Dynamic control for in-plant milk-run systems with volatile transport demand

• Applicant: Professor Dr.-Ing. Willibald A. Günthner
• Subject Area: Production Systems, Operations Management, Quality Management and Factory Planning
• Term: from 2015 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 280752532

Recently, transportation systems for in-plant production supply are often organized as in-plant milk-run systems. These systems deliver different materials to various points of use in a single tour with high frequency. In state-of-the-art planning procedures milk-run routes and departure times are planned and fixed long-term assuming constant material demand known well ahead. However, in operational in-plant milk-run systems material demand is volatile in the short term and demand peaks result in expensive exception handling processes. The objective of the research project is to develop a control concept for in-plant milk-run systems, determining routes, departure times and resource allocation dynamically based on current transportation orders and the milk-run systems current state. In contrast to existing planning procedures for milk-run systems, several planning decisions have to be implemented into the control logic. Corresponding decision algorithms are not published and will be developed and evaluated as part of this research. These algorithms continually have to determine, which transportation orders to serve with which resource, on which route and at what time. The aim of this concept is to enable stable system operations even in systems where transportation demand is volatile in the short term and thus avoid costly exception handling procedures. Overall, a reduction of necessary resources is expected in comparison to the static planning scenario due to the resource allocation based on actual transportation orders. Additionally, re-planning of routes and timetables based on long-term changes in demand is obsolete. Furthermore recommendations on typical use cases where the dynamic approach is most beneficial will be derived.

• DFG Programme: Research Grants