Theme 3. Supply chain integration and information management
Theme 3 aims to transform business practices and performance through the development and integration of innovative new technologies. New sensor technologies enable the collection of smart data across the value chain, providing the ability to record and track products from the forest to the end-user. A key focus of theme 3 is to enhance resource grading, tracking and management by developing mechanisms for the flow of information across a traditionally fragmented forestry sector. This will enable improved resource utilisation, production efficiencies and enable value chain optimisation.
Current projects
Heesung Woo - PhD Candidate
Assoc Prof Paul Turner, Dr Mohammad Taskhiri, Dr Martin Moroni
This project investigates mechanisms within forest industry supply chains to optimise the value and utilisation of eucalypt forest residues for bio-energy and bio-based product markets. The research aims to empirically investigate the availability, quality and feasibility of eucalypt residue utilisation and to produce a multi-objective optimisation of residue utilisation that includes consideration of socio-economic and environmental dimensions within an efficiency supply chain management model. This model will be integrated with existing geographic information systems already being used by Sustainable Timber Tasmania and Private Forests Tasmania. This integration will be presented to users through a web/mobile application that will enable identification of optimal locations for feedstock utilization for bio-energy and/or EWPs. The application will also support decision-making about balancing socio-economic and environmental factors in any specific harvest/haulage operation.
Check out Heesung explain his project below:
Mihai Neagoe - PhD Candidate
Assoc Prof Paul Turner, Assoc Prof Oanh Nyugen, Dr Mohammad Taskhiri, Darrell Clark
This project proposes the implementation and evaluation of an online scheduling tool for the woodchip export terminal at the port of Burnie to improve the traffic flow issues the facility is facing. The project's first stage involved mapping the supply chain and identifying the relevant factors affecting operations at the port. Several potential alternatives to alleviate the issues identified are investigated: eliminating stages from the operational process, traffic smoothing, traffic shifting, contractual incentives, or capacity increases. Demand smoothing was identified as the most versatile and scalable option from these alternatives and was operationalised as a terminal appointment system. The next stage is the implementation of the appointment system at the terminal. Finally, the impact of the system on the supply chain’s performance is compared to the initial situation.
The appointment system is applied on a woodchip supply chain in Tasmania and is the first implementation of a scheduling system for a bulk supply chains as opposed to containerised supply chains. Furthermore, it is expected that the implementation of the tool would reduce the truck queuing time, and therefore supply chain costs originating from the land-side of the operations.
Check out Mihai explain his project below:
Sean Krisanski - PhD Candidate
Assoc Prof Paul Turner, Dr Mohammad Sadegh Taskhiri, Dr Dean Williams
Drones are a cost-effective means of collecting forest data and are conventionally used above the forest canopy. This project seeks to develop an autonomous, unmanned aerial system for mapping the forest from beneath the canopy. The purpose of this approach is to provide a mapping solution for areas of dense undergrowth and dense canopy, where ground-based methods are difficult/hazardous and above canopy methods struggle to penetrate to the stems. The end goal of this project is to be able to autonomously map a difficult region of forest in less time and in far greater detail than can humans, reducing inventory costs and improving worker safety.
Check out Sean explain his project below:
Improving Real-time Vision in Turbid Underwater Environments combining Sonar and an Underwater Video System (UVS)
Dr Mohammad Sadegh Taskhiri, Assoc Prof Paul Turner
Demand for effective and efficient approaches to map, monitor and manage underwater environments continues to grow. Industrial, climatological and environmental activities increasingly require ever-more accurate modelling and analysis of underwater environments. Many technological approaches have already been developed to address challenges imposed by darkness, depth/pressure and salinity. However water turbidity (cloudiness) continues to be a major inhibitor underwater, especially where there is a requirement for real-time data.
This project aims to contribute to the science of methods for data capture and analysis of real-time vision in turbid circumstances. To test these methods the research team have forged collaboration with an industrial partner who is actively engaged in industrial underwater timber harvesting. This project presents a unique opportunity to enhance the activities and advancing the science of real-time vision in turbid waters.
Recent improvements in underwater video systems and in processing algorithms for image filtering and detection suggest a new research opportunity. The plan is to mount a video camera system on the harvester head to capture video-images that will be processed in real-time to provide improved vision clarity in these turbid underwater environments. It is anticipated that this improved vision combined with improved sonar mapping will enable the harvester to locate, manoeuvre and safely harvest submerged tree stems at greater depth than is currently possible.
Developing Predictive Imputation of internal defects in standing Trees using nondestructive techniques
Dr Mohammad Sadegh Taskhiri, Assoc Prof Paul Turner
The unseen internal features of logs from native and plantation forests can affect the product types that their timber can be used for, and this in turn affects the value of the timber and the financial return to forest growers. For both types of forests, challenges remain in being able to identify internal features in a timely and cost-effective manner prior to harvesting. Being able to predict the internal structure of a log means it can be directed to the most appropriate use, thereby increasing resource use efficiency and value.
This current project aims to:
(i) Proof of concept through trials in native and plantation eucalypt forests.
(ii) Build a predictive imputation model for different types of tree species and different growing conditions across Australia.
The field assessment involve using various non-destructive techniques including ultrasonic and Ground Penetrating Radar (GPR) that use and ultrasonic sound and electromagnetic waves respectively to penetrate the internal structure of standing trees. These assessment techniques will assist forest growers to more accurately evaluate the quality of growing stems in the field. A wide selection of growing conditions and forest types will be assessed to generate data that can then be used to generate a software algorithm for predictive imputation of likely internal features within particular forests under particular growing conditions.
