Victor Vican

• Commonly, methods applied in production planning may lead to production orders flowing across similar sequences of machines within similar periods of time. However, within such spatiotemporal neighbourhoods, interdependency effects among production orders may arise, causing compounding delays. The importance of anticipating interdependencies amongst production orders during production planning is key to accurately predict logistics performance such as lead time or expected delays. This is a challenging task for production planners, as interdependencies arise during operations, are difficult to foresee, and can be caused by a multitude of different factors. Only little research has been carried out to establish a generic and measurable understanding of the root-causes of interdependencies in manufacturing systems. In other research areas, such interdependency effects are explored as a key impact factor on system performance. Particularly in physics, research on granular matter systems has led to the development of multiple theories and concepts of particle-particle interactions, summarised here as Granular Matter Theory (GMT). In this thesis, we draw on these concepts in order to define and measure interdependency effects for manufacturing systems and discover a negative relation between to logistics performance indicators. Furthermore, we provide first evidence on some structural and non-structural impact factors that drive such effects and derive recommendations for practitioners in production planning.