PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

A Gap Study between Employers’ Expectations in Thailand and Current Competence of Master’s Degree Students in Industrial Engineering under Industry 4.0

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Industry 4.0 is an era in which the manufacturing industry has adopted digital technologies and the Internet to enable smart manufacturing system, machines used in the production now can communicate with each other and exchange information between each other, and the machinery used in the manufacturing process is more modern and precise. Therefore, educational institutions should develop the curriculum to produce qualified graduates with the knowledge required for the Industry 4.0 era, especially Industrial Engineering graduates who are directly related to the industry sector. The purpose of this research is to collect the data for the Master of Industrial Engineering (MSIE) curriculum development. The Analytic Hierarchy Process (AHP) technique is used to rank the indicators of knowledge that is important to the employment of graduates with a master’s degree in Industrial Engineering, and study the gap between the expectations of employers and the ability of the current MSIE students of Khon Kaen University. The results of the study reveal that the first indicators that are most important to the employment of MSIE graduates is the knowledge of Industry 4.0 strategy and the knowledge that the students should have developed are the collaboration of humans and robots, big data analytics, real time data usage and databased decision making.
Rocznik
Strony
50--57
Opis fizyczny
Bibliogr. 26 poz., rys., tab.
Twórcy
  • Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, Thailand
  • Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, Thailand
  • Research unit on System Modelling for Industry, Faculty of Engineering, Khon Kaen University, Thailand
Bibliografia
  • 1. Abdel-Basset, M., Mohamed, M., Smarandache, F., 2018. An Extension of Neutrosophic AHP–SWOT Analysis for Strategic Planning and Decision-Making, Symmetry, 10(4), 116.
  • 2. Bonekamp, L., Sure, M., 2015. Consequences of Industry 4.0 on Human Labour and Work Organisation, Journal of Business and Media Psychology, 6(1), 33-40.
  • 3. Chouhan, S., Mehra, P., Dasot, A., 2017. India’s Readiness for Industry 4.0 – A Focus on Automotive Sector, Confederation of Indian Industry (CII), Grant Thornton-An instinct for growth.
  • 4. Coskun, S., Gençay, E., Kayikci, Y., 2019. Adapting Engineering Education to Industry 4.0 Vision, Technologies, 7(10), 1-13, DOI: 10.3390/technologies7010010
  • 5. Dumitrescu, A., Lima, R., Chattinnawat, W., Savu, T., 2019. Industry 4.0 competencies’ gap analysis. Industry 4.0, 4(3), 138-141.
  • 6. Galankashi, M. R., Helmi, S. A., Hashemzahi, P., 2016. Supplier Selection in Automobile Industry: A Mixed Balanced Scorecard–fuzzy AHP Approach. Alexandria Engineering Journal, 55(1), 93-100.
  • 7. Horvat, D., Stahlecker, T., Zenker, A., Lerch, C., Mladineo, M., 2018. A Conceptual Approach to Analysing Manufacturing Companies’ profiles Concerning Industry 4.0 in Emerging Economies, Procedia Manufacturing, 17, 419-426.
  • 8. Kádárová, J., Kováč, J., Durkáčová, M., Kádárb., G, 2014. Education in Industrial Engineering in Slovakia, Procedia - Social and Behavioral Sciences, 143, 156-162.
  • 9. Lee, Y.C., Wang, Y.C., Chien, C.H., Wu, C.H., Lu, S.C., Tsai, S.B., Dong, W., 2016. Applying Revised Gap Analysis Model in Measuring Hotel Service Quality, SpringerPlus, 5(1), 1191.
  • 10. Leyh, C., Schäffer, T., Bley, K., Forstenhäusler, S., 2016. SIMMI 4.0 – A Maturity Model for Classifying the Enterprise-wide IT and Software Landscape Focusing on Industry 4.0, Proceedings Of The 2016 Federated Conference on Computer Science and Information Systems, 8, 1297–1302, DOI: 10.15439/2016f478
  • 11. Lima, R.M., Mesquita, D., Sousa, R.M., Monteiro, M.T.T., Cunha, J., 2019. Curriculum analysis process: Analysing fourteen industrial engineering programs.
  • 12. Luthra, S., Mangla, S.K., 2018. Evaluating Challenges to Industry 4.0 Initiatives for Supply Chain Sustainability in Emerging Economies, Process Safety and Environmental Protection, 117, 168-179.
  • 13. Machado, C.G., Winroth, M., Carlsson, D., Almström, P., Centerholt, V., Hallin, M., 2019. Industry 4.0 Readiness in Manufacturing Companies: Challenges and Enablers Towards Increased Digitalization, Procedia CIRP, 81, 1113-1118, DOI: 10.1016/j.procir.2019.03.262
  • 14. McKinsey & Company, 2016. Industry 4.0 at McKinsey’s model factories, Retrieved from https://capability-center.mckinsey.com/files/mccn/2017-03/digital_4.0model_factories_brochure_2.pdf
  • 15. Muhisn, Z.A.A., Omar, M., Ahmad, M., Muhisn, S.A., 2015. Team Leader Selection by Using an Analytic Hierarchy Process (AHP) Technique, JSW, 10(10), 1216-1227.
  • 16. Nick, G., Szaller, Á., Bergmann, J., Várgedő, T., 2019. Industry 4.0 Readiness in Hungary: Model, and the First Results in Connection to Data Application, IFAC PaperOnLine, 52(13), 289-294.
  • 17. Patacsil, F.F., Tablatin, C.L.S., 2017. Exploring the Importance of Soft and Hard Skills as Perceived by IT Internship Students and Industry: A gap Analysis. Journal of Technology and Science Education, 7(3), 347-368.
  • 18. Pawar, S.S., Rathod, R.R., 2019. A Decision Support System Using Analytical Hierarchy Process for Student-Teacher-Industry Expectation Perspective: In Computing, Communication and Signal Processing, Springer, Singapore, 523-534.
  • 19. Petruni, A., Giagloglou, E., Douglas, E., Geng, J., Leva, M.C., Demichela, M., 2019. Applying Analytic Hierarchy Process (AHP) to Choose a Human Factors Technique: Choosing the Suitable Human Reliability Analysis Technique for the Automotive Industry, Safety Science, 119, 229-239.
  • 20. Pimentel, C., Silva, H., Dias, M.F., Amorim, M., 2016. Transversal entrepreneurial competencies for youth employability –a GAP analysis. Proceedings of 2100 Projects Association Join Conferences 5.
  • 21. Pinzone, M., Fantini, P., Perini, S., Garavaglia, S., Taisch, M, Miragliotta, G., 2017. Jobs and skills in Industry 4.0: An exploratory research. In IFIP International Conference on Advances in Production Management System, Springer, Cham, 282-288.
  • 22. Ramadi, E., Ramadi, S., Nasr, K., 2016. Engineering Graduates’ skill Sets in the MENA Region: a Gap Analysis of Industry Expectations and Satisfaction, European Journal of Engineering Education, 41(1), 34-52.
  • 23. Sadeghpour, F., Far, M.G., Khah, A.R., Amiri, M.A.A., 2017. Marketing Strategic Planning and Choosing the Right Strategy using AHP Technique (Case Study: Ghavamin Bank Mazandaran), Dutch Journal of Finance and Management, 1(2), 45.
  • 24. Schumacher, A., Erol, S. & Sihn, W., 2016. A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises, procedia CIRP 52, 161-166, DOI: 10.1016/j.procir.2016.07.040
  • 25. Schumacher, A., Nemeth, T., Sihn, W., 2019. Roadmapping Towards Industrial Digitalization based on an Industry 4.0 Maturity Model for Manufacturing Enterprises, Procedia CIRP, 79, 409-414.
  • 26. VDMA’s IMPULS-Stiftung, 2015. Industrie 4.0-readiness, Retrieved from https://industrie40.vdma.org/documents/4214230/5356229/Industrie%204.0%20Readiness%20Study%20English.pdf/f6de92c1-74ed-4790-b6a4-74b30b1e83f0
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e285a9e4-7024-4db6-b3f5-c79b374baa57
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.