Planning and Scheduling in the Automotive Industry

With practical examples from the automotive industry, the course expands the participants' ability to apply quantitative methods for operational problems. Planning systems in the automotive industry are demonstrated using real examples and problem sizes. The relationships between planning problems and the associated coordination concepts (e.g. hierarchical planning, rolling planning, event-driven) are presented. The implementation of mass customization, strategies for variety reduction, layout and assembly line, sequencing, production program planning, strategic allocation of products to plants and production lines are shown. The course shows the connection between strategic and operational tasks using the latest mathematical modeling for digital production planning. You will learn the introduced methods are applied in modern modeling software (CPLEX, R and Python KI libraries). Practical cases Ramp-up planning for new product introduction in a global production network, MRP for high variety premium production, Exploring the power of option bundling, Aggregate planning and the impact of pricing and capacity planning, Capacity fixing for body-shop planning Methodologies Mixed integer programming for strategic network optimization; Bayesian forecasting, AI-based data fusion and deep learning with neural networks for MRP; Constraint programming for car sequencing.

• Gain an overview and insights on different manufacturing environments for automotive production and supply chain management • Understand modelling strategies to match customer demand and automotive order-to-delivery processes in a flexible production network • Describe and Link product variety to order-fulfillment strategies and understand the impact of product variety on operations • Define Mass customization strategies and their function in different production scenarios • Apply Bayesian forecasting techniques, AI and deep learning models to real-world cases and apply forecast error measurement systems • Understand optimization techniques for manufacturing operations planning and balance production loads with linear programming • Use stochastic models for uncertain data and planning situations • Be able to calculate complex product launch and ramp-up scenarios for automotive production and understand the Management of the Operations Interfaces • Define and apply Material Requirements planning for automotive components and understand the sourcing cost structure and supplier cascade in this industry • Understand the concept of Assembly Lines and be able to apply balancing and sequencing OR approaches.

The assessment takes place in form of a written exam (120 min) at the end of the semester. In the exam students demonstrate that they are able to explain, discuss and critically evaluate specific concepts of operations and supply chain management in the automotive industry. Furthermore, they proof that they can apply the discussed quantitative approaches and assess these approaches in terms of effectiveness and efficiency.

Operations Research and Higher Mathematics

The module consists of lectures with integrated exercises. In the lectures the contents of the module are delivered through presentations and talks. In the integrated exercises students apply their knowledge to solve case assignments. The results are then discussed in class. The students improve the acquired knowledge by studying the suggested literature.