شناسایی و رتبه‌بندی عوامل مؤثر بر ارتقای انعطاف پذیری تولید در شرکت‌های کوچک و متوسط تکنولوژی محور بین‌المللی باتوجه‌به صنعت ۴.۰

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد، گروه مدیریت، دانشکده مدیریت و اقتصاد، دانشگاه گیلان، رشت، ایران.

2 استاد، گروه مدیریت، دانشکده مدیریت و اقتصاد، دانشگاه گیلان، رشت، ایران.

3 دانشیار، گروه مدیریت، دانشکده مدیریت و اقتصاد، دانشگاه گیلان، رشت، ایران.

10.48308/jimp.15.2.74

چکیده

مقدمه و اهداف: امروزه به‌منظور رقابت و پاسخگویی به انتظارات روزافزون مشتریان، توجه صنایع تولیدی به سیستم‌های ساخت و تولید پیشرفته ضروری است. انعطاف‌پذیری در تولید یکی از این مفاهیم پیشرفته تولید و عملیات است که توسط برخی صنایع برای بهبود عملکرد و کارایی استفاده می‌شود. انقلاب صنعتی چهارم امکان جمع‌آوری و تجزیه‌وتحلیل مستقل داده‌ها و همچنین تعامل بین محصولات، فرایندها، تأمین‌کنندگان و مشتریان را از طریق اینترنت فراهم می‌کند. ترکیب فناوری‌های صنعت 4.0  با سیستم تولید انعطاف‌پذیر می‌تواند به تولیدکنندگان کمک کند تا سرعت، کارایی و هماهنگی را افزایش دهند. باتوجه ‌به اینکه اکثر شرکت های تولیدی کوچک و متوسط هستند، افزایش انعطاف‌پذیری تولید با هزینه مناسب و ارتقای تولید به بالاترین کیفیت که پاسخگوی نیاز مشتریان باشد، در شرکت‌های کوچک و متوسط، به ویژه شرکت‌های فناوری محور بین‌المللی که بر تجاری‌سازی فناوری­های جدید تمرکز دارند، بیش از گذشته احساس می‌شود. پژوهش انجام شده با دو هدف شناسایی و رتبه‌بندی مهم‌ترین عوامل مؤثر بر انعطاف‌پذیری تولید در شرکت‌های کوچک و متوسط بین‌المللی با فناوری پیشرفته بر اساس صنعت 4.0  انجام شده است.
روش‌ها: پژوهش حاضر از نظر نوع و روش تحقیق آمیخته (کمی و کیفی) است. در بخش کیفی با استفاده از منابع کتابخانه­ای و مرور پیشینه 6 معیار اصلی و 28 زیرمعیار شناسایی شد. پس از شناسایی معیارها و زیرمعیارها، از پرسشنامه دلفی در دو دور برای شناسایی مهم­ترین عوامل استفاده شد. خبرگان برای شناسایی عوامل مؤثر بر افزایش انعطاف‌پذیری تولید در دور اول شامل 14 متخصص و در دور دوم دلفی شامل 11 نفر در زمینه صنعت 4.0  و تولید انعطاف‌پذیر بودند. خبرگان برای رتبه‌بندی معیارها و زیرمعیارها با استفاده از روش سوآرا شامل 21 کارشناس از اساتید دانشگاه و کارشناسان تولید در شرکت‌های بین‌المللی کوچک و متوسط با فناوری پیشرفته انتخاب شدند. نمونه‌ها به روش گلوله­برفی انتخاب شدند. پرسشنامه‌های طراحی شده به صورت الکترونیکی توزیع شد و پاسخ­ها با استفاده از مقیاس لیکرت طراحی شد.
یافته‌­ها: معیارها و زیرمعیارهای شناسایی شده در روش دلفی، جهت رتبه‌بندی در اختیار خبرگان قرار گرفت که باتوجه‌به میانگین وزن اختصاص‌داده‌شده و اهمیت نسبی هر معیار و زیرمعیار، رتبه­ی آنها توسط روش سوآرا شناسایی شد. مهم‌ترین معیارهای شناسایی شده به ترتیب شامل: هوشمندی و یکپارچگی زنجیره تأمین، رباتیک، اینترنت اشیا، داده‌کاوی و رایانش ابری و دوقلوهای دیجیتال می‌باشند. فناوری‌های درحال‌توسعه صنعت 4.0  این پتانسیل را دارند که از طریق معیارها و زیرمعیارهای شناسایی شده در پژوهش، موجب تقویت سیستم‌های تولید انعطاف‌پذیر و بالابردن راندمان تولید صنعتی شوند.
نتیجه‌­گیری: شناسایی عوامل مؤثر در افزایش انعطاف‌پذیری تولید در شرکت‌های کوچک و متوسط فناوری محور بین‌المللی و تجزیه­‌وتحلیل داده­ها پس از رتبه‌بندی با استفاده از روش سوآرا، باهدف شناخت و استفاده مناسب از ابزارهای مدیریتی برای مدیران شرکت­های فناوری محور بین­المللی انجام شده است. ارائه‌ی نتایج  پژوهش به مدیران این شرکت‌ها که بر تحقیق و توسعه تمرکز دارد و تأکید اصلی آن، بر بهره­برداری از دانش فنی و افزایش حضور و مشارکت در بازارهای جهانی است کمک می‌کند که تغییرات مهم و اقدامات جدید را در شرکت‌های تولیدی برای حضور در بازارهای جهانی با هزینه و خطای کمتر  انجام دهند و اجرای موفق‌تری را در جهت پیشرفت کسب‌وکار داشته باشند، از این امکانات در محیط‌های رقابتی پویا و فعال استفاده کرده و در افزایش صادرات و بین‌المللی شدن موفقیت بیشتری کسب کنند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Identifying and Ranking Factors Affecting the Improvement of Manufacturing Flexibility in International High-Tech SMEs Based on Industry 4.0

نویسندگان [English]

  • Samaneh Ghorbani Moghadam 1
  • Mostafa Ebrahimpour Azbari 2
  • Mohammad Rahim Ramazanian 3
1 Master's student, Department of Management, Faculty of Management and Economics, University of Guilan, Rasht, Iran.
2 Professor, Department of Management, Faculty of Management and Economics, University of Guilan, Rasht, Iran.
3 Associate Professor, Department of Management, Faculty of Management and Economics, University of Guilan, Rasht, Iran.
چکیده [English]

Introduction: Nowadays, in order to compete and respond to the growing expectations of customers, attention to advanced manufacturing and production systems is essential. Flexibility in production is one of these advanced production and operations concepts used by some industries to improve performance and efficiency. The Fourth Industrial Revolution enables independent data collection and analysis, as well as interaction between products, processes, suppliers, and customers through the Internet. Combining Industry 4.0 technologies with a flexible manufacturing system can help manufacturers increase speed, efficiency, and coordination. Considering that most manufacturing companies are small and medium-sized enterprises (SMEs), increasing production flexibility at a reasonable cost and upgrading production to the highest quality to meet customer needs is felt more than ever in SMEs, especially international high-tech companies focusing on the commercialization of new technologies. This research was conducted with two objectives: identifying and ranking the most important factors affecting production flexibility in international high-tech SMEs based on Industry 4.0.
Methods: The present research is mixed-method (quantitative and qualitative) in terms of type and methodology. In the qualitative part, six main criteria and twenty-eight sub-criteria were identified through library resources and literature review. After identifying the criteria and sub-criteria, a Delphi questionnaire was used in two rounds to determine the most important factors. In the first round, 14 experts and in the second round, 11 experts in the field of Industry 4.0 and flexible production participated. For ranking the criteria and sub-criteria using the SWARA method, 21 experts—including university professors and production specialists from international high-tech SMEs—were selected. The samples were chosen using the snowball method. The designed questionnaires were distributed electronically, and the responses were collected using a Likert scale.
Results and discussion: The criteria and sub-criteria identified through the Delphi method were provided to experts for ranking. Based on the average weight assigned and the relative importance of each criterion and sub-criterion, their ranking was determined using the SWARA method. The most important identified criteria include: supply chain intelligence and integration, robotics, Internet of Things, data mining and cloud computing, and digital twins. The developing technologies of Industry 4.0 have the potential, through the identified criteria and sub-criteria, to strengthen flexible manufacturing systems and increase industrial production efficiency.
Conclusion:  Identifying the factors affecting increased production flexibility in international high-tech SMEs and analyzing the data after ranking using the SWARA method were conducted with the aim of helping managers of high-tech companies to recognize and apply appropriate management tools. Presenting the results of this research assists managers in making significant changes and implementing new measures in manufacturing companies to enter global markets with lower costs and fewer errors, thereby achieving more successful business development. Utilizing these capabilities in dynamic and competitive environments can also lead to greater success in increasing exports and internationalization.

کلیدواژه‌ها [English]

  • Manufacturing flexibility
  • Fourth Industrial Revolution
  • International high-tech SMEs
  • SWARA technique
  • Delphi method
  1. Abbaszadeh, M. (2011). A reflection on validity and reliability in qualitative research. Applied Sociology, 23(45), 19-34. (In Persian).
  2. Abdulnour, Samir ; Baril ,Chantal. (2022). Implementing Industry 4.0 Principles and Tools in SME. Sustainability. 14(10), 6336.
  3. Agolla, J. E. (2018). Human capital in the smart manufacturing and industry 4.0 revolution. Digital Transformation in Smart Manufacturing, 41–58.
  4. Amid, A., Ghamkhahari, S. (2009). Investigating the effect of information technology on the development of exports of small and medium industries in Iran. Management Perspective, 32, 183-202. (In Persian).
  5. Amini, A., Fatahi, H. (2018). Designing a model for the internationalization of SME’s in nano-based knowledge companies. Journal of Business Management, 10,583-602. (In Persian).
  6. Ammar, M., Haleem, A., Javaid, M., Wail, R., Bah, S. (2021). Improving material quality management and manufacturing organizations system through Industry 4.0 technologies. Materials Today: Proceedings, 45, 5089–5096.
  7. Bazargan, A. (2019). An introduction to qualitative and mixed research methods: common approaches in behavioral sciences. Tehran: Didar Publishing House. (In Persian).
  8. Bejtkovský, J., Rózsa, Z., Mulyaningsih, H. (2018). A phenomenon of digitalization and e-recruitment in business environment. Polish Journal of Management Studies, 18, 58–68.
  9. Bonilla, S., Silva, H., Terra D. Silva, M., Franco Gonçalves, R., Sacomano, J. B. (2018). Industry 4.0 and sustainability implications: a scenario-based analysis of the impacts and challenges. Sustainability, 10(10),3740 .
  10. Buer, S., Strandhagen, O., Chan, F. (2018). The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda. International Journal of Production Research, 56(4):1-17
  11. Davari, A., Rezazadeh, A. (2012). Structural equation modeling with PLS software. Tehran: Jihad University Press. (In Persian).
  12. Ebrahimpour Azbari, M., Moradi, M., Marzban Moghadam, N. (2014). Providing a model for improving the performance of technology-oriented companies based on the ability of supplier integration. Industrial Technology Development Bi-Quarterly, 26, 65-77. (In Persian).
  13. Eloundou, J., Sahnoun, M., Louis, A., Baudr, D., Bensrhair, A. (2015). Evaluation of the routing flexibility of flexible manufacturing system. International Conference on Integrated Design and Production CPI, Tangier, Morocco, Dec. 2015, 1-22.
  14. Erol, S., Jager, A., Hold, P., Ott, K., Sihn, W. (2016). Tangible Industry 4.0: a scenario-based approach to learning for the future of production. Procedia CIRP, 54, 13–18.
  15. Esmaeilian, B., Behdad, S., Wang, B. (2016). The evolution and future of manufacturing: a review. Journal of Manufacturing Systems, 39(1), 79–100.
  16. Esmaeilpour, R., Soleimani, R., Akbari, M., Ebrahimpour, M. (2020). Designing a strategic model for internationalization of Iranian knowledge-based enterprises. Journal of International Business Administration, 8, 83–108.
  17. El Tamimi, A., Abidi, H., Mian, S., Aalam, J. (2011). Analysis of performance measures of flexible manufacturing system. Journal of King Saud University – Engineering Sciences, Volume 24, Issue 2, July 2012, Pages 115-129
  18. Faizi, K., Irandoost, M. (2012). A method for research, decision-making and foresight. Tehran: Publications of Industrial Management Organization.
  19. Frank, A., Dalenogare, L., Ayala, N. (2019). Industry 4.0 technologies: implementation patterns in manufacturing companies. International Journal of Production Economics, 210, 15–26.
  20. Ghobakhloo, M. (2018). The future of manufacturing industry: a strategic roadmap toward Industry 4.0. Journal of Manufacturing Technology Management, 29(6), 910–936.
  21. Hadjielias, E., Christofi, M., Christou, P., Hadjielia Drotarova, M. (2022). Digitalization, agility, and customer value in tourism. Technological Forecasting and Social Change, 175, 121334.
  22. Hafez Nia, M. (2008). An introduction to research methods in human sciences. Tehran: Samt Publications. (In Persian).
  23. Hanelt, A., Bohnsack, R., Marz, D., Antunes, C. (2021). A systematic review of the literature on digital transformation: insights and implications for strategy and organizational change. Journal of Management Studies, Volume58, Issue5, 1159-1197.
  24. He, J., Liu He, X., Liu, X. (2023). Study on the impact and mechanism of industrial internet pilot on digital transformation of manufacturing enterprises. Sustainability, 15(10), 7872.
  25. Hose, K., Amaral, A., Go¨tze, U., Pec, P. (2023). Implementation of flexible manufacturing systems in Africa: multiple case studies in the Gambia and Ghana. Nigerian Journal of Technological Development / Global Journal of Flexible Systems Management, 20(1).
  26. Iranzadeh, S., Shamsi, Y., Taghizadeh, H. (2021). Designing and explaining the model of production flexibility in the food industry. Industrial Management Studies, 19(63), 125-162. (In Persian).
  27. Jacob, H. (1989). Flexibilität und ihre Bedeutung für die Betriebspolitik. Integration und Flexibilität, 15–60.
  28. Javaid, M., Haleem, A., Pratap Singh, R., Suman, R. (2022). Enabling flexible manufacturing system (FMS) through the applications of Industry 4.0 technologies. Internet of Things, 2, 2022, 49-62.
  29. Karabasevic, D., Paunkovic, J., Stanujkic, D. (2016). Ranking of companies according to the indicators of corporate social responsibility based on SWARA and ARAS methods. Serbian Journal of Management, 11(1),43-53.
  30. Keršuliene, V., Zavadskas, E., Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243–258.
  31. Kiani Bakhtiari, A., Mousavi Mohadi, A. (2021). Fourth industrial revolution and the leading fundamental changes. Nesha Alam Magazine, 11(2), 155–163. (In Persian).
  32. Kohne, T., Theisinger, L., Sheriff, J., Weigold, M. (2021). Data and optimization model of an industrial heat transfer station to increase energy flexibility. Energy Informatics, 4, 1–17.
  33. Lucas Santos, D., Brittes, B. G., Fabián, A. N., Germán Frank, A. (2018). The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of Production Economics, 204, Pages 383-394.
  34. Luscinski, S., Ivanov, I. (2020). A simulation study of Industry 4.0 factories based on the ontology on flexibility with using Flexim software. Management and Production Engineering Review, 11(3),74-83
  35. Mohammadpour, A. (2017). Anti-methodology: philosophical backgrounds and practical procedures in qualitative methodology. Second Edition. Qom: Logos Publishing. (In Persian).
  36. Molazadeh Yazdani, B., Poya, A., Tavakoli, A. (2017). Typology of production strategies and introducing its differentiating dimensions. Industrial Management Perspective, 21, 79–96. (In Persian).
  37. Moslemipour, G., Qadirpour, S. (2021). Intelligent design of dynamic deployment of facilities in the random environment of flexible production systems by considering the flexibility of the production route. Perspective of Industrial Management, 11(401), 175. (In Persian).
  38. Noeleen, G. (2013). A taxonomy of manufacturing strategies in manufacturing companies in Ireland. Journal of Manufacturing Technology Management, (2013) 24 (4), 488–510.
  39. Ojstersek, R., Buchmeister, B. (2020). The impact of manufacturing flexibility and multi-criteria optimization on the sustainability of manufacturing systems. Symmetry, 12(1), 157.
  40. Olsen, L., Tomlin, B. (2020). Industry 4.0: opportunities and challenges for operations management. Manufacturing & Service Operations Management, 22, 113–122.
  41. Otrebski, R., Pospisil, D., Engelhardt-Nowitzki, C., Kryvinska, N., Aburaia, M. (2019). Flexibility enhancements in digital manufacturing by means of ontological data modeling. Procedia Computer Science, 155, 296–302.
  42. Piccarozzi, M., Aquilani, B., Gatti, C. (2018). Industry 4.0 in management studies: a systematic literature review. Sustainability, 10(10), 3821.
  43. Poya, A. (2013). The effect of production technology on the competitiveness of production and improvement of commercial performance. Technology Development Management Quarterly, 3. (In Persian).
  44. Pylaeva, I., Podshivalova, M. V., Alola, A., Podshivalov, D. V., Demin, A. (2022). A new approach to identifying high-tech manufacturing SMEs with sustainable technological development: empirical evidence. Journal of Cleaner Production, 363, 132322.
  45. Rajput, S., Bennett, D. (1989). Modular system design and control for flexible assembly. International Journal of Operations & Production Management. 9 (7), 17–29.
  46. Sajid, S., Haleem, A., Bah, J., Mohd Goyal, T., Mittal, M. (2021). Data science applications for predictive maintenance and materials science in context to Industry 4.0. Materials Today: Proceedings, 45, 4898-4905.
  47. Salvador, F., Rungtusanatham, M., Forza, C., Trentin, A. (2007). Mix flexibility and volume flexibility in a build-to-order environment: synergies and trade-offs. International Journal of Operations, 27 (11), 1173–1191.
  48. Sari, W., Herianto, M., Budi, D., Tontow, A. (2023). Social manufacturing on integrated production system: a systematic literature review. Management Systems in Production Engineering, 31(1),18-26
  49. Sassanelli, C., Terzi, S. (2022). The D-BEST reference model: a flexible and sustainable support for the digital transformation of small and medium enterprises. Global Journal of Flexible Systems Management, 23(3), 345–370.
  50. Schröder, C. (2017). The challenges of Industry 4.0 for small and medium-sized enterprises. Friedrich Ebert Stiftung, ISBN: 978-3-95861-543-4.
  51. Sertbaş, A. (2021). Internet of Things: leading the future of manufacturing. 67,108961.
  52. Shivanand, H. K., Benal, M. M., Koti, V. (2009). Flexible manufacturing system. New Age International (P) Ltd. ISBN (13) : 978-81-224-2559-8.
  53. Sima, V., Gheorghe, I., Georgiana Subic, J., Nancu, D. (2020). Influences of the Industry 4.0 revolution on the human capital development and consumer behavior: a systematic review. Sustainability, 12(10), 4035.
  54. Spena, R., Holzner, P., Rauch, E., Vidoni, R., Matt, D. (2016). Requirements for the design of flexible and changeable manufacturing and assembly systems: a SME-survey. Procedia CIRP, 207–212.
  55. Tasc, D., Mejía, G. (2020). Strategies for flexibility in production systems in Industry 4.0: a framework for characterization. International Conference of Production Research – Americas, Springer, Cham, 330–341.
  56. Tavakoli, G., Zahiri, M. (2014). Designing organizational culture segmentation pattern in the fourth generation industrial revolution. Journal of Cultural Management, 16(56), 1-19. (In Persian).
  57. Theorin, A., Bengtsson, K., Provost, J., Lieder, M., Johnsson, C., Lundholm, T., Lennartson, B. (2016). An event-driven manufacturing information system architecture for Industry 4.0. International Journal of Production Research, 55(5).
  58. Upton, D. M. (1994). The management of manufacturing flexibility. California Management Review, 36(2), 72-89.
  59. Walker, J., Childe, S., Wang, Y. (2019). Analysing manufacturing enterprises to identify opportunities for automation and guide implementation. IFAC – International Federation of Automatic Control Conference, 52(13),2273-2278.
  60. Yu, F., Schweisfurth, T. (2020). Industry 4.0 technology implementation in SMEs: a survey in the Danish-German border region. International Journal of Innovation Studies, 4, 76–84.
  61. Yul Lee, J., Soo Yang, Y., Ghauri, P., Park, B. (2022). The impact of social media and digital platforms experience on SME international orientation: the moderating role of COVID-19 pandemic. Journal of International Management, 28(4),
  62. Zolfani, S., Hashemkhani Z., Edmundas, K., Turskis, Z. (2013). Design of products with both international and local perspectives based on Yin-Yang balance theory and SWARA method. Economic Research – Ekonomska Istrazivanja, 26(2), 153–166.