Closing Date

31^st December 2020*

Applicants should contact the primary supervisor, and submit their Expression of Interest (EOI) and Application as soon as possible.

*unless filled earlier

The Research Project

It is often misjudged that the introduction of the word 'autonomous' is the way forward to eliminating human error. However, fully autonomous ships lack the advantage of human recoveries, where humans saved possible catastrophic situations due to technical malfunctions. Intuitively, the fully autonomous level requires complex control systems to eliminate shore supervision, which is not likely shortly. Therefore, constrained autonomy might be most likely, where ships operate with shore supervision, thus establishing a socio-technical system embedded with human error and human recoveries.

In constrained autonomous systems, the operator changes limits or remotely control it until constrained operations resume if the ship needs to override the set parameters. The Human Factors (HF) research community has stated this as a rational and pragmatic approach with humans and technology teaming-up providing safer and effective outcomes. This approach is relatively new and called Human-Autonomy Teaming (HAT), which is increasingly utilised to realise the capabilities of powerful automation systems while gaining acceptance. HAT is defined as the interdependent coupling between one or more human operators and one or more autonomous systems requiring collaboration and coordination to accomplish system and task goals. In this context, Deep Learning (DL) can be integrated for developing autonomous systems, which are identified as agents. These DL agents can perform complex tasks and make decisions based on numerous training trials rather than the use of explicitly constructed or pre-programmed data.

This research project aims to develop a DL algorithm of a human-centred engine-room control agent operating in a HAT environment. Integrating real-operational scenarios into the engine-room control agent requires a profound knowledge of user-context, which manifolds due to various concurrent goals and established human teaming procedures. Therefore, various scenario-based engine-room operational activities will be performed in the engine room simulator of the Australian Maritime College (AMC) for obtaining real-world user context data. The data will be collected in the forms of surveys, observations, focus group interviews and scenario-based simulator data generation. The research will then utilise the elements such as task analysis, hierarchical task analysis, and event sequence diagrams to analyse the data. The findings will be used to train, test, and validate the DL algorithm within the human-centred engine-room control agent. The outcome of this study will contribute to human-centred maritime autonomy and the training and education needs of the shore-based operators.

Eligibility

• Essential skills: deep learning algorithms, data mining and data analytics
• Experience: Matlab and Simulink
• Requirements: technical report and scientific writing skills
• Desirable: experience in human factors and human-centred design, experience on board ships, computer programming and experience in engine room simulator software will be an added advantage

See the following web page for entry requirements: www.utas.edu.au/research/degrees/what-is-a-research-degree

Application Process

Applicants who require more information or are interested in this specific project should first contact the listed Supervisor. Information and guidance on the application process can be found on the Apply Now website.

Information about scholarships is available on the Scholarships webpage.

More Information

Please contact, Dr Apsara Abeysiriwardhane for further information.

Closing Date

31^st December 2020*

Applicants should contact the primary supervisor, and submit their Expression of Interest (EOI) and Application as soon as possible.

*unless filled earlier

The Research Project

Rapid technological development has accelerated industry development to Industry 4.0 concept, where machines are connected more than ever in a collaborative community. Parallel to this, 'Smart Logistics' and 'Logistic 4.0' are emerging in the field of transport and logistics. With these advancements, the logistics in port and maritime supply chains have reached a degree of complexity that the management of port operations need of intelligent analytical methods to support the decision-making process. However, the use of analytical methods during daily operations is found to be problematic to implement without the aid of technological platforms that simplify the required computations. The most common technological platform currently used is the Decision Support System (DSS).

Human Factors (HF) engineering can make a positive contribution to improving the usability of DSS. For DSS, usability is critical and if the system is mismatched with intended user requirements, it leads to poor and fatal decision making as human error is increasing. Therefore, to guarantee a high level of productivity, efficiency, and to make sure DSS reflects usability as good as possible, it is necessary to consider physical, cognitive, and psychosocial HF during the design of DSS, which can be accomplished through Human-Centred Design (HCD) approach.

In the port logistic management context, the HF studies are predominantly focused on physical HF, such as reducing human energy expenditure or fatigue in logistics and supply chain. Very little attention has been paid to the interactions between engineering choices and cognitive and psychosocial factors that influence system performance. Thus, the application of HCD in the design of DSS in port logistics management systems has been overlooked in the past. Besides, it is identified that
re+latively little or no support has been provided for engineers designing DSS systems in terms of HF and how to provide the information in a way that actively supports human decision making.

This research project is aiming to address this gap and develop a framework for integrating HF into the design of DSS for port logistics management systems. Firstly, a systematic literature mapping on the design and development of DSS for port logistics management will be performed to identify the challenges in applying the HCD approach in DSS design. Then, a deeper understanding will be gained of DSS users and user-technology interactions within the port logistics system from psychological and sociological perspectives. This research study will use the Activity Theory as the theoretical foundation considering the port logistics system as a socio-technical system. Perspectives of Activity Theory, distributed cognition, and situated learning have profound reference value in human-technology interaction research, providing insightful understanding about the nature of knowledge and interaction design, particularly how tool mediation could facilitate social interaction.

With such a broad scope, a qualitative, exploratory research approach will be considered appropriate to capture rich, detailed information on the nature of DSS users and their interactions with technology within the port logistics system. The findings will then be used to develop a framework that can be used by DSS system design engineers during the early design phase to integrate the HF requirements to improve usability. The outcome of this research will promisingly contribute to a long-term human-centric vision regarding design and technological innovation in the process of information and the digital revolution, which would expectedly contribute to the safety, efficiency, effectiveness, and sustainability of the port logistics management systems in the long run.

Eligibility

Essential Skills:

• Applicants must be able to demonstrate strong research and analytical skills
• Applicants must already have been awarded a First Class Honours degree or hold equivalent qualifications (e.g. master's degree) or relevant and substantial research experience in an appropriate sector
• Applicants must have knowledge and skills in the following areas: Port logistics management, decision support systems, and user-technology interactions from psychological and sociological perspectives
• Evidence of high level written and communication skills expected for doctoral study

Desirable Skills:

• Experience in Human Factors and Human Centred Design
• Work experience in port logistics management, maritime supply chain management, international organisations, the government or logistics sector is desirable

See the following web page for entry requirements: www.utas.edu.au/research/degrees/what-is-a-research-degree

Application Process

Applicants who require more information or are interested in this specific project should first contact the listed Supervisor. Information and guidance on the application process can be found on the Apply Now website.

Information about scholarships is available on the Scholarships webpage.

More Information

Please contact, Apsara Abeysiriwardhane for further information.

Closing Date

15^th August 2020

Applicants should contact the primary supervisor, and submit their Expression of Interest (EOI) and Application as soon as possible.

The Research Project

With an increase of demand for clean fossil fuel, the production and processing of natural gas have been pushed to ultra-deepwater locations using complex facilities such Floating Liquefied Natural Gas (FLNG) processing facility. Having very little operational experiences of FLNG, the production of LNG using land-based technologies in rough seas presents a high risk of LNG leakage and subsequent events such as fire and vapour cloud explosion (VCE). An integrated impact of LNG spill including dispersion, fire and VCE on structure and personnel is a key aspect for safer FLNG operations. This project integrates the following key safety aspects of an FLNG processing facility;

• Identification of credible spill scenarios in FLNG processing facilities,
• An effective design for early detection system for LNG leakage and its vapour,
• Modelling impacts of multiple pool fires in FLNG processing facilities,
• Assessing the likelihood of Deflagration to detonation transition (DDT) occurrence in FLNG processing facilities, and
• Development of novel methodologies to reduce the likelihood and/or impact of LNG spill and subsequent events

Therefore, the project aims to develop novel frameworks for modelling impacts of LNG spill by incorporating a series of subsequent events and developing methodologies for reducing the likelihood and/or impact of those events. The outcome of this project will provide key insights into the risk assessment and safety management in FLNG processing facilities.

Eligibility

• Open to domestic (Australia and New Zealand) and international candidates
• The degree must be undertaken on a full time basis
• Already awarded First Class Honours Degree or hold equivalent qualifications or relevant and substantial research experience in an appropriate sector
• Able to demonstrate strong research and analytical skills and be first author of at least two published (or accepted) high-ranked journal papers
• Experience with CFD codes/software

Desirable Skills:

• Priority will be given to those who got the first-class honours for his/her bachelor’s degree and master by coursework course with research components and/or publications
• In-depth knowledge of oil and gas production and processing particularly floating processing facilities

See the following web page for entry requirements: www.utas.edu.au/research/degrees/what-is-a-research-degree

Application Process

Applicants who require more information or are interested in this specific project should first contact the listed Supervisor. Information and guidance on the application process can be found on the Apply Now website.

Information about scholarships is available on the Scholarships webpage.

More Information

Please contact, Til Baalisampang for further information.

Closing Date

15^th August 2020*

Applicants should contact the primary supervisor, and submit their Expression of Interest (EOI) and Application as soon as possible.

*unless filled earlier

The Research Project

There is a growing need for implementation of artificial intelligence (AI) in procurement functions as it allows procurement departments to solve complex problems by using smart computer algorithms, generating effective innovation strategies. Digital technologies such as machine learning, deep learning, and neural networks can all be considered as AI which provides a wide range of opportunities for firms to bring innovations faster to the market. The ability of the firms to drive innovations as new value-adding products and services can significantly affect their competitive advantages which cannot be successfully achieved without collaborations with their suppliers.

Supply networks are potentially rich sources of ideas and innovation, and suppliers have been considered as the most important partners in the firms' innovation efforts. This emphasises the importance of procurement in assisting firms to access suppliers' innovation capabilities. Best practices have indicated that AI applications in procurement functions can increasingly facilitate the innovation development process in different ways. For example, through automation and improvement of firms' search capabilities, AI applications provide procurement professionals with additional insights into identifying the highly innovative suppliers and analysing their role in developing more innovative products and services. However, research contributions in exploring the impact of AI applications on supporting procurement decisions for collaborative innovations are extremely limited.

Therefore, there are huge potentials for focusing on procurement functions to stimulate supplier innovations in the era of digital transformation. In this regard, this project investigates the applications of AI in enabling procurement functions to leverage supplier capabilities for the innovation development process.

Eligibility

• Deep understanding of supply chain management and procurement functions
• Understanding of AI and related technologies
• Evidence of high level written and communication skills expected for doctoral study
• Good analytical skills
• Work or research experience in supply chain management

See the following web page for entry requirements: www.utas.edu.au/research/degrees/what-is-a-research-degree

Application Process

Applicants who require more information or are interested in this specific project should first contact the listed Supervisor. Information and guidance on the application process can be found on the Apply Now website.

Information about scholarships is available on the Scholarships webpage.

More Information

Please contact, Hadi Rezaei Vandchali for further information.

Closing Date

15^th July 2020

Applicants should contact the primary supervisor, and submit their Expression of Interest (EOI) and Application as soon as possible.

The Research Project

The purpose of this research is to gain insight into the unsteady loading imparted to lifting surfaces immersed in structured turbulent flows. The study will explore experimentally the dependency on the physical characteristics of the oncoming flow and the hydrofoil geometry. New instrumentation will be developed with an extended range of frequency resolution to provide greater insight into the correlation between the underlying flow physics and the resulting unsteady force spectra.

The main benefit of the outcomes of this project will be to contribute to improved propulsion and control surface design for naval platforms. Reduced vibration and radiated noise will result in improved structural design and signature performance.

Eligibility

Essential Skills:

• Honors degree or equivalent in mathematics, science or engineering
• The successful candidate must be prepared to submit a valid application for Australian Security Clearance (for further information see www.defence.gov.au/security/clearances)

Desirable Skills:

• Expertise in experimental fluid mechanics and advanced data analysis skills

See the following web page for entry requirements: www.utas.edu.au/research/degrees/what-is-a-research-degree

Application Process

Applicants who require more information or are interested in this specific project should first contact the listed Supervisor. Information and guidance on the application process can be found on the Apply Now website.

Information about scholarships is available on the Scholarships webpage.

More Information

Please contact, Paul Brandner for further information.