Einfluss der Reihenfolgeplanung auf den Durchsatz von diskontinuierlichen Bearbeitungsmaschinen am Beispiel einer Längsteilanlage

Abstract

In industrial manufacturing, the efficient use of limited resources is a central objective of production planning. One of the most critical aspects in this context is sequencing, determining the order in which a given set of jobs is to be processed. This is especially true for discontinuous systems such as slitting lines, where complex setup procedures, technical constraints, and interconnected subprocesses like knife assembly robots and strapping machines must be taken into account. An unfavorable sequence can lead to production interruptions, inefficient use of resources, and increased throughput times. The aim of this thesis is therefore to examine various sequencing methods and evaluate their impact on key performance indicators. After introducing the fundamentals of production and sequencing planning and providing a detailed description of the analyzed slitting line, the key technical characteristics influencing sequencing decisions are identified. Subsequently, several sequencing approaches, including four heuristic rules and one evolutionary algorithm, are implemented and tested using a realistic model with three sets of 50 actual production orders each. The performance of these methods is evaluated based on total makespan, the number of tool and recoiler changes, and delays at interconnected process stations. The results demonstrate that significant efficiency improvements can be achieved through targeted sequencing strategies. While the unplanned sequence results in a total processing time of nearly 26 hours, the evolutionary algorithm reduces this to just under 21 hours, an improvement of approximately 20%. Even simple rules like MST or SAS show substantial gains compared to the reference sequence. The study thus highlights the importance of sequencing as an effective tool for optimizing complex production systems.

Date of Award	2025
Original language	German (Austria)
Supervisor	Klaus Altendorfer (Supervisor)