7th December, 2010
Aston University is involved in a €2.79m project to create a computer system that improves goods delivery across large scale European transport networks.
Logistically, major distribution companies can be faced with billions of new statistics each and every month. This includes details such as customer orders, depot deliveries, postal addresses and satellite vehicle tracking.
ADVANCE (Advanced Predictive-Analysis-Based Decision-Support Engine for Logistics) is a computer based information system being created to help collate and analyse such information and through this improve transport network efficiency.
This three year European Commission funded project will produce software capable of monitoring existing logistics for transport networks while also predicting future logistic requirements. It involves the academic partners Computer and Automation Research Institute of the Hungarian Academy of Sciences (Hungary), Aston University in Birmingham, (UK), and the University of Groningen (Netherlands).
The researchers will be working with leading European logistic partner Palletways (Lichfield, UK) and Technology Transfer Systems, (Italy), to design the ADVANCE system. It will analyse all the transport requirements of all the independent haulage companies working within the logistics network, to deploy vehicles in the most efficient way. This will include reducing miles travelled and ensuring lorries are filled to capacity, rather than, as the industry terms it, ‘delivering air’.
The Aston engineering research team consisting of Computer Scientists Anikó Ekárt, Christopher Buckingham, and Philip Welch believe the new system will provide a strategic oversight coupled with instant decision making.
Dr Christopher Buckingham, said; “This system will create a decision-support engine capable of analysing a massive volume of data for companies who can typically accumulate over one billion new items of data each month. This data is generated every minute of every day by thousands of pallets travelling on hundreds of trailers for more than one million customers scattered across hundreds of thousands of postcodes, each with multiple different service requirements.”
Dr Anikó Ekárt, added; “The patterns and dependencies that exist in the data can only be meaningfully processed by intelligent data mining approaches. This system will provide a dual perspective on transport requirements combining instant analysis to guide short-term decisions about lorry deployment as well as longer-term plans for managing the network behaviour as a whole.“
Once the trial period is complete, the analysis software will be made available for any interested companies.
Visit the ADVANCE webpages for further information and regular updates on the project
For further media information please contact Alex Earnshaw, University Communications on 0121 204 4549