Plant-wide master production scheduling in the automotive industry under component blockings: an MILP-approach and a simulation study

Abstract Supply chain disruptions in the automotive industry have been increasingly prevalent, especially in recent years due to various factors such as natural disasters, geopolitical tensions, and the global pandemic. These disruptions have led to shortages of critical components, which in turn require orders containing these components to be blocked for production. Such component blockings can result in production delays and significantly increased production costs. In this paper, we propose a mixed-integer linear programming based short-term master production scheduling approach that strives to balance two contradicting goals in the presence of component blockings: the timely completion of customer orders and the need to maintain a mix of orders in the plant that allows for the construction of a feasible production sequence. Unlike existing approaches for short-term master production scheduling, we use a volume-oriented model formulation and consider the structure of a typical automotive plant, its inventories, and crucial lead times. Furthermore, we anticipate reduced component installation rates due to interdependencies of sequencing rules. In a simulation study, we demonstrate the practical viability of our approach. In particular, in a scenario with multiple component blockings, we show that it considerably reduces the number of sequencing rule violations that can lead to expensive rework or line stoppages while minimizing due date deviation costs.