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 | |
| 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 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
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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
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 - Huang, Yueh-Min
A2 - Starcic, Andreja Istenic
A2 - Shadieva, Rustam
PB - Springer Verlag
ER -