Developing the capability indicators for CNC machine R&D staff in Taiwan

Dyi Cheng Chen; Tzu Wen Chen

doi:10.1007/978-3-319-99737-7_23

Developing the capability indicators for CNC machine R&D staff in Taiwan

Dyi Cheng Chen, Tzu Wen Chen

Department of Industrial Education and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Innovative Technologies and Learning - First International Conference, ICITL 2018, Proceedings
Editors	Lin Lin, Ting-Ting Wu, Yueh-Min Huang, Yueh-Min Huang, Andreja Istenic Starcic, Rustam Shadieva
Publisher	Springer Verlag
Pages	223-230
Number of pages	8
ISBN (Print)	9783319997360
DOIs	https://doi.org/10.1007/978-3-319-99737-7_23
Publication status	Published - 2018 Jan 1
Event	1st International Conference on Innovative Technologies and Learning, ICITL 2018 - Portoroz, Slovenia Duration: 2018 Aug 27 → 2018 Aug 30

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11003 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	1st International Conference on Innovative Technologies and Learning, ICITL 2018
Country	Slovenia
City	Portoroz
Period	18-08-27 → 18-08-30

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-99737-7_23

Fingerprint Dive into the research topics of 'Developing the capability indicators for CNC machine R&D staff in Taiwan'. Together they form a unique fingerprint.

Cite this

Chen, D. C., & Chen, T. W. (2018). Developing the capability indicators for CNC machine R&D staff in Taiwan. In L. Lin, T-T. Wu, Y-M. Huang, Y-M. Huang, A. I. Starcic, & R. Shadieva (Eds.), Innovative Technologies and Learning - First International Conference, ICITL 2018, Proceedings (pp. 223-230). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11003 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-99737-7_23

Chen, Dyi Cheng ; Chen, Tzu Wen. / Developing the capability indicators for CNC machine R&D staff in Taiwan. Innovative Technologies and Learning - First International Conference, ICITL 2018, Proceedings. editor / Lin Lin ; Ting-Ting Wu ; Yueh-Min Huang ; Yueh-Min Huang ; Andreja Istenic Starcic ; Rustam Shadieva. Springer Verlag, 2018. pp. 223-230 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{793e42d8aeea42c8930bc3068c0aee0e,

title = "Developing the capability indicators for CNC machine R&D staff in Taiwan",

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.",

author = "Chen, {Dyi Cheng} and Chen, {Tzu Wen}",

year = "2018",

month = jan,

day = "1",

doi = "10.1007/978-3-319-99737-7_23",

language = "English",

isbn = "9783319997360",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "223--230",

editor = "Lin Lin and Ting-Ting Wu and Yueh-Min Huang and Yueh-Min Huang and Starcic, {Andreja Istenic} and Rustam Shadieva",

booktitle = "Innovative Technologies and Learning - First International Conference, ICITL 2018, Proceedings",

address = "Germany",

note = "1st International Conference on Innovative Technologies and Learning, ICITL 2018 ; Conference date: 27-08-2018 Through 30-08-2018",

}

Chen, DC & Chen, TW 2018, Developing the capability indicators for CNC machine R&D staff in Taiwan. in L Lin, T-T Wu, Y-M Huang, Y-M Huang, AI Starcic & R Shadieva (eds), Innovative Technologies and Learning - First International Conference, ICITL 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11003 LNCS, Springer Verlag, pp. 223-230, 1st International Conference on Innovative Technologies and Learning, ICITL 2018, Portoroz, Slovenia, 18-08-27. https://doi.org/10.1007/978-3-319-99737-7_23

Developing the capability indicators for CNC machine R&D staff in Taiwan. / Chen, Dyi Cheng; Chen, Tzu Wen.

Innovative Technologies and Learning - First International Conference, ICITL 2018, Proceedings. ed. / Lin Lin; Ting-Ting Wu; Yueh-Min Huang; Yueh-Min Huang; Andreja Istenic Starcic; Rustam Shadieva. Springer Verlag, 2018. p. 223-230 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11003 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Developing the capability indicators for CNC machine R&D staff in Taiwan

AU - Chen, Dyi Cheng

AU - Chen, Tzu Wen

PY - 2018/1/1

Y1 - 2018/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85053258658&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85053258658&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-99737-7_23

DO - 10.1007/978-3-319-99737-7_23

M3 - Conference contribution

AN - SCOPUS:85053258658

SN - 9783319997360

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 223

EP - 230

BT - Innovative Technologies and Learning - First International Conference, ICITL 2018, Proceedings

A2 - Lin, Lin

A2 - Wu, Ting-Ting

A2 - Huang, Yueh-Min

A2 - Starcic, Andreja Istenic

A2 - Shadieva, Rustam

PB - Springer Verlag

T2 - 1st International Conference on Innovative Technologies and Learning, ICITL 2018

Y2 - 27 August 2018 through 30 August 2018

ER -

Chen DC, Chen TW. Developing the capability indicators for CNC machine R&D staff in Taiwan. In Lin L, Wu T-T, Huang Y-M, Huang Y-M, Starcic AI, Shadieva R, editors, Innovative Technologies and Learning - First International Conference, ICITL 2018, Proceedings. Springer Verlag. 2018. p. 223-230. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-99737-7_23