Integrated production planning of orders with priorities and due dates in the automotive industry

This paper addresses the integrated production planning problem by developing a mixed integer mathematical optimisation model (MIP). A numerical study using data from an OEM (Original Equipment Manufacturer) assembly plant is conducted. The study underlines the model’s ability to coordinate planned inbound and outbound logistics activities with the OEM assembly plant’s production plan. Our model enables us to handle disruptions in a supply chain (e.g., variations in lead times, shortages, and an increase in supply costs) in a coordinated way with an end-to-end perspective, including supply, distribution and production activities, to minimise the overall cost of operations, based on extensive data. Our aim is to provide practical guidance for the performance of operations (in terms of logistics, emergency shipments -thus emissions, leading to sustainable operations, inventory reduction and capacity utilisation) as well as improving supply chain agility (how to best cope with disruptions arising in inbound/outbound operations, and to ensure stability in production). Results indicate that the production plan provided by our model improves the adherence to release dates of 35% of the manufacturing orders compared to the current industrial tool used by the car manufacturer and reduces the holding cost of components by 80% on the studied horizon. • The research refers to real challenges facing the Automotive Industry in production planning. • Integrating inbound and outbound capacities in production planning improves the performance of supply chains. • We introduce a mixed integer linear programming model to optimize the production plan while considering inbound and outbound capacities. • We compare the performance of the current production planning method at Renault to our integrated planning method using data.