A5100748563- Manufacturing Process and Optimization
- Reliability and Maintenance Optimization
- Advanced Computational Techniques and Applications
- Advanced Data Processing Techniques
- Risk and Safety Analysis
- Electrical Fault Detection and Protection
- Engineering and Test Systems
- Urban Planning and Valuation
- Fault Detection and Control Systems
- Probabilistic and Robust Engineering Design
- Advanced machining processes and optimization
- Business Process Modeling and Analysis
- Power System Reliability and Maintenance
- Transportation Planning and Optimization
- Industrial Technology and Control Systems
- Advanced Optimization Algorithms Research
- Product Development and Customization
- Guidance and Control Systems
- Digital Transformation in Industry
- Additive Manufacturing and 3D Printing Technologies
- Advanced Sensor and Control Systems
- Regional Development and Environment
- Optimization and Variational Analysis
Qiongtai Teachers College
2019-2021
Xi'an Jiaotong University
2009-2013
Xi’an University of Posts and Telecommunications
2013
Weatherford College
2001
The manufacturing process of modern equipment becomes very complex due to features such as mass units, multiple machining, and complicated coupling-relationships, posing a big challenge for determining the scheme. This paper addresses by proposing graph theory-based optimization design process. A detailed analysis serial models built according reveals that Hamilton is suitable modeling system. Some model weight assignment functions are extracted quantitative study. Further optimal scheme an...
Process systems are different from discrete manufacturing in that they composed of many interlocking subsystems consist various tightly coupled units. Hence, whenever a small unit subsystem functions badly, it could influence or cause the whole system to function abnormally. Under this circumstance, how locate abnormal failed units will be very formidable task. By introducing Bayesian networks into tracking fault sources process systems, new method source tracing is proposed, and model set...
We consider the problem of multi-objective alignment foundation models with human preferences, which is a critical step towards helpful and harmless AI systems. However, it generally costly unstable to fine-tune large using reinforcement learning (RL), multi-dimensionality, heterogeneity, conflicting nature preferences further complicate process. In this paper, we introduce Rewards-in-Context (RiC), conditions response model on multiple rewards in its prompt context applies supervised...
It is a difficult and valuable research to automatically generate the system model according some rulers desired.So, new auto-modeling method for industrial systems presented.In research, divided into many individual units, mathematical expressions are introduced building model.A series of numbering rules nodes defined in light unit coupling relationships.A data structure designed save information, saved information classified groups certain ruler mapped classification sets.Next, these sets...
At present, electromechanical systems are becoming more and complex, the quality of their key components plays a vital role in reliability whole system. Considering economy, redundant configuration has become an important assurance method for systems. However, there is no good to determine level system reliability, which results over-design or under-configuration. For this reason, redundancy optimization parts proposed, provides theoretical basis design In paper, following aspects studied....