Changhao Zhu
A data-driven soft sensor for quality control.
Email: c.zhu5@ncl.ac.uk
Supervisors
Project description
Industry faces the pressure of reducing production costs and improving product quality. Advanced monitoring and control techniques are important for this.
In process control, hardware instrumentation hinders product quality control. The issues include unavailability or high cost.
Empirical models can overcome these issues. They use process operational data from real industrial processes. They allow us to estimate difficult-to-measure quality variables from easy-to-measure process variables.
This modelling technique is based on historical process data. It has become increasingly popular in chemical processes in recent years. Such data-driven models are effective in reducing the cost of production in industrial processes. They also improve efficiency.
The research will develop a data-driven soft sensor. The sensor will estimate and predict quality variables in chemical processes.
Interests
Process control, machine learning, development of data driven soft sensor and their applications industrial chemical processes.
Qualifications
- BSc, Shandong University, China, 2014
- MSc, Newcastle University, UK, 2016