Deutsche Post supports new chair at RWTH Aachen Technical University
High standards of work and quality through co-operation of scientific institutions and industryBonn, 11/05/2003, 10:30 AM CET
At the Rheinisch-Westfälische Technische Hochschule (RWTH) Technical University in Aachen, Germany, a new chair, financially supported by Deutsche Post, will be established as of 01/01/2004 with the name 'Deutsche Post - Lehrstuhl für Optimierung von Distributionsnetzwerken' (Deutsche Post - Chair for Optimising Distribution Networks). The sponsored professorship has initially been agreed for six years and will deepen the long-standing and successful co-operation between Deutsche Post and RWTH Aachen Technical University. Prof. Hans-Jürgen Sebastian, head of Operations Research and Logistics Management, will hold the chair.
During the presentation both partners emphasised the special importance of the joint research and its positive practical consequences. 'In Germany and also world-wide we hold a leading position with regard to our high standards of work and quality in the mail business. This is not least thanks to the use of up-to-date scientific methods,' said Dr Hans-Dieter Petram, Board Member at Deutsche Post and responsible for the Corporate Division MAIL.
Prof. Burkhart Rauhut, chancellor at RWTH Aachen Technical University, referred to the numerous company successes as a result of working together closely with the technical university's research areas: 'Successful companies distinguish themselves these days by entering into partnerships with scientific institutions. This is the only way to implement innovative scientific uses quickly and purposefully.'
The example of redesigning mail delivery routes clearly shows how complicated it is to adjust distribution networks, for example, to different shipment volumes. Deutsche Post uses its self-established GeoDatenZentrale as an extensive data hub for regional planning instruments. A database with more than 2.4 million data records is kept up-to-date with all of Germany's streets and house numbers. During previous years, significant optimisation successes have already been achieved with the help of these data.