H, Lee T H, Yang I, Youn B D, Ahn S H (2021) Appropriate Smart Factory for SMEs: Concept, Application and Perspective. International Journal of Precision Engineering and Manufacturing, 22(1), 201-215. https://doi.org/10.1007/s12541-020-00445-2
Kanakana Katumba M G, Maladzi R W, Oyesola M O (2022). Smart Manufacturing Systems for Small Medium Enterprises: A Conceptual Data Collection Architecture. In Global Conference on Sustainable Manufacturing (pp. 604-613). https://doi.org/10.1007/978-3-031-28839-5_68
Kılıç R, Erkayman B, (2023) Multi-criteria analysis through determining production technology based on critical features of smart manufacturing systems. Soft Computing, 27(11), 7071-7096. https://doi.org/10.1007/s00500-023-08012-3
Kumar A (2018) Methods and materials for smart manufacturing: additive manufacturing, internet of things, flexible sensors and soft Robotization. Manuf Lett 15:122–125. https://doi.org/10.1016/j.mfglet.2017.12.014
Kusiak A (2019) Fundamentals of smart manufacturing: a multithread perspective. Annu Rev Control 47:214–220. https://doi.org/10.1016/j.arcontrol.2019.02.001
Larsen M S, Lassen A H (2020) Design parameters for smart manufacturing innovation processes. Procedia CIRP 93:365–370. https://doi.org/10.1016/j.procir.2020.04.068
Lu H P, Weng C I (2018) Smart manufacturing technology, market maturity analysis and technology roadmap in the computer and electronic product manufacturing industry. Technol Forecast Soc Chang 133:85–94. https://doi.org/10.1016/j.techfore.2018.03.005
Mahmoud M A, Ramli R, Azman F, Grace J (2020) ‘‘A development methodology framework of smart manufacturing systems (industry 4.0)’’. Int J Adv Sci Eng Inf Technol 10(5):1927.
Malaga A, Vinodh S, (2023) Analysis of factors influencing smart and sustainable manufacturing systems using a multi-criteria decision making tool. In Innovation and Sustainable Manufacturing (pp. 109-124). https://doi.org/10.1016/B978-0-12-819513-0.00002-0
Matt D T, Rauch E, Dallasega P (2014) Mini-factory – A learning factory concept for students and small and medium sized enterprises. Procedia CIRP, 17, 178–183. https://doi.org/10.1016/j.procir.2014.01.057
Mittal S, Khan MA, Romero D, Wuest T (2019a) Building blocks for adopting smart manufacturing. Procedia Manuf 34:978–985. https://doi.org/10.1016/j.promfg.2019.06.098
Mittal S, Khan MA, Romero D, Wuest T (2019b) Smart manufacturing: characteristics, technologies and enabling factors. Proceed the Inst Mech Eng, Part B: J Eng Manuf 233:1342–1361. https://doi.org/10.1177/0954405417736547
Mohammadi V, Minaei S, (2019) Artificial intelligence in the production process. In Engineering tools in the beverage industry. Woodhead Publishing (pp. 27-63). https://doi.org/10.1016/B978-0-12-815258-4.00002-0
Mou Q, Xu Z, Liao H (2016) An intuitionistic fuzzy multiplicative best-worst method for multi-criteria group decision making. Information Sciences, 374, 224-239. https://doi.org/10.1016/j.ins.2016.08.074
Mourtzis D (2024) Industry 4.0 and smart manufacturing. In Manufacturing from Industry 4.0 to Industry 5.0 (pp. 13-61). https://doi.org/10.1016/B978-0-443-13924-6.00002-8
Phuyal S, Bista D, Bista R (2020) Challenges, opportunities and future directions of smart manufacturing: a state of art review. Sustainable Futures 2 (2020): 100023. https://doi.org/10.1016/j.sftr.2020.100023
Qu Y, Xinguo M, Qiu S, Liu Z, Zhang X, Hou Z (2019) Integrating fuzzy Kano model and fuzzy analytic hierarchy process to evaluate requirements of smart manufacturing systems. Concurrent Engineering, 27(3), 201-212. https://doi.org/10.1177/1063293X19845137
Qu Y, Wang Y, Ming X, Chu X (2023) Multi-stakeholder’s sustainable requirement analysis for smart manufacturing systems based on the stakeholder value network approach. Computers & Industrial Engineering, 177, 109043. https://doi.org/10.1016/j.cie.2023.109043
Rauch E, Dallasega P, Unterhofer M (2019) Requirements and barriers for introducing smart manufacturing in small and medium-sized enterprises. IEEE Engineering Management Review, 47(3), 87-94. https://doi.org/10.1109/EMR.2019.2931564
Rauch E, Vickery A R (2020) Systematic analysis of needs and requirements for the design of smart manufacturing systems in SMEs. Journal of Computational Design and Engineering, 7(2), 129-144. https://doi.org/10.1093/jcde/qwaa012
Rezaei J, Best-worst multi-criteria decision-making method, Omega 53 (2015) 49–57. https://doi.org/10.1016/j.omega.2014.11.009
Sharma S, Kumar Kar A, Gupta M P (2021) Unpacking Digital Accountability: Ensuring efficient and answerable e-governance service delivery. In Proceedings of the 14th International Conference on Theory and Practice of Electronic Governance (pp. 260-269). https://doi.org/10.1145/3494193.3494229
Simetinger F, Basl J (2022) A pilot study: An assessment of manufacturing SMEs using a new Industry 4.0 Maturity Model for Manufacturing Small-and Middle-sized Enterprises (I4MMSME). Procedia Computer Science, 200, 1068-1077. https://doi.org/10.1016/j.procs.2022.01.306
Sahoo S, Lo C Y (2022) Smart manufacturing powered by recent technological advancements: A review. Journal of Manufacturing Systems, 64, 236-250. https://doi.org/10.1016/j.jmsy.2022.06.008
Sharma R, Villányi B (2022) Evaluation of corporate requirements for smart manufacturing systems using predictive analytics. Internet of Things, 19, 100554. https://doi.org/10.1016/j.iot.2022.100554
