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Uncertainty Quantification in Design, Manufacturing and Maintenance of Complex Systems
Topic Information
Dear Colleagues,
There are various uncertainty sources affecting the design, manufacturing, and maintenance of complex engineering systems. In recent decades, uncertainty quantification has demonstrated great potential for scientifically analyzing how the uncertainties affect the performance of products. On the one hand, the uncertainty factors stemming from design, manufacturing, and operation are expected to be thoroughly quantified and considered when designing new products, which is the so-called design under uncertainty. On the other hand, the uncertainty sources contained in the manufacturing process and in the prediction of operational performance are expected to be comprehensively quantified and included for decision making under uncertainty during manufacturing and operation. The purpose of this topic is to present the latest advancements in the field of uncertainty quantification in design, manufacturing, and maintenance. The topic includes but is not limited to:
- Uncertainty quantification and reduction;
- Design under uncertainty;
- Decision making under uncertainty;
- Uncertainty modeling and analysis;
- Model calibration, verification, and validation;
- Risk and reliability analysis;
- Robust/reliability-based design optimization;
- Uncertainty-aware machine learning models;
- Uncertainty quantification in additive manufacturing;
- Confidence-based remaining useful life estimation;
- Uncertainty-aware diagnostics and prognostics;
- Uncertainty-aware battery management systems;
- Probabilistic and non-probabilistic approaches in complex engineering systems;
- Highly efficient uncertainty propagation techniques in complex engineering systems;
- Applications of uncertainty quantification in design, manufacturing, or maintenance.
Dr. Chen Jiang
Dr. Zhenzhong Chen
Dr. Xiaoke Li
Dr. Xiwen Cai
Dr. Zan Yang
Topic Editors
Keywords
- uncertainty quantification
- uncertainty propagation
- risk and reliability
- design under uncertainty
- decision making under uncertainty
- manufacturing uncertainty
- operational uncertainty
- probabilistic and non-probabilistic methods
Participating Journals
| Journal Name | Impact Factor | CiteScore | Launched Year | First Decision (median) | APC |
|---|---|---|---|---|---|
Aerospace
|
2.1 | 3.4 | 2014 | 21.3 Days | CHF 2400 |
Applied Sciences
|
2.5 | 5.3 | 2011 | 18.4 Days | CHF 2400 |
Batteries
|
4.6 | 4.0 | 2015 | 19.7 Days | CHF 2700 |
Energies
|
3.0 | 6.2 | 2008 | 16.8 Days | CHF 2600 |
Journal of Marine Science and Engineering
|
2.7 | 4.4 | 2013 | 16.4 Days | CHF 2600 |
Machines
|
2.1 | 3.0 | 2013 | 15.5 Days | CHF 2400 |
Mathematics
|
2.3 | 4.0 | 2013 | 18.3 Days | CHF 2600 |
Sensors
|
3.4 | 7.3 | 2001 | 18.6 Days | CHF 2600 |
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