Ful-Chiang Wu
- Management Science and Operations Research top 5%
- Industrial and Manufacturing Engineering top 5%
- Statistics, Probability and Uncertainty top 2%
- Computational Theory and Mathematics top 5%
- Mechanical Engineering
- Topics
- Optimal Experimental Design Methods (15 papers)Manufacturing Process and Optimization (8 papers)Advanced Multi-Objective Optimization Algorithms (8 papers)
- Cited by
- Statistics, Probability and UncertaintyIndustrial and Manufacturing EngineeringManagement Science and Operations Research
In The Last Decade
Ful-Chiang Wu
19 papers receiving 314 citations
Peers
Comparison fields: 5 of 72
- Management Science and Operations Research 173
- Industrial and Manufacturing Engineering 142
- Statistics, Probability and Uncertainty 103
- Computational Theory and Mathematics 93
- Mechanical Engineering 60
Countries citing papers authored by Ful-Chiang Wu
This map shows the geographic impact of Ful-Chiang Wu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ful-Chiang Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ful-Chiang Wu more than expected).
Fields of papers citing papers by Ful-Chiang Wu
This network shows the impact of papers produced by Ful-Chiang Wu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ful-Chiang Wu. The network helps show where Ful-Chiang Wu may publish in the future.
Co-authorship network of co-authors of Ful-Chiang Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Ful-Chiang Wu. A scholar is included among the top collaborators of Ful-Chiang Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ful-Chiang Wu. Ful-Chiang Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | Economical Model of Selecting an Appropriate Sample Size of Experiments | 1 |
| 7 | QUALITY DESIGN OF TAGUCHI’S DIGITAL DYNAMIC SYSTEMS | 2 |
| 8 | 2 | |
| 9 | 46 | |
| 10 | 5 | |
| 11 | Simultaneous Optimization of Robust Design with Quantitative and Ordinal Data | 8 |
| 12 | 0 | |
| 13 | 21 | |
| 14 | 1 | |
| 15 | 16 | |
| 16 | 108 | |
| 17 | 24 | |
| 18 | 39 | |
| 19 | 2 | |
| 20 | 10 |
About Ful-Chiang Wu
Ful-Chiang Wu is a scholar working on Industrial and Manufacturing Engineering, Management Science and Operations Research and Statistics, Probability and Uncertainty, having authored 21 papers that have together received 334 indexed citations. Recurring topics across this work include Optimal Experimental Design Methods (15 papers), Manufacturing Process and Optimization (8 papers) and Advanced Multi-Objective Optimization Algorithms (8 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (103 citations), Industrial and Manufacturing Engineering (142 citations) and Management Science and Operations Research (173 citations). Ful-Chiang Wu has collaborated with scholars based in Taiwan, China and France. Frequent co-authors include Fuh‐Der Chou, Huimei Wang, Fang-Chih Tien, Pei‐Chun Wu, Thomas C. Chuang and Hongming Zhou. Their work appears in journals such as International Journal of Production Research, The International Journal of Advanced Manufacturing Technology and Computers & Industrial Engineering.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.