The chair of logistics & quantitative methods and its industry collaborations
The chair of logistics & quantitative methods and its industry collaborations
Prof. Dr. Richard Pibernik
His research and teaching is focused on quantitative methods for supply chain and logistics management, in particular data-driven approaches that integrate machine learning and traditional optimization models.
He's working on various projects in collaboration with companies like Lufthansa Technik, va-Q-tec and Maisha meds.
va-Q-tec
va-Q-tec
The VIPs insulate around 10 times more efficiently than conventional fiber or foam insulation.
They manufacture passive thermal packaging solutions (containers & boxes) which offer constant temperature conditions typically for 4 to 10 days. The company produces in Germany and assures the highest quality standards.
The efficient technology of va-Q-tec’s products saves valuable energy, for example in transport of pharmaceutical products, as well as in automobiles and aircraft.
The collaboration
Professor Pibernik immediately recognized the opportunity for a fruitful collaboration between the company and his team of researchers. This was the outset of a project to improve the routing, positioning and maintenance of containers based on big data.
Where is a container? Where does it have to be next? When is the next maintenance scheduled or needed? These are important questions, that require and create a lot of data. The team around Professor Pibernik trys to opimize and even create new processes based on the data generated by the containers.
Currently there are five students actively involved in the project. They are working on collecting data and obtaining new insights through its analysis.
Lufthansa
Lufthansa Technik Logistik Services
In the global network of its Logistik Services division, thousands of spare aircraft parts – from standard screws to airplane engines – are moved from place to place each day. However, fluctuations in quantities and demands for ever shorter throughput times make planning and managing these material flows a difficult task, which is nevertheless very important. In order to better manage these tasks, the intention of this scheme is to create a digital image of every material movement, which makes all of the information centrally accessible.
The collaboration
The aim of a 100-day project by LTLS and researchers from Professor Richard Pibernik's team is to improve manpower planning in central goods receiving departments by using large amounts of data on material movements. In connection with this, machine learning techniques are deployed in order to use the data provided to create forecasts and direct proposals for decision making.
Maisha Meds
Maisha Meds
Yet, they often lack the tools required to deliver effective care.
Therefore the company supports the management of pharmacies and helps to purchase high-quality medicine at lower prices.
The idea behind it is to make life saving medicine accessible to everyone, especially to people in less inhabited and less wealthy regions.
The collaboration
The collaboration with Maisha Meds is all about developing new methodologies for pharmacy operations based on data they receive from different pharmacies through Maisha Meds.
These methodologies then build the foundation for innovative managemnet concepts and recommendations for the pharmacies on when and how much to order health care products.
This project means a lot to the chair as it has purpose beyond cost improvement and, hopefully contributes to the well-being of many people.