Study level

PhD

Faculty/School

Topic status

We're looking for students to study this topic.

Supervisors

Dr Iman Ashtiani Abdi
Position
Postdoctoral Research Fellow Chemical/Process Engineer
Division / Faculty
Science and Engineering Faculty

Overview

For several years, we've recognised the benefit of a supervisory or advisory support tool for pan stage operations in sugar factories. However, it appears no system is currently operating to the extent where there are strong, beneficial results.

Supervisors and operators currently manage the shift operations with:

  • their knowledge and experience of the process
  • the operational plan for the pan and fugal stations nominated by the production manager.

However, operating the pan and fugal stations optimally has become increasingly complex with heavy financial implications.

To achieve a truly optimal result, management decisions for the stations must happen in relatively short timeframes. This means that compliance with a static operational plan set by the production manager may not be appropriate. Ideally, a production manager should set the production objectives for the shift and the supervisor/operators should make real-time, optimal decisions to meet those objectives.

The pan and fugal stations are an ideal location to initiate progress towards a factory-wide supervisory or advisory system.

Research activities

You will work in a multi-disciplinary team of chemical and mechanical engineers who work closely with Australian sugar mills. Your work will involve experimental measurements, computational simulation and data analysis.

Outcomes

We expect to implement a smart supervisory/advisory control system (SSCS) for pan and fugal station operations. We will demonstrate and evaluate its effectiveness and acceptability by factory operators, supervisors and management using machine learning.

The SSCS will provide advice to supervisors and operators so that early decisions, such as changes to steam rates or allocation of pans to different duties. This will result in improved outcomes while maintaining good operational performance.

Skills and experience

Prior study with knowledge and skills in any of the following will be considered valuable:

  • chemical engineering
  • mechanical engineering (fluid/thermal)
  • data science.

Scholarships

You may be able to apply for a research scholarship in our annual scholarship round.

Annual scholarship round

Contact

Contact the supervisor for more information.