Supply chain analytics
This program focuses on the design and improvement of supply chains to mitigate risks associated with the collection and storage of data.
Led by Dr Hadi Ghaderi, this research program focuses on the design and improvement of supply chains. With the proliferation of smartphones and connected devices, there has never been a more important time to understand and mitigate the risks associated with the collection, storage and maintenance of data.
Given the challenges associated with today’s unpredictable market, it is critical to make data-driven and reliable supply chain decisions. The recent progress in Artificial Intelligence (AI) and Machine Learning (ML) is enabling us to achieve this objective.
Data science enhances the capability of our supply chain tools by sensing various data sources and providing advanced analytics for smarter decision-making. Observing this growing need, our supply chain analytics program aims to build capability and harness opportunities in three industry-demanded areas.
Real-time supply chain network optimisation
Development of optimisation tools that are data-driven and dynamic (such as dynamic routing in the presence of autonomous vehicles and dynamic pricing for revenue management)
Real-time inventory optimisation
Predictive and prescriptive resource optimisation.
Supply chain visualisation and authentication
Scalable and smart visualisation solutions to enhance supply chain transparency and sustainability
Leveraging supply chain data to build advanced dashboards and data-driven key performance indicators
User behaviour analytics to understand and improve customer journey and loyalty.
Intelligent supply chains
AI-enabled supply chain decision making
Predictive risk modelling for supply chain resilience by benefiting from advanced ML and AI tools.
Swinburne partners with world-first crowdsourced delivery companySwinburne has partnered with Passel, the world’s first crowdsourced delivery company, to develop algorithms to improve its delivery service model.Wednesday 26 June 2019
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