Abstract
The purpose of this paper was to develop the capability indicators for R&D staff of CNC machine industry in Taiwan. In order to improve the effectiveness of developing new CNC machine ability and working skills of R&D staff. In the first parts of this study, three experts in the CNC machine industry field were interviewed, and a list of capability indicator was concluded. In the second part of the study, 10 field experts were invited as subjects. Using the Delphi technique, questionnaires are constructed to assess capability indicators for R&D staff of CNC machine industry. In the third of the study, the data collected from the questionnaires were analyzed using a non-parametric Wilcoxon signed rank test. Finally, this study concluded 31 capability indicators under four dimensions for R&D staff of CNC machine industry in Taiwan.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Leu, J.H.: Towards a New Industrial Development Model, Industrial Development Bureau, Ministry of Economic Affairs (2016)
Hiroyuki, C.: Sources of machine-tool industry leadership in the 1990s: overlooked intrafirm factors. In: Center Discussion Paper, pp. 837–839 (2001)
Liu, S.J.: Taiwan government create the capital of intelligence machinery in Taichung, Commercial Times (2017)
Lee, W.B., Li, J.G., Cheung, C.F.: Development of a virtual training workshop in ultra-precision machining. Int. J. Eng. Educ. 18(5), 584–596 (2002)
Lamancusa, J.S., Zayas, J.L., Allen, L., Soyster, L.M., Jorgensen, J.: 2006 Bernard M. gordon prize lecture: the learning factory: industry-partnered active learning. J. Eng. Educ. 97(1), 5–11 (2008)
Taiwan Machine Tools Shaping the Future, September 2016. http://www.imis.ncku.edu.tw/ezfiles/398/1398/img/2728/IMTSAgenda_0721.pdf
Zoran, P., Andrzej, M., Amadeusz, N.: Virtual modelling and simulation of a CNC machine feed drive system. Trans. FAMENA 39(4), 37–54 (2015)
Kao, Y.C., Lee, C.S., Liu, Z.R., Lin, Y.F.: Case study of virtual reality in CNC machine tool exhibition. In: MATEC Web of Conferences, vol. 123 (2017)
Srinivasa Prasad, B., Siva Prasad, D., Sandeep, A., Veeraiah, G.: Condition monitoring of CNC machining using adaptive control. Int. J. Autom. Comput. 10(3), 202–209 (2013)
Parham, D.: Empirical Analysis of the Effects of R&D on Productivity: Implications for Productivity Measurement? vol. 17. OECD Publishing (2009)
Zhu, Y.Q.: Why and how knowledge sharing matters for R&D engineers. R&D Manage. 47(2), 212–223 (2017)
Choi, J.Y., Jeong, S.K., Jung, J.K.: Evolution of technology convergence networks in Korea: Characteristics of temporal changes in R&D according to institution type. PLoS ONE 13(2), 1–23 (2018)
Heike, B.: Companies with R&D abroad make Germany a strong research location. DIW Econ. Bull. 7(46/47), 477–487 (2017)
Heather, G.T., Raymond, H., John, N., Chris, S.: Competency model design and assessment: findings and future directions. J. Public Aff. Educ. 19(1), 141–171 (2013)
Hsu, C.C.: The Delphi technique: making sense of consensus. A Peer Rev. Electron. J. 12(10), 1–8 (2007)
Shyr, W.J., Chiou, C.F., Yang, F.C., Li, P.C.: Energy management competency development based on the Internet of Things (IOT)*. Int. J. Eng. Educ. 33(4), 1380–1385 (2017)
Parkes, M., Reading, C., Stein, S.: The competencies required for effective performance in a university e-learning environment. Australas. J. Educ. Technol. 29(6), 777–791 (2013)
Ball, G., Zaugg, H., Davies, R., Tateishi, P.I., Jensen, C., Magleby, P.: Identification and validation of a set of global competencies for engineering students. Int. J. Eng. Educ. 28(1), 156–168 (2012)
Imam, A., Mohammed, U., Abanyam, M.: On consistency and limitation of paired t-test, sign and wilcoxon sign rank test. IOSR J. Math. 10(1), 1–6 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Chen, DC., Chen, TW. (2018). Developing the Capability Indicators for CNC Machine R&D Staff in Taiwan. In: Wu, TT., Huang, YM., Shadiev, R., Lin, L., Starčič, A. (eds) Innovative Technologies and Learning. ICITL 2018. Lecture Notes in Computer Science(), vol 11003. Springer, Cham. https://doi.org/10.1007/978-3-319-99737-7_23
Download citation
DOI: https://doi.org/10.1007/978-3-319-99737-7_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-99736-0
Online ISBN: 978-3-319-99737-7
eBook Packages: Computer ScienceComputer Science (R0)