Enhancing Interoperability in Timber Processing for Automated Defect Detection and Grading

About this project

The timber industry faces significant interoperability challenges due to the use of diverse equipment from multiple suppliers throughout the timber processing lifecycle, which includes harvesting, milling, and distribution. These challenges result in inefficient data flow, inconsistent product quality, and increased operational costs. This research proposal aims to develop a comprehensive interoperability framework that addresses these issues by leveraging advanced artificial intelligence (AI) techniques. The primary objectives of this research are:

•  Analysis of Interoperability Challenges: Conduct a detailed assessment of the current interoperability issues within the timber processing sector, focusing on data exchange limitations, equipment compatibility, and varying analytical capabilities.
• Framework Development: Design and implement a robust interoperability framework that facilitates seamless data exchange among heterogeneous tools and systems used in timber processing, ensuring compatibility across different suppliers and equipment types.
• AI Methodology Application: Apply state-of-the-art AI techniques, such as machine learning algorithms, to enhance the accuracy and efficiency of automated defect detection and grading processes, thereby improving product quality and reducing waste.

Applicants with experience in software modelling and development methods will be highly regarded.


What you’ll do

In this project, you will have access to highly experienced researchers and gain skills in understanding AI and data management techniques in industrial ecosystems. The student will have access to state-of-the-art technology and tools for data analysis, machine learning, and mechanical wood testing, including a unique large dataset created by UniSA STEM that will be instrumental for training and testing AI algorithms. Specialized research centres and laboratories dedicated to timber processing and AI applications will support empirical studies and experimentation, allowing for the implementation of the interoperability framework in real-world scenarios. Close collaboration with industry partners, such as Forest & Wood Products Australia (FWPA) and local timber mills, will provide practical insights and access to real industry datasets, enhancing the relevance of the research. Additionally, the student will benefit from a vibrant community of researchers and peers engaged in similar projects, fostering a supportive atmosphere for academic and professional growth. The research environment will also offer various professional development opportunities, including workshops, seminars, and conferences, enabling the student to present their research, gain feedback, and connect with other professionals in the field.

The PhD applicant will engage in several key activities aimed at enhancing interoperability and product quality in the timber processing industry. They will begin with a systematic literature review to synthesize existing research on interoperability and AI applications, which will inform the development of a robust interoperability framework. The applicant will collaborate with timber mills to conduct field studies, gathering qualitative and quantitative data on current practices and interoperability challenges. They will design and implement the framework, standardizing data formats to facilitate seamless data exchange among diverse equipment. Additionally, the applicant will apply machine learning algorithms to improve automated defect detection and grading processes using a unique dataset from UniSA STEM. Case studies will be conducted in selected timber processing facilities to evaluate the framework's effectiveness in real-world scenarios. Close collaboration with industry partners, including Forest & Wood Products Australia (FWPA), will ensure the research remains relevant and practical. The applicant may also need to travel to various facilities for field studies and attend conferences to present their findings. Overall, these activities will contribute significantly to advancing the timber processing sector.

The project will also include the writing and submission of research papers, and some travel to domestic and international conferences is expected. The industry placement may be possible. There may be opportunity for visits to industry partner subject to project travel cost availability.


Where you’ll be based

The PhD candidate will be primarily based in the Industrial AI Research Centre (IAI), a vibrant multidisciplinary environment of over 100 researchers with an extensive track record in research in applied Artificial Intelligence areas such as knowledge representation and reasoning, autonomous agents, and machine learning. Researchers in the Centre collaborate with industrial partners in a variety of domains. Financial Support

This project is funded for reasonable research expenses. A fee offset for the standard term of the program is available to Australian and New Zealand citizens, and permanent residents of Australia, including permanent humanitarian visa holders.  Additionally, any Australian Aboriginal and/or Torres Strait Islander applicant who holds an offer of admission without a living allowance will be eligible for the Aboriginal Enterprise Research Scholarship. This scholarship is to the value of $52,352 per annum (2025 rate). Any Aboriginal Enterprise Research Scholarship recipient will also receive a fee waiver. Where an international applicant holds an external scholarship or sponsorship a full or partial fee waiver may apply in some circumstances for exceptional applicants. Other international applicants will be required to pay full tuition fees of approximately $44,300 per annum (2025 rates).
 

Eligibility and Selection

This project is open to applications from both Domestic and International applicants.

Applicants must meet the eligibility criteria for entrance into a PhD. 

Additionally, applicants must meet the project selection criteria:

• Experience in software modelling and development methods.

All applications that meet the eligibility and selection criteria will be considered for this project. A merit selection process will be used to determine the successful candidate.

The successful applicant is expected to study full-time but part-time considered in special circumstances, and to be based at our Mawson Lakes Campus in the north of Adelaide. Note that international students on a student visa will need to study full-time.


Essential Dates

Applicants are expected to start in a timely fashion upon receipt of an offer. Extended deferral periods are not available. Applications close on 30 January 2025.